[3Commas] HA & MAHA & MA
🔷What it does: This tool is designed to test a trend-following strategy using Heikin Ashi candles and moving averages. It enters trades after pullbacks, aiming to let profits run once the risk-to-reward ratio reaches 1:1 while securing the position.
🔷Who is it for: It is ideal for traders looking to compare final results using fixed versus dynamic take profits by adjusting parameters and trade direction—a concept applicable to most trading strategies.
🔷How does it work: We use moving averages to define the market trend, then wait for opposite Heikin Ashi candles to form against it. Once these candles reverse in favor of the trend, we enter the trade, using the last swing created by the pullback as the stop loss. By applying the breakeven ratio, we protect the trade and let it run, using the slower moving average as a trailing stop.
A buy signal is generated when:
The previous candle is bearish (ha_bear ), indicating a pullback.
The fast moving average (ma1) is above the slow moving average (ma2), confirming an uptrend.
The current candle is bullish (ha_bull), showing trend continuation.
The Heikin Ashi close is above the fast moving average (ma1), reinforcing the bullish bias.
The real price close is above the open (close > open), ensuring bullish momentum in actual price data.
The signal is confirmed on the closed candle (barstate.isconfirmed) to avoid premature signals.
dir is undefined (na(dir)), preventing repeated signals in the same direction.
A sell signal is generated when:
The previous candle is bullish (ha_bull ), indicating a temporary upward move before a potential reversal.
The fast moving average (ma1) is below the slow moving average (ma2), confirming a downtrend.
The current candle is bearish (ha_bear), showing trend continuation to the downside.
The Heikin Ashi close is below the fast moving average (ma1), reinforcing bearish pressure.
The real price close is below the open (close < open), confirming bearish momentum in actual price data.
The signal is confirmed after the candle closes (barstate.isconfirmed), avoiding premature entries.
dir is undefined (na(dir)), preventing consecutive signals in the same direction.
In simple terms, this setup looks for trend continuation after a pullback, confirming entries with both Heikin Ashi and real price action, supported by moving average alignment to avoid false signals.
If the price reaches a 1:1 risk-to-reward ratio, the stop will be moved to the entry point. However, if the slow moving average surpasses this level, it will become the new exit point, acting as a trailing stop
🔷Why It’s Unique
Easily visualizes the benefits of using risk-to-reward ratios when trading instead of fixed percentages.
Provides a simple and straightforward approach to trading, embracing the "keep it simple" concept.
Offers clear visualization of DCA Bot entry and exit points based on user preferences.
Includes an option to review the message format before sending signals to bots, with compatibility for multi-pair and futures contract pairs.
🔷 Considerations Before Using the Indicator
⚠️Very important: The indicator must be used on charts with real price data, such as Japanese candlesticks, line charts, etc. Do not use it on Heikin Ashi charts, as this may lead to unrealistic results.
🔸Since this is a trend-following strategy, use it on timeframes above 4 hours, where market noise is reduced and trends are clearer. Also, carefully review the statistics before using it, focusing on pairs that tend to have long periods of well-defined trends.
🔸Disadvantages:
False Signals in Ranges: Consolidating markets can generate unreliable signals.
Lagging Indicator: Being based on moving averages, it may react late to sudden price movements.
🔸Advantages:
Trend Focused: Simplifies the identification of trending markets.
Noise Reduction: Uses Heikin Ashi candles to identify trend continuation after pullbacks.
Broad Applicability: Suitable for forex, crypto, stocks, and commodities.
🔸The strategy provides a systematic way to analyze markets but does not guarantee successful outcomes. Use it as an additional tool rather than relying solely on an automated system.
Trading results depend on various factors, including market conditions, trader discipline, and risk management. Past performance does not ensure future success, so always approach the market cautiously.
🔸Risk Management: Define stop-loss levels, position sizes, and profit targets before entering any trade. Be prepared for potential losses and ensure your approach aligns with your overall trading plan.
🔷 STRATEGY PROPERTIES
Symbol: BINANCE:BTCUSDT (Spot).
Timeframe: 4h.
Test Period: All historical data available.
Initial Capital: 10000 USDT.
Order Size per Trade: 1% of Capital, you can use a higher value e.g. 5%, be cautious that the Max Drawdown does not exceed 10%, as it would indicate a very risky trading approach.
Commission: Binance commission 0.1%, adjust according to the exchange being used, lower numbers will generate unrealistic results. By using low values e.g. 5%, it allows us to adapt over time and check the functioning of the strategy.
Slippage: 5 ticks, for pairs with low liquidity or very large orders, this number should be increased as the order may not be filled at the desired level.
Margin for Long and Short Positions: 100%.
Indicator Settings: Default Configuration.
MA1 Length: 9.
MA2 Length: 18.
MA Calculations: EMA.
Take Profit Ratio: Disable. Ratio 1:4.
Breakeven Ratio: Enable, Ratio 1:1.
Strategy: Long & Short.
🔷 STRATEGY RESULTS
⚠️Remember, past results do not guarantee future performance.
Net Profit: +324.88 USDT (+3.25%).
Max Drawdown: -81.18 USDT (-0.78%).
Total Closed Trades: 672.
Percent Profitable: 35.57%.
Profit Factor: 1.347.
Average Trade: +0.48 USDT (+0.48%).
Average # Bars in Trades: 13.
🔷 HOW TO USE
🔸 Adjust Settings:
The default values—MA1 (9) and MA2 (18) with EMA calculation—generally work well. However, you can increase these values, such as 20 and 40, to better identify stronger trends.
🔸 Choose a Symbol that Typically Trends:
Select an asset that tends to form clear trends. Keep in mind that the Strategy Tester results may show poor performance for certain assets, making them less suitable for sending signals to bots.
🔸 Experiment with Ratios:
Test different take profit and breakeven ratios to compare various scenarios—especially to observe how the strategy performs when only the trade is protected.
🔸This is an example of how protecting the trade works: once the price moves in favor of the position with a 1:1 risk-to-reward ratio, the stop loss is moved to the entry price. If the Slow MA surpasses this level, it will act as a trailing stop, aiming to follow the trend and maximize potential gains.
🔸In contrast, in this example, for the same trade, if we set a take profit at a 1:3 risk-to-reward ratio—which is generally considered a good risk-reward relationship—we can see how a significant portion of the upward move is left on the table.
🔸Results Review:
It is important to check the Max Drawdown. This value should ideally not exceed 10% of your capital. Consider adjusting the trade size to ensure this threshold is not surpassed.
Remember to include the correct values for commission and slippage according to the symbol and exchange where you are conducting the tests. Otherwise, the results will not be realistic.
If you are satisfied with the results, you may consider automating your trades. However, it is strongly recommended to use a small amount of capital or a demo account to test proper execution before committing real funds.
🔸Create alerts to trigger the DCA Bot:
Verify Messages: Ensure the message matches the one specified by the DCA Bot.
Multi-Pair Configuration: For multi-pair setups, enable the option to add the symbol in the correct format.
Signal Settings: Enable whether you want to receive long or short signals (Entry | TP | SL), copy and paste the the messages for the DCA Bots configured.
Alert Setup:
When creating an alert, set the condition to the indicator and choose "alert() function call only.
Enter any desired Alert Name.
Open the Notifications tab, enable Webhook URL, and paste the Webhook URL.
For more details, refer to the section: "How to use TradingView Custom Signals".
Finalize Alerts: Click Create, you're done! Alerts will now be sent automatically in the correct format.
🔷 INDICATOR SETTINGS
MA 1: Fast MA Length
MA 2: Slow MA Length
MA Calc: MA's Calculations (SMA,EMA, RMA,WMA)
TP Ratio: This is the take profit ratio relative to the stop loss, where the trade will be closed in profit.
BE Ratio: This is the breakeven ratio relative to the stop loss, where the stop loss will be updated to breakeven or if the MA2 is greater than this level.
Strategy: Order Type direction in which trades are executed.
Use Custom Test Period: When enabled signals only works in the selected time window. If disabled it will use all historical data available on the chart.
Test Start and End: Once the Custom Test Period is enabled, here you select the start and end date that you want to analyze.
Check Messages: Enable the table to review the messages to be sent to the bot.
Entry | TP | SL: Enable this options to send Buy Entry, Take Profit (TP), and Stop Loss (SL) signals.
Deal Entry and Deal Exit : Copy and paste the message for the deal start signal and close order at Market Price of the DCA Bot. This is the message that will be sent with the alert to the Bot, you must verify that it is the same as the bot so that it can process properly so that it executes and starts the trade.
DCA Bot Multi-Pair: You must activate it if you want to use the signals in a DCA Bot Multi-pair in the text box you must enter (using the correct format) the symbol in which you are creating the alert, you can check the format of each symbol when you create the bot.
👨🏻💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented.
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The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
스크립트에서 "stop loss"에 대해 찾기
Enhanced Bollinger Bands Strategy with SL/TP// Title: Enhanced Bollinger Bands Strategy with SL/TP
// Description:
// This strategy is based on the classic Bollinger Bands indicator and incorporates Stop Loss (SL) and Take Profit (TP) levels for automated trading. It identifies potential long and short entry points based on price crossing the lower and upper Bollinger Bands, respectively. The strategy allows users to customize several parameters to suit different market conditions and risk tolerances.
// Key Features:
// * **Bollinger Bands:** Uses Simple Moving Average (SMA) as the basis and calculates upper and lower bands based on a user-defined standard deviation multiplier.
// * **Customizable Parameters:** Offers extensive customization, including SMA length, standard deviation multiplier, Stop Loss (SL) in pips, and Take Profit (TP) in pips.
// * **Long/Short Position Control:** Allows users to independently enable or disable long and short positions.
// * **Stop Loss and Take Profit:** Implements Stop Loss and Take Profit levels based on pip values to manage risk and secure profits. Entry prices are set to the band levels on signals.
// * **Visualizations:** Provides options to display Bollinger Bands and entry signals on the chart for easy analysis.
// Strategy Logic:
// 1. **Bollinger Bands Calculation:** The strategy calculates the Bollinger Bands using the specified SMA length and standard deviation multiplier.
// 2. **Entry Conditions:**
// * **Long Entry:** Enters a long position when the closing price crosses above the lower Bollinger Band and the `Enable Long Positions` setting is enabled.
// * **Short Entry:** Enters a short position when the closing price crosses below the upper Bollinger Band and the `Enable Short Positions` setting is enabled.
// 3. **Exit Conditions:**
// * **Stop Loss:** Exits the position if the price reaches the Stop Loss level, calculated based on the input `Stop Loss (Pips)`.
// * **Take Profit:** Exits the position if the price reaches the Take Profit level, calculated based on the input `Take Profit (Pips)`.
// Input Parameters:
// * **SMA Length (length):** The length of the Simple Moving Average used to calculate the Bollinger Bands (default: 20).
// * **Standard Deviation Multiplier (mult):** The multiplier applied to the standard deviation to determine the width of the Bollinger Bands (default: 2.0).
// * **Enable Long Positions (enableLong):** A boolean value to enable or disable long positions (default: true).
// * **Enable Short Positions (enableShort):** A boolean value to enable or disable short positions (default: true).
// * **Pip Value (pipValue):** The value of a pip for the traded instrument. This is crucial for accurate Stop Loss and Take Profit calculations (default: 0.0001 for most currency pairs). **Important: Adjust this value to match the specific instrument you are trading.**
// * **Stop Loss (Pips) (slPips):** The Stop Loss level in pips (default: 10).
// * **Take Profit (Pips) (tpPips):** The Take Profit level in pips (default: 20).
// * **Show Bollinger Bands (showBands):** A boolean value to show or hide the Bollinger Bands on the chart (default: true).
// * **Show Entry Signals (showSignals):** A boolean value to show or hide entry signals on the chart (default: true).
// How to Use:
// 1. Add the strategy to your TradingView chart.
// 2. Adjust the input parameters to optimize the strategy for your chosen instrument and timeframe. Pay close attention to the `Pip Value`.
// 3. Backtest the strategy over different periods to evaluate its performance.
// 4. Use the `Enable Long Positions` and `Enable Short Positions` settings to customize the strategy for specific market conditions (e.g., only long positions in an uptrend).
// Important Notes and Disclaimers:
// * **Backtesting Results:** Past performance is not indicative of future results. Backtesting results can be affected by various factors, including market volatility, slippage, and transaction costs.
// * **Risk Management:** This strategy is provided for informational and educational purposes only and should not be considered financial advice. Always use proper risk management techniques when trading. Adjust Stop Loss and Take Profit levels according to your risk tolerance.
// * **Slippage:** The strategy takes into account slippage by specifying a slippage parameter on the `strategy` declaration. However, real-world slippage may vary.
// * **Market Conditions:** The performance of this strategy can vary significantly depending on market conditions. It may perform well in trending markets but poorly in ranging or choppy markets.
// * **Pip Value Accuracy:** **Ensure the `Pip Value` is correctly set for the specific instrument you are trading. Incorrect pip value will result in incorrect stop loss and take profit placement.** This is critical.
// * **Broker Compatibility:** The strategy's performance may vary depending on your broker's execution policies and fees.
// * **Disclaimer:** I am not a financial advisor, and this script is not financial advice. Use this strategy at your own risk. I am not responsible for any losses incurred while using this strategy.
Briss Thorn XtremeStrategy Description: Briss Thorn Xtreme
The Briss Thorn Xtreme is an innovative trading strategy designed to identify and capitalize on opportunities in the forex market through advanced technical analysis and dynamic risk management. This strategy combines calculations based on RSI and ATR with time and day filters, providing customized signals and real-time alerts via Discord. Ideal for traders seeking a structured and highly customizable methodology, Briss Thorn Xtreme integrates enhanced visual tools for efficient trade management.
Key Features:
RSI and ATR-Based Signals: Utilizes smoothed RSI and ATR calculations to identify trends and measure volatility, allowing for more precise detection of buy and sell opportunities.
Dynamic Stop-Loss (SL) and Take-Profit (TP) Levels: Automatically calculates SL and TP levels based on market volatility, dynamically adjusting to optimize risk management.
Advanced Discord Integration: Sends detailed alerts to your Discord channel, including information such as the asset, signal time, entry price, and SL/TP levels, facilitating real-time decision-making.
Complete Customization: Allows users to adjust key parameters such as RSI periods, smoothing factors, liquidity thresholds, trading schedules, and operation days, adapting to different trading styles and market conditions.
Enhanced Chart Visualization: Includes visual elements like candle color changes based on trend, colored boxes for SL and TP, and a summary table of recent trades, enabling quick market interpretation.
Day and Time Operation Filters: Enables selection of specific days of the week and time slots during which signals are generated, optimizing market exposure and avoiding periods of low liquidity or unwanted high volatility.
Trade Summary: Displays a summary of the last three trades directly on the chart, indicating whether TP or SL was reached, aiding in strategy performance evaluation.
Customizable Alert Messages: Allows customization of messages sent to Discord for buy and sell signals, tailoring them to your specific preferences and requirements.
Additional Visual Tools: Highlights the operational range on the chart during permitted trading hours and colors candles based on the current trend (bullish, bearish, or neutral), enhancing visibility and decision-making.
How the Strategy Works:
Technical Indicators Calculation:
- RSI (Relative Strength Index) : Calculates RSI with a defined period and smooths it using an Exponential Moving Average (EMA) to obtain a more stable and reliable signal.
- ATR (Average True Range) : Calculates ATR adjusted by a rapid liquidity factor to measure the current market volatility, thereby determining the strength of the trend.
Generating Buy and Sell Signals:
- Buy Signal: A buy signal is generated when the liquidity index surpasses the short liquidity level, indicating potential accumulation and an upward trend.
- Sell Signal: A sell signal is generated when the liquidity index falls below the long liquidity level, indicating potential distribution and a downward trend.
- Operation Conditions: Signals are only generated on selected days and times, avoiding periods of low liquidity or unwanted high volatility.
Dynamic SL and TP Levels Calculation:
- Stop-Loss (SL) and Take-Profit (TP): SL and TP levels are calculated based on the entry price and a defined number of ticks, automatically adjusting to market volatility to optimize risk management.
- SL and TP Visualization: Colored boxes are drawn on the chart for a clear visual reference of SL and TP levels, facilitating trade management.
Automatic Execution and Alerts:
- Order Execution: Upon signal generation, the strategy automatically executes a market order (buy or sell).
- Discord Alerts: Detailed alerts are sent to the configured Discord channel, providing essential information for swift decision-making, including asset, signal time, entry price, current volatility (ATR), and trend direction.
Trade Management and Monitoring:
- Trade Summary: A table on the chart displays a summary of the last three trades (Today, Yesterday, Day Before Yesterday), indicating whether TP or SL was reached, allowing real-time performance evaluation.
- Automatic Trade Closure: The strategy automatically closes trades upon reaching the established SL or TP levels, ensuring efficient risk management and preventing excessive losses.
Additional Visualization:
- Candle Coloring by Trend: Candles are colored based on the current trend (bullish, bearish, or neutral), facilitating quick identification of market direction.
- Operational Range Highlighting: The chart background is colored during permitted trading hours, highlighting active periods of the strategy and enhancing trade visibility.
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Strategy Properties (Important)
This backtest is conducted on M17 EURUSD using the following backtesting properties:
Initial Capital: $1000
Order Size: 1% of capital
Commission: $0.20 per order
Slippage: 1 tick
Pyramiding: 1 order
Price Verification for Limit Orders: 0 ticks
Recalculate on Order Execution: Enabled
Recalculate on Every Tick: Enabled
Recalculate After Order Execution: Enabled
Bar Magnifier for Backtesting Precision: Enabled
These properties ensure a realistic preview of the backtesting system. Note that default properties may vary for different reasons:
Order Size: It is essential to calculate the contract size according to the traded asset and desired risk level.
Commission and Slippage: These costs may vary depending on the market and instrument; there is no default value that guarantees realistic results.
All users are strongly recommended to adjust the properties within the script settings to align them with their trading accounts and platforms, ensuring that strategy results are realistic.
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Backtesting Results:
- Net Profit: $327.90 (32.79%)
- Total Closed Trades: 162
- Profit Percentage: 35.80%
- Profit Factor: 1.298
- Maximum Drawdown: $146.70 (10.27%)
- Average per Trade: $2.02 (0.02%)
- Average Bars per Trade: 22
These results were obtained under the mentioned conditions and properties, providing an overview of the strategy's historical performance.
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Interpretation of Results:
- The strategy has demonstrated profitability over the analyzed period, albeit with a success rate of 32.79%, indicating that success depends on a favorable risk-reward ratio.
- The profit factor of 1.298 suggests that total gains exceed total losses by this proportion.
- It is crucial to consider the maximum drawdown of 10.27% when evaluating the strategy's suitability to your risk tolerance.
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Risk Warning:
Trading with leveraged financial instruments involves a high level of risk and may not be suitable for all investors. Before deciding to trade, you should carefully consider your investment objectives, level of experience, and risk tolerance. Past performance does not guarantee future results. It is essential to perform additional testing and adjust the strategy according to your needs.
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What Makes This Strategy Original?
Unique RSI and Liquidity Focus: Unlike conventional strategies, Briss Thorn Xtreme focuses on combining RSI analysis with liquidity parameters to reflect institutional activity and macroeconomic events that may influence the market.
Advanced Technological Integration: The combination of automatic execution and customized alerts via Discord provides an efficient and modern tool for active traders.
Customization and Adaptability: The wide range of adjustable parameters allows the strategy to adapt to different assets, time zones, and trading styles, offering flexibility and complete user control.
Enhanced Visual Tools: Integrated visual elements, such as candle coloring, SL/TP boxes, and summary tables, facilitate quick market interpretation and informed decision-making.
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Additional Considerations
Continuous Testing and Optimization: Users are advised to perform additional backtests and optimize parameters based on their own observations and requirements.
Complementary Analysis: Use this strategy in conjunction with other indicators and fundamental analysis tools to reinforce decision-making and confirm generated signals.
Rigorous Risk Management: Ensure that SL and TP levels, as well as position sizes, are aligned with your risk management plan to avoid excessive losses.
Updates and Support: I am committed to providing updates and improvements based on community feedback. For inquiries or suggestions, feel free to contact me.
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Example Configuration
Assuming you want to use the strategy with the following parameters:
Discord Webhook: Your unique Discord Webhook
RSI Period: 6
RSI Smoothing Factor: 5
Rapid Liquidity Factor: 5
Liquidity Threshold: 5
SL Ticks: 100
TP Ticks: 250
SL/TP Box Width: 25 bars
Trading Days: Monday, Tuesday, Wednesday, Thursday, Friday
Trading Hours: Start at 8:00, End at 11:00
Simulated Initial Capital: $1000
Risk per Trade in Simulation: 1% of capital
Slippage and Commissions in Simulation: 1 tick slippage and $0.20 commission per trade
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Conclusion
The Briss Thorn Xtreme strategy offers an innovative approach by combining advanced technical analysis with dynamic risk management and modern technological tools. Its original and adaptable design makes it a valuable tool for traders looking to diversify their methods and capitalize on opportunities based on less conventional patterns. Ready for immediate implementation in TradingView, this strategy can enhance your trading arsenal and contribute to a more informed and structured approach in your operations.
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Final Disclaimer:
Financial markets are volatile and can present significant risks. This strategy should be used as part of a comprehensive trading approach and does not guarantee positive results. It is always advisable to consult with a professional financial advisor before making investment decisions.
Pivot High/Low [s3]This is a technical analysis tool that identifies significant price pivot points (highs and lows) in the market. It looks for both major and minor pivot points, which can help traders identify potential support and resistance levels, trend reversals, and breakout opportunities.
How Pivot Points Are Calculated:
The indicator uses a straightforward "higher than everything around it" or "lower than everything around it" approach:
For Pivot Highs:
- The indicator looks at a specific bar and compares it to bars before and after it
- For a major pivot high: It checks 50 bars to the left and 20 bars to the right
- If the bar's high price is higher than ALL bars within this range, it's marked as a pivot high
- Think of it like a mountain peak - it needs to be the highest point compared to everything around it
For Pivot Lows:
- Same concept but reversed - looking for valleys instead of peaks
- Checks the same ranges (50 left, 20 right)
- The bar's low price must be lower than ALL surrounding bars
- Like finding the bottom of a valley - it needs to be the lowest point in the area
Key Features:
1. Two types of pivot points:
- Major pivots (using longer lookback periods of 50 bars left, 20 bars right)
- Minor pivots (using half the lookback periods - 25 left, 10 right)
2. Visual elements:
- Triangle markers above/below bars for pivot points
- Dotted lines extending from pivot points
- Color coding: Green for lows (support), Red for highs (resistance)
- Major pivots are more prominent than minor pivots
3. Customizable alerts for:
- Formation of new pivot points
- Breakouts above/below pivot levels
Trading Applications:
1. Support and Resistance:
- Major pivot levels act as strong support (lows) and resistance (highs)
- Multiple touches of these levels increase their significance
- Minor pivots can indicate intermediate support/resistance levels
2. Trend Analysis:
- Higher highs and higher lows = Uptrend
- Lower highs and lower lows = Downtrend
- Breaking of major pivot levels can signal trend changes
3. Entry/Exit Signals:
- Long entries: When price bounces off major pivot lows
- Short entries: When price rejects from major pivot highs
- Take profits: At opposite pivot levels
- Stop losses: Just beyond the entry pivot level
4. Breakout Trading:
- Breaking above major pivot highs suggests bullish momentum
- Breaking below major pivot lows suggests bearish momentum
- Use the alert system to catch breakouts early
Settings Customization:
- Adjust lookback periods based on your timeframe
- Toggle visibility of markers and lines
- Customize colors for better visibility
- Enable/disable specific types of alerts
Risk Management Tips:
1. Don't rely solely on pivot points - combine with other indicators
2. Wait for confirmation of bounces/rejections before entering trades
3. Use proper position sizing based on stop loss placement
4. Consider market context and overall trend when trading pivot levels
This indicator is particularly useful for swing traders and position traders who focus on key market turning points and trend changes. It helps identify significant price levels where the market has previously shown reaction, making it valuable for both trend following and counter-trend strategies.
Quantify [Entry Model] | FractalystWhat’s the indicator’s purpose and functionality?
Quantify is a machine learning entry model designed to help traders identify high-probability setups to refine their strategies.
➙ Simply pick your bias, select your entry timeframes, and let Quantify handle the rest for you.
Can the indicator be applied to any market approach/trading strategy?
Absolutely, all trading strategies share one fundamental element: Directional Bias
Once you’ve determined the market bias using your own personal approach, whether it’s through technical analysis or fundamental analysis, select the trend direction in the Quantify user inputs.
The algorithm will then adjust its calculations to provide optimal entry levels aligned with your chosen bias. This involves analyzing historical patterns to identify setups with the highest potential expected values, ensuring your setups are aligned with the selected direction.
Can the indicator be used for different timeframes or trading styles?
Yes, regardless of the timeframe you’d like to take your entries, the indicator adapts to your trading style.
Whether you’re a swing trader, scalper, or even a position trader, the algorithm dynamically evaluates market conditions across your chosen timeframe.
How can this indicator help me to refine my trading strategy?
1. Focus on Positive Expected Value
• The indicator evaluates every setup to ensure it has a positive expected value, helping you focus only on trades that statistically favor long-term profitability.
2. Adapt to Market Conditions
• By analyzing real-time market behavior and historical patterns, the algorithm adjusts its calculations to match current conditions, keeping your strategy relevant and adaptable.
3. Eliminate Emotional Bias
• With clear probabilities, expected values, and data-driven insights, the indicator removes guesswork and helps you avoid emotional decisions that can damage your edge.
4. Optimize Entry Levels
• The indicator identifies optimal entry levels based on your selected bias and timeframes, improving robustness in your trades.
5. Enhance Risk Management
• Using tools like the Kelly Criterion, the indicator suggests optimal position sizes and risk levels, ensuring that your strategy maintains consistency and discipline.
6. Avoid Overtrading
• By highlighting only high-potential setups, the indicator keeps you focused on quality over quantity, helping you refine your strategy and avoid unnecessary losses.
How can I get started to use the indicator for my entries?
1. Set Your Market Bias
• Determine whether the market trend is Bullish or Bearish using your own approach.
• Select the corresponding bias in the indicator’s user inputs to align it with your analysis.
2. Choose Your Entry Timeframes
• Specify the timeframes you want to focus on for trade entries.
• The indicator will dynamically analyze these timeframes to provide optimal setups.
3. Let the Algorithm Analyze
• Quantify evaluates historical data and real-time price action to calculate probabilities and expected values.
• It highlights setups with the highest potential based on your selected bias and timeframes.
4. Refine Your Entries
• Use the insights provided—entry levels, probabilities, and risk calculations—to align your trades with a math-driven edge.
• Avoid overtrading by focusing only on setups with positive expected value.
5. Adapt to Market Conditions
• The indicator continuously adapts to real-time market behavior, ensuring its recommendations stay relevant and precise as conditions change.
How does the indicator calculate the current range?
The indicator calculates the current range by analyzing swing points from the very first bar on your charts to the latest available bar it identifies external liquidity levels, also known as BSLQ (buy-side liquidity levels) and SSLQ (sell-side liquidity levels).
What's the purpose of these levels? What are the underlying calculations?
1. Understanding Swing highs and Swing Lows
Swing High: A Swing High is formed when there is a high with 2 lower highs to the left and right.
Swing Low: A Swing Low is formed when there is a low with 2 higher lows to the left and right.
2. Understanding the purpose and the underlying calculations behind Buyside, Sellside and Pivot levels.
3. Identifying Discount and Premium Zones.
4. Importance of Risk-Reward in Premium and Discount Ranges
How does the script calculate probabilities?
The script calculates the probability of each liquidity level individually. Here's the breakdown:
1. Upon the formation of a new range, the script waits for the price to reach and tap into pivot level level. Status: "■" - Inactive
2. Once pivot level is tapped into, the pivot status becomes activated and it waits for either liquidity side to be hit. Status: "▶" - Active
3. If the buyside liquidity is hit, the script adds to the count of successful buyside liquidity occurrences. Similarly, if the sellside is tapped, it records successful sellside liquidity occurrences.
4. Finally, the number of successful occurrences for each side is divided by the overall count individually to calculate the range probabilities.
Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity.
What does the multi-timeframe functionality offer?
You can incorporate up to 4 higher timeframe probabilities directly into the table.
This feature allows you to analyze the probabilities of buyside and sellside liquidity across multiple timeframes, without the need to manually switch between them.
By viewing these higher timeframe probabilities in one place, traders can spot larger market trends and refine their entries and exits with a better understanding of the overall market context.
What are the multi-timeframe underlying calculations?
The script uses the same calculations (mentioned above) and uses security function to request the data such as price levels, bar time, probabilities and booleans from the user-input timeframe.
How does the Indicator Identifies Positive Expected Values?
Quantify instantly calculates whether a trade setup has the potential to generate positive expected value (EV).
To determine a positive EV setup, the indicator uses the formula:
EV = ( P(Win) × R(Win) ) − ( P(Loss) × R(Loss))
where:
- P(Win) is the probability of a winning trade.
- R(Win) is the reward or return for a winning trade, determined by the current risk-to-reward ratio (RR).
- P(Loss) is the probability of a losing trade.
- R(Loss) is the loss incurred per losing trade, typically assumed to be -1.
By calculating these values based on historical data and the current trading setup, the indicator helps you understand whether your trade has a positive expected value.
How can I know that the setup I'm going to trade with has a positive EV?
If the indicator detects that the adjusted pivot and buy/sell side probabilities have generated positive expected value (EV) in historical data, the risk-to-reward (RR) label within the range box will be colored blue and red .
If the setup does not produce positive EV, the RR label will appear gray.
This indicates that even the risk-to-reward ratio is greater than 1:1, the setup is not likely to yield a positive EV because, according to historical data, the number of losses outweighs the number of wins relative to the RR gain per winning trade.
What is the confidence level in the indicator, and how is it determined?
The confidence level in the indicator reflects the reliability of the probabilities calculated based on historical data. It is determined by the sample size of the probabilities used in the calculations. A larger sample size generally increases the confidence level, indicating that the probabilities are more reliable and consistent with past performance.
How does the confidence level affect the risk-to-reward (RR) label?
The confidence level (★) is visually represented alongside the probability label. A higher confidence level indicates that the probabilities used to determine the RR label are based on a larger and more reliable sample size.
How can traders use the confidence level to make better trading decisions?
Traders can use the confidence level to gauge the reliability of the probabilities and expected value (EV) calculations provided by the indicator. A confidence level above 95% is considered statistically significant and indicates that the historical data supporting the probabilities is robust. This high confidence level suggests that the probabilities are reliable and that the indicator’s recommendations are more likely to be accurate.
In data science and statistics, a confidence level above 95% generally means that there is less than a 5% chance that the observed results are due to random variation. This threshold is widely accepted in research and industry as a marker of statistical significance. Studies such as those published in the Journal of Statistical Software and the American Statistical Association support this threshold, emphasizing that a confidence level above 95% provides a strong assurance of data reliability and validity.
Conversely, a confidence level below 95% indicates that the sample size may be insufficient and that the data might be less reliable. In such cases, traders should approach the indicator’s recommendations with caution and consider additional factors or further analysis before making trading decisions.
How does the sample size affect the confidence level, and how does it relate to my TradingView plan?
The sample size for calculating the confidence level is directly influenced by the amount of historical data available on your charts. A larger sample size typically leads to more reliable probabilities and higher confidence levels.
Here’s how the TradingView plans affect your data access:
Essential Plan
The Essential Plan provides basic data access with a limited amount of historical data. This can lead to smaller sample sizes and lower confidence levels, which may weaken the robustness of your probability calculations. Suitable for casual traders who do not require extensive historical analysis.
Plus Plan
The Plus Plan offers more historical data than the Essential Plan, allowing for larger sample sizes and more accurate confidence levels. This enhancement improves the reliability of indicator calculations. This plan is ideal for more active traders looking to refine their strategies with better data.
Premium Plan
The Premium Plan grants access to extensive historical data, enabling the largest sample sizes and the highest confidence levels. This plan provides the most reliable data for accurate calculations, with up to 20,000 historical bars available for analysis. It is designed for serious traders who need comprehensive data for in-depth market analysis.
PRO+ Plans
The PRO+ Plans offer the most extensive historical data, allowing for the largest sample sizes and the highest confidence levels. These plans are tailored for professional traders who require advanced features and significant historical data to support their trading strategies effectively.
For many traders, the Premium Plan offers a good balance of affordability and sufficient sample size for accurate confidence levels.
What is the HTF probability table and how does it work?
The HTF (Higher Time Frame) probability table is a feature that allows you to view buy and sellside probabilities and their status from timeframes higher than your current chart timeframe.
Here’s how it works:
Data Request: The table requests and retrieves data from user-defined higher timeframes (HTFs) that you select.
Probability Display: It displays the buy and sellside probabilities for each of these HTFs, providing insights into the likelihood of price movements based on higher timeframe data.
Detailed Tooltips: The table includes detailed tooltips for each timeframe, offering additional context and explanations to help you understand the data better.
What do the different colors in the HTF probability table indicate?
The colors in the HTF probability table provide visual cues about the expected value (EV) of trading setups based on higher timeframe probabilities:
Blue: Suggests that entering a long position from the HTF user-defined pivot point, targeting buyside liquidity, is likely to result in a positive expected value (EV) based on historical data and sample size.
Red: Indicates that entering a short position from the HTF user-defined pivot point, targeting sellside liquidity, is likely to result in a positive expected value (EV) based on historical data and sample size.
Gray: Shows that neither long nor short trades from the HTF user-defined pivot point are expected to generate positive EV, suggesting that trading these setups may not be favorable.
What machine learning techniques are used in Quantify?
Quantify offers two main machine learning approaches:
1. Adaptive Learning (Fixed Sample Size): The algorithm learns from the entire dataset without resampling, maintaining a stable model that adapts to the latest market conditions.
2. Bootstrap Resampling: This method creates multiple subsets of the historical data, allowing the model to train on varying sample sizes. This technique enhances the robustness of predictions by ensuring that the model is not overfitting to a single dataset.
How does machine learning affect the expected value calculations in Quantify?
Machine learning plays a key role in improving the accuracy of expected value (EV) calculations. By analyzing historical price action, liquidity hits, and market bias patterns, the model continuously adjusts its understanding of risk and reward, allowing the expected value to reflect the most likely market movements. This results in more precise EV predictions, helping traders focus on setups that maximize profitability.
What is the Kelly Criterion, and how does it work in Quantify?
The Kelly Criterion is a mathematical formula used to determine the optimal position size for each trade, maximizing long-term growth while minimizing the risk of large drawdowns. It calculates the percentage of your portfolio to risk on a trade based on the probability of winning and the expected payoff.
Quantify integrates this with user-defined inputs to dynamically calculate the most effective position size in percentage, aligning with the trader’s risk tolerance and desired exposure.
How does Quantify use the Kelly Criterion in practice?
Quantify uses the Kelly Criterion to optimize position sizing based on the following factors:
1. Confidence Level: The model assesses the confidence level in the trade setup based on historical data and sample size. A higher confidence level increases the suggested position size because the trade has a higher probability of success.
2. Max Allowed Drawdown (User-Defined): Traders can set their preferred maximum allowed drawdown, which dictates how much loss is acceptable before reducing position size or stopping trading. Quantify uses this input to ensure that risk exposure aligns with the trader’s risk tolerance.
3. Probabilities: Quantify calculates the probabilities of success for each trade setup. The higher the probability of a successful trade (based on historical price action and liquidity levels), the larger the position size suggested by the Kelly Criterion.
What is a trailing stoploss, and how does it work in Quantify?
A trailing stoploss is a dynamic risk management tool that moves with the price as the market trend continues in the trader’s favor. Unlike a fixed take profit, which stays at a set level, the trailing stoploss automatically adjusts itself as the market moves, locking in profits as the price advances.
In Quantify, the trailing stoploss is enhanced by incorporating market structure liquidity levels (explain above). This ensures that the stoploss adjusts intelligently based on key price levels, allowing the trader to stay in the trade as long as the trend remains intact, while also protecting profits if the market reverses.
Why would a trader prefer a trailing stoploss based on liquidity levels instead of a fixed take-profit level?
Traders who use trailing stoplosses based on liquidity levels prefer this method because:
1. Market-Driven Flexibility: The stoploss follows the market structure rather than being static at a pre-defined level. This means the stoploss is less likely to be hit by small market fluctuations or false reversals. The stoploss remains adaptive, moving as the market moves.
2. Riding the Trend: Traders can capture more profit during a sustained trend because the trailing stop will adjust only when the trend starts to reverse significantly, based on key liquidity levels. This allows them to hold positions longer without prematurely locking in profits.
3. Avoiding Premature Exits: Fixed stoploss levels may exit a trade too early in volatile markets, while liquidity-based trailing stoploss levels respect the natural flow of price action, preventing the trader from exiting too soon during pullbacks or minor retracements.
🎲 Becoming the House: Gaining an Edge Over the Market
In American roulette, the casino has a 5.26% edge due to the presence of the 0 and 00 pockets. On even-money bets, players face a 47.37% chance of winning, while true 50/50 odds would require a 50% chance. This edge—the gap between the payout odds and the true probabilities—ensures that, statistically, the casino will always win over time, even if individual players win occasionally.
From a Trader’s Perspective
In trading, your edge comes from identifying and executing setups with a positive expected value (EV). For example:
• If you identify a setup with a 55.48% chance of winning and a 1:1 risk-to-reward (RR) ratio, your trade has a statistical advantage over a neutral (50/50) probability.
This edge works in your favor when applied consistently across a series of trades, just as the casino’s edge ensures profitability across thousands of spins.
🎰 Applying the Concept to Trading
Like casinos leverage their mathematical edge in games of chance, you can achieve long-term success in trading by focusing on setups with positive EV and managing your trades systematically. Here’s how:
1. Probability Advantage: Prioritize trades where the probability of success (win rate) exceeds the breakeven rate for your chosen risk-to-reward ratio.
• Example: With a 1:1 RR, you need a win rate above 50% to achieve positive EV.
2. Risk-to-Reward Ratio (RR): Even with a win rate below 50%, you can gain an edge by increasing your RR (e.g., a 40% win rate with a 2:1 RR still has positive EV).
3. Consistency and Discipline: Just as casinos profit by sticking to their mathematical advantage over thousands of spins, traders must rely on their edge across many trades, avoiding emotional decisions or overleveraging.
By targeting favorable probabilities and managing trades effectively, you “become the house” in your trading. This approach allows you to leverage statistical advantages to enhance your overall performance and achieve sustainable profitability.
What Makes the Quantify Indicator Original?
1. Data-Driven Edge
Unlike traditional indicators that rely on static formulas, Quantify leverages probability-based analysis and machine learning. It calculates expected value (EV) and confidence levels to help traders identify setups with a true statistical edge.
2. Integration of Market Structure
Quantify uses market structure liquidity levels to dynamically adapt. It identifies key zones like swing highs/lows and liquidity traps, enabling users to align entries and exits with where the market is most likely to react. This bridges the gap between price action analysis and quantitative trading.
3. Sophisticated Risk Management
The Kelly Criterion implementation is unique. Quantify allows traders to input their maximum allowed drawdown, dynamically adjusting risk exposure to maintain optimal position sizing. This ensures risk is scientifically controlled while maximizing potential growth.
4. Multi-Timeframe and Liquidity-Based Trailing Stops
The indicator doesn’t just suggest fixed profit-taking levels. It offers market structure-based trailing stop-loss functionality, letting traders ride trends as long as liquidity and probabilities favor the position, which is rare in most tools.
5. Customizable Bias and Adaptive Learning
• Directional Bias: Traders can set a bullish or bearish bias, and the indicator recalculates probabilities to align with the trader’s market outlook.
• Adaptive Learning: The machine learning model adapts to changes in data (via resampling or bootstrap methods), ensuring that predictions stay relevant in evolving markets.
6. Positive EV Focus
The focus on positive EV setups differentiates it from reactive indicators. It shifts trading from chasing signals to acting on setups that statistically favor profitability, akin to how professional quant funds operate.
7. User Empowerment
Through features like customizable timeframes, real-time probability updates, and visualization tools, Quantify empowers users to make data-informed decisions.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst use, reproduction, or distribution of these proprietary elements is prohibited.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
FXC NQ Opening Range Breakout Strategy V2.4Mechanical Strategy that trades breakouts on NQ futures on the 15min timeframe during the NYSE session. It's designed to manage Apex and Top Step accounts with the lowest risk possible.
Risk Disclaimer:
Past results as well as strategy tester reports do not indicate future performance. Guarantees do not exist in trading. By using this strategy you risk losing all your money.
Important:
It only trades on Monday, Wednesday and Friday and takes usually only 1 trade per trading day.
It works on the 15min timeframe only.
The settings are optimised already for NQ but feel free to change them.
How it works:
Every selected trading day it measures the range of the first 15min candle after the NYSE open. As soon as price closes above on the 15min timeframe, it will trade the breakout targeting a set risk to reward ratio. SL on the opposite side of the range. It will trail the SL after a set amount of points and uses a buffer of the set amount of points to trail it.
Settings:
Opening Range Time : This is the time of the day in hours and minutes when the strategy starts looking for trades. It's in the EST/ NY Timezone and set to 9:30-09:45 by default
because that's the NYSE open.
Session Time : This is the time of the day in hours and minutes until the strategy trades. It's in the EST/ NY Timezone and set to 09:45-14:45 by default.
because that's what gave the best results in backtesting. Open trades will get closed automatically once the end of the session is reached. No matter if win or loss. This is just to prevent holding positions over night.
Session Border This setting is to select the border color in which the session box will be plotted.
Opening Range Box This setting is to select the fill color of the opening range box.
Opening Range Border This setting is to select the border color of the session box.
Trade Timeframe This setting determines on which timeframe candle has to close outside the opening range box in order to take a trade. It's set to 15min by default because this is what worked by far the best in backtests and live trading.
Stop Loss Buffer in Points: This is simply the buffer in points that is added to the SL for safety reasons. If you have it on 0, the SL will be at the exact price of the opposite side of the range. By default it's set to 0 pips because this is what delivered the best results in backtests.
Profit Target Factor: This is simply the total SL size in points multiplied by x.
Example: If you put 2, you get a 1:2 Risk to Reward Ratio. By Default it's set to 4 because this gave the best results in backtests, because trades always get closed either by trailing SL or because the end of the session is reached.
Use Trailing Stop Loss: This setting is to enable/ disable the trailing stop loss. It's enabled by default because this is a fundamental part of the strategy.
Trailing Stop Buffer: This setting determines after how many points in profit the trailing SL will be activated.
Risk Type: You can chose either between Fixed USD Amount, Risk per Trade in % or Fixed Contract Size. By default it's set to fixed contract size.
Risk Amount (USD or Contracts): This setting is to set how many USD or how many contracts you want to risk per trade. Make sure to check which risk type you have selected before you chose the risk amount.
Use Limit Orders If enabled, the strategy will place a pending order x points from the current price, instead of a market order. Limit orders are enabled by default for a better performance. Important: It doesn't actually place a limit order. The strategy will just wait for a pullback and then enter with a market order. It's more like a hidden limit order.
Limit Order Distance (points): If you have limit orders enabled, this setting determines how many points from the current price the limit order will be placed.
Trading Days: These checkboxes are to select on which week days the strategy has to trade. Thursday is disabled by default because backtests have shown that Thursday is the least profitable day
Backtest Settings:
For the backtest the commissions ere set to 0.35 USD per mini contract which is the highest amount Tradeovate charges. Margin was not accounted for because typically on Apex accounts you can use way more contracts than you need for the extremely low max drawdown. Margin would be important on personal accounts but even there typically it's not an issue at all especially because this strategy runs on the 15min timeframe so it won't use a lot of contracts anyways.
What makes it unique:
This script is unique because it's designed to be used on Apex and Top Step accounts with extremely strict drawdown rules.
The strategy is optimised to be traded with a fixed contract size instead of using % risk. The reason for that is that the drawdown rules of these Futures Prop Accounts are very strict and the fact that the smallest trade-able contract size is 1.
Why the source code is hidden:
The source code is hidden because I invested a lot of time and money into developing this strategy and optimising it with paid 3rd party software. Also since I use it myself on my Apex accounts and prop firms don't allow copy trading I don't want it to be used by too many traders.
Skeleton Key LiteSkeleton Key Lite Strategy
Note : Every input, except for the API Alerts, depends on an external indicator to provide the necessary values for the strategy to function.
Definitions
Strategy Direction: The trading direction (long or short) as determined by an external source, such as an indicator.
Threshold Conditions:
- Enter Condition: Defines the condition for entering a trade.
- Exit Condition: Defines the condition for exiting a trade.
Stop Loss (SL):
- Trail SL: A trailing stop loss, dynamically updated during the trade.
- Basic SL: A static stop loss level.
- Emergency SL (ER SL): A fallback stop loss for extreme conditions.
- Max SL: The maximum risk tolerance in stop loss.
- Limit SL: A predefined stop loss that is executed as a limit order.
Take Profit (TP):
- Max TP: The maximum profit target for a trade.
- Limit TP: A predefined take profit level executed as a limit order.
API Alerts:
- API Entry: JSON-based configuration for sending entry signals.
- API Exit: JSON-based configuration for sending exit signals.
Broad Concept
The Skeleton Key Lite strategy script is designed to provide a generalized framework for orchestrating trade execution based on external indicators. It allows QuantAlchemy and others to encapsulate strategies into indicators, which can then be backtested and automated using this strategy script.
Inputs
Note : All inputs are dependent on external indicators for values except for the API Alerts.
Strategy Direction:
- Source: Direction signal from an external indicator.
- Options: `LONG` (`1`), `SHORT` (`-1`).
Trade Conditions:
- Enter: Source input, trigger for entry condition.
- Exit: Source input, trigger for exit condition.
Stops and Take Profits:
- Trail SL: Enable/disable dynamic trailing stop loss.
- Basic SL: Enable/disable static stop loss.
- Emergency SL: Enable/disable emergency stop loss.
- Max SL: Enable/disable maximum risk stop loss.
- Max TP: Enable/disable maximum take profit.
- Limit SL: Enable/disable predefined stop loss executed as a limit order.
- Limit TP: Enable/disable predefined take profit executed as a limit order.
Alerts:
- API Entry: Configurable JSON message for entry signals.
- API Exit: Configurable JSON message for exit signals.
How It Works
Trade Logic:
- Conditions for entering and exiting trades are evaluated based on the selected input sources.
Stop Loss and Take Profit Management:
- Multiple stop loss types (trailing, basic, emergency, etc.) and take profit levels are calculated dynamically during the trade entry. Trailing stop loss is updated during the trade based on the selected input.
API Alerts:
- Alerts are triggered using customizable JSON messages, which can be integrated with external trading systems or APIs.
Trade Execution:
- Enter: Initiates a new trade if entry conditions are met and there is no open position.
- Exit: Closes all trades if exit conditions are met or stop loss/take profit thresholds are hit.
Key Features
Customizable: Fully configurable entry and exit conditions based on external indicators.
Encapsulation: Integrates seamlessly with indicators, allowing strategies to be developed as indicator-based signals.
Comprehensive Risk Management:
- Multiple stop loss and take profit options.
- Emergency stop loss for unexpected conditions.
API Integration: Alerts are designed to interface with external systems for automation and monitoring.
Plots
The script plots key variables on the chart for better visualization:
Enter and Exit Signals:
- `enter`: Displays when the entry condition is triggered.
- `exit`: Displays when the exit condition is triggered.
Risk Management Levels:
- `trailSL`: Current trailing stop loss level.
- `basicSL`: Static stop loss level.
- `erSL`: Emergency stop loss level.
- `maxSL`: Maximum risk stop loss level.
Profit Management Levels:
- `maxTP`: Maximum take profit level.
- `limitTP`: Limit-based take profit level.
Limit Orders:
- `limitSL`: Limit-based stop loss level.
- `limitTP`: Limit-based take profit level.
Proposed Interpretations
Entry and Exit Points:
- Use the plotted signals (`enter`, `exit`) to analyze the trade entry and exit points visually.
Risk and Profit Levels:
- Monitor the stop loss (`SL`) and take profit (`TP`) levels to assess trade performance.
Dynamic Trail SL:
- Observe the `trailSL` to evaluate how the trailing stop adapts during the trade.
Limitations
Dependence on Indicators:
- This script relies on external indicators to provide signals for strategy execution.
No Indicator Included:
- Users must integrate an appropriate indicator for source inputs.
Back-Test Constraints:
- Back-testing results depend on the accuracy and design of the integrated indicators.
Final Thoughts
The Skeleton Key Lite strategy by QuantAlchemy provides a robust framework for automated trading by leveraging indicator-based signals. Its flexibility and comprehensive risk management make it a valuable tool for traders seeking to implement and backtest custom strategies.
Disclaimer
This script is for educational purposes only. Trading involves risk, and past performance does not guarantee future results. Use at your own discretion and risk.
Balthazar by Aloupay📈 BALTHAZAR BY ALOUPAY: Advanced Trading Strategy for Precision and Reliability
BALTHAZAR BY ALOUPAY is a comprehensive trading strategy developed for TradingView, designed to assist traders in making informed and strategic trading decisions. By integrating multiple technical indicators, this strategy aims to identify optimal entry and exit points, manage risk effectively, and enhance overall trading performance.
🌟 Key Features
1. Integrated Indicator Suite
Exponential Moving Averages (EMAs) : Utilizes Fast (12), Medium (26), and Slow (50) EMAs to determine trend direction and strength.
Stochastic RSI : Employs Stochastic RSI with customizable smoothing periods to assess momentum and potential reversal points.
Average True Range (ATR) : Calculates dynamic stop loss and take profit levels based on market volatility using ATR multipliers.
MACD Confirmation : Incorporates MACD histogram analysis to validate trade signals, enhancing the reliability of entries.
2. Customizable Backtesting Parameters
Date Range Selection: Allows users to define specific backtesting periods to evaluate strategy performance under various market conditions.
Timezone Adaptability: Ensures accurate time-based filtering in alignment with the chart's timezone settings.
3. Advanced Risk Management
Dynamic Stop Loss & Take Profit: Automatically adjusts exit points using ATR multipliers to adapt to changing market volatility.
Position Sizing: Configurable to risk a sustainable percentage of equity per trade (recommended: 5-10%) to maintain disciplined money management.
4. Clear Trade Signals
Long & Short Entries: Generates actionable signals based on the convergence of EMA alignment, Stochastic RSI crossovers, and MACD confirmation.
Automated Exits: Implements predefined take profit and stop loss levels to secure profits and limit losses without emotional interference.
5. Visual Enhancements
EMA Visualization: Displays Fast, Medium, and Slow EMAs on the chart for easy trend identification.
Stochastic RSI Indicators: Uses distinct shapes to indicate bullish and bearish momentum shifts.
Risk Levels Display: Clearly marks take profit and stop loss levels on the chart for transparent risk-reward assessment.
🔍 Strategy Mechanics
Trend Identification with EMAs
Bullish Trend: Fast EMA (12) > Medium EMA (26) > Slow EMA (50)
Bearish Trend: Fast EMA (12) < Medium EMA (26) < Slow EMA (50)
Momentum Confirmation with Stochastic RSI
Bullish Signal: %K line crosses above %D line, indicating upward momentum.
Bearish Signal: %K line crosses below %D line, signaling downward momentum.
Volatility-Based Risk Management with ATR
Stop Loss: Positioned at 1.0 ATR below (for long) or above (for short) the entry price.
Take Profit: Positioned at 4.0 ATR above (for long) or below (for short) the entry price.
MACD Confirmation
Long Trades: Executed only when the MACD histogram is positive.
Short Trades: Executed only when the MACD histogram is negative.
💱 Recommended Forex Pairs
While BALTHAZAR BY ALOUPAY has shown robust performance on the 4-hour timeframe for Gold (XAU/USD), it is also well-suited for the following highly liquid forex pairs:
EUR/USD (Euro/US Dollar)
GBP/USD (British Pound/US Dollar)
USD/JPY (US Dollar/Japanese Yen)
AUD/USD (Australian Dollar/US Dollar)
USD/CAD (US Dollar/Canadian Dollar)
NZD/USD (New Zealand Dollar/US Dollar)
EUR/GBP (Euro/British Pound)
These pairs offer high liquidity and favorable trading conditions that complement the strategy's indicators and risk management features.
⚙️ Customization Options
Backtesting Parameters
Start Date: Define the beginning of the backtesting period.
End Date: Define the end of the backtesting period.
EMAs Configuration
Fast EMA Length: Default is 12.
Medium EMA Length: Default is 26.
Slow EMA Length: Default is 50.
Source: Default is Close price.
Stochastic RSI Configuration
%K Smoothing: Default is 5.
%D Smoothing: Default is 4.
RSI Length: Default is 14.
Stochastic Length: Default is 14.
RSI Source: Default is Close price.
ATR Configuration
ATR Length: Default is 14.
ATR Smoothing Method: Options include RMA, SMA, EMA, WMA (default: RMA).
Stop Loss Multiplier: Default is 1.0 ATR.
Take Profit Multiplier: Default is 4.0 ATR.
MACD Configuration
MACD Fast Length: Default is 12.
MACD Slow Length: Default is 26.
MACD Signal Length: Default is 9.
📊 Why Choose BALTHAZAR BY ALOUPAY?
Comprehensive Integration: Combines trend, momentum, and volatility indicators for a multifaceted trading approach.
Automated Precision: Eliminates emotional decision-making with rule-based entry and exit signals.
Robust Risk Management: Protects capital through dynamic stop loss and take profit levels tailored to market conditions.
User-Friendly Customization: Easily adjustable settings to align with individual trading styles and risk tolerance.
Proven Reliability: Backtested over extensive periods across various market environments to ensure consistent performance.
Disclaimer : Trading involves significant risk of loss and is not suitable for every investor. Past performance is not indicative of future results. Always conduct your own research and consider your financial situation before engaging in trading activities.
Stocks & Options P/L TrackerOverview:
The Stocks & Options P/L Tracker is a custom TradingView indicator developed to offer traders precise tracking of stocks & options trades’ profit and loss in real-time. It features a detailed display of P/L intervals, stop-loss and take-profit levels, and an adaptable trailing stop mechanism to help traders manage risk and optimize their trading strategies. This tool is particularly useful for active traders who seek immediate visual feedback on their trades’ performance.
Key Features:
Real-Time P/L Display: Computes and displays the P/L per contract/share and total P/L dynamically on the chart based on the specified entry price, relative to the current market price, and number of contracts or shares.
Configurable Take Profit and Stop Loss: Users can set take-profit and stop-loss amounts, and the indicator will visually mark these levels with corresponding dollar amounts for easy reference.
Trailing Stop Functionality: Offers an option to enable a trailing stop that automatically adjusts based on price movements.
Interval-Based P/L Tracking: Uses customizable intervals to display projected P/L levels above and below the entry price, helping users understand potential profit or loss scenarios at a glance.
Dynamic Labeling and Alerts: Visual labels are used to mark P/L, take-profit, stop-loss, trailing stop, and entry levels. These labels update dynamically on each new price bar to provide immediate insights into trade performance. NOTE: Due to TradingView's limitations with server-side alerts on fixed prices, dynamic alerts (for Take Profit, Stop Loss, and Trailing Stop) that adjust with price changes are not yet available. Alerts must be manually reset to your desired price each time.
Clean and Responsive Design: Utilizes color-coded labels and lines for P/L intervals, making it easy to distinguish profit, loss, stop, and take-profit zones. Colors adjust automatically to the current price to maintain clarity.
User Input Validation: Ensures appropriate input values for items like entry price, contract/share size, and profit/loss intervals to prevent errors and optimize performance.
Efficient Object Management: Implements object reusability for lines and labels to stay within Pine Script's object limits, ensuring smooth operation and maximum accuracy in real-time tracking.
Automatic Adjustments Based on Market Changes: Calculates and adjusts trailing stop levels dynamically based on highest price movement, which provides traders flexibility while maintaining risk controls.
Trader Benefits:
This indicator empowers traders with a robust tool to manage their trades visually and strategically on TradingView. The real-time feedback and customization options help traders make informed decisions, minimize risks, and maximize potential profits.
Happy Trading! :)
ATR - FSThis script calculates and visualizes the Average True Range (ATR) along with its moving average, highest, and lowest values over a defined period. The ATR is a widely used volatility indicator in trading that measures the degree of price movement within a market. By incorporating both the average ATR and the high/low ranges, this script provides a comprehensive view of market volatility dynamics.
Use Cases:
Volatility-Based Trading:
Traders can use this indicator to gauge market volatility and adjust their trading strategies accordingly. For example:
High ATR values often indicate periods of high volatility, suggesting larger price swings and more aggressive trading opportunities.
Low ATR values signal quieter market conditions, where range-bound trading or less aggressive positioning might be favorable.
Stop-Loss & Take-Profit Placement:
The ATR is commonly used to determine optimal stop-loss and take-profit levels:
During high volatility periods (high ATR values), traders might widen their stop-loss levels to accommodate larger price swings.
Conversely, during low volatility periods, traders may tighten their stop-loss levels to capture profits before the market moves against them.
Trend Identification:
The moving average of ATR helps traders identify long-term volatility trends, which can indicate the strength of a market trend:
If the average ATR is increasing, it could suggest the continuation of a strong trend.
A decreasing average ATR may indicate the start of a consolidation period or weakening trend.
Volatility Breakouts:
By analyzing the highest and lowest ATR values, traders can spot potential breakout opportunities:
A sudden spike in ATR (breaking above the green line) can indicate a breakout from a consolidation phase.
Dropping below the orange line may signal a period of market stagnation or consolidation.
Risk Management:
The ATR is a critical tool in risk management, helping traders set stop-losses and position sizes based on market conditions:
Higher ATR values might prompt a trader to reduce their position size to account for larger potential losses.
Lower ATR values may encourage a trader to take on larger positions, as the market risk is lower.
PERFECT PIVOT RANGE DR ABIRAM SIVPRASAD (PPR)PERFECT PIVOT RANGE (PPR) by Dr. Abhiram Sivprasad
The Perfect Pivot Range (PPR) indicator is designed to provide traders with a comprehensive view of key support and resistance levels based on pivot points across different timeframes. This versatile tool allows users to visualize daily, weekly, and monthly pivots along with high and low levels from previous periods, helping traders identify potential areas of price reversals or breakouts.
Features:
Multi-Timeframe Pivots:
Daily, weekly, and monthly pivot levels (Pivot Point, Support 1 & 2, Resistance 1 & 2).
Helps traders understand price levels across various timeframes, from short-term (daily) to long-term (monthly).
Previous High-Low Levels:
Displays the previous week, month, and day high-low levels to highlight key zones of historical support and resistance.
Traders can easily see areas of price action from prior periods, giving context for future price movements.
Customizable Options:
Users can choose which pivot levels and high-lows to display, allowing for flexibility based on trading preferences.
Visual settings can be toggled on and off to suit different trading strategies and timeframes.
Real-Time Data:
All pivot points and levels are dynamically calculated based on real-time price data, ensuring accurate and up-to-date information for decision-making.
How to Use:
Pivot Points: Use daily, weekly, or monthly pivot points to find potential support or resistance levels. Prices above the pivot suggest bullish sentiment, while prices below indicate bearishness.
Previous High-Low: The high-low levels from previous days, weeks, or months can serve as critical zones where price may reverse or break through, indicating potential trade entries or exits.
Confluence: When pivot points or high-low levels overlap across multiple timeframes, they become even stronger levels of support or resistance.
This indicator is suitable for all types of traders (scalpers, swing traders, and long-term investors) looking to enhance their technical analysis and make more informed trading decisions.
Here are three detailed trading strategies for using the Perfect Pivot Range (PPR) indicator for options, stocks, and commodities:
1. Options Buying Strategy with PPR Indicator
Strategy: Buying Call and Put Options Based on Pivot Breakouts
Objective: To capitalize on sharp price movements when key pivot levels are breached, leading to high returns with limited risk in options trading.
Timeframe: 15-minute to 1-hour chart for intraday option trading.
Steps:
Identify the Key Levels:
Use weekly pivots for intraday trading, as they provide more significant levels for options.
Enable the "Previous Week High-Low" to gauge support and resistance from the previous week.
Call Option Setup (Bullish Breakout):
Condition: If the price breaks above the weekly pivot point (PP) with high momentum (indicated by a strong bullish candle), it signifies potential bullishness.
Action: Buy Call Options at the breakout of the weekly pivot.
Confirmation: Check if the price is sustaining above the pivot with a minimum of 1-2 candles (depending on timeframe) and the first resistance (R1) isn’t too far away.
Target: The first resistance (R1) or previous week’s high can be your target for exiting the trade.
Stop-Loss: Set a stop-loss just below the pivot point (PP) to limit risk.
Put Option Setup (Bearish Breakdown):
Condition: If the price breaks below the weekly pivot (PP) with strong bearish momentum, it’s a signal to expect a downward move.
Action: Buy Put Options on a breakdown below the weekly pivot.
Confirmation: Ensure that the price is closing below the pivot, and check for declining volumes or bearish candles.
Target: The first support (S1) or the previous week’s low.
Stop-Loss: Place the stop-loss just above the pivot point (PP).
Example:
Let’s say the weekly pivot point (PP) is at 1500, the price breaks above and sustains at 1510. You buy a Call Option with a strike price near 1500, and the target will be the first resistance (R1) at 1530.
2. Stock Trading Strategy with PPR Indicator
Strategy: Swing Trading Using Pivot Points and Previous High-Low Levels
Objective: To capture mid-term stock price movements using pivot points and historical high-low levels for better trade entries and exits.
Timeframe: 1-day or 4-hour chart for swing trading.
Steps:
Identify the Trend:
Start by determining the overall trend of the stock using the weekly pivots. If the price is consistently above the pivot point (PP), the trend is bullish; if below, the trend is bearish.
Buy Setup (Bullish Trend Reversal):
Condition: When the stock bounces off the weekly pivot point (PP) or previous week’s low, it signals a bullish reversal.
Action: Enter a long position near the pivot or previous week’s low.
Confirmation: Look for a bullish candle pattern or increasing volumes.
Target: Set your first target at the first resistance (R1) or the previous week’s high.
Stop-Loss: Place your stop-loss just below the previous week’s low or support (S1).
Sell Setup (Bearish Trend Reversal):
Condition: When the price hits the weekly resistance (R1) or previous week’s high and starts to reverse downwards, it’s an opportunity to short-sell the stock.
Action: Enter a short position near the resistance.
Confirmation: Watch for bearish candle patterns or decreasing volume at the resistance.
Target: Your first target would be the weekly pivot point (PP), with the second target as the previous week’s low.
Stop-Loss: Set a stop-loss just above the resistance (R1).
Use Previous High-Low Levels:
The previous week’s high and low are key levels where price reversals often occur, so use them as reference points for potential entry and exit.
Example:
Stock XYZ is trading at 200. The previous week’s low is 195, and it bounces off that level. You enter a long position with a target of 210 (previous week’s high) and place a stop-loss at 193.
3. Commodity Trading Strategy with PPR Indicator
Strategy: Trend Continuation and Reversal in Commodities
Objective: To capitalize on the strong trends in commodities by using pivot points as key support and resistance levels for trend continuation and reversal.
Timeframe: 1-hour to 4-hour charts for commodities like Gold, Crude Oil, Silver, etc.
Steps:
Identify the Trend:
Use monthly pivots for long-term commodities trading since commodities often follow macroeconomic trends.
The monthly pivot point (PP) will give an idea of the long-term trend direction.
Trend Continuation Setup (Bullish Commodity):
Condition: If the price is consistently trading above the monthly pivot and pulling back towards the pivot without breaking below it, it indicates a bullish continuation.
Action: Enter a long position when the price tests the monthly pivot (PP) and starts moving up again.
Confirmation: Look for a strong bullish candle or an increase in volume to confirm the continuation.
Target: The first resistance (R1) or previous month’s high.
Stop-Loss: Place the stop-loss below the monthly pivot (PP).
Trend Reversal Setup (Bearish Commodity):
Condition: When the price reverses from the monthly resistance (R1) or previous month’s high, it’s a signal for a bearish reversal.
Action: Enter a short position at the resistance level.
Confirmation: Watch for bearish candle patterns or decreasing volumes at the resistance.
Target: Set your first target as the monthly pivot (PP) or the first support (S1).
Stop-Loss: Stop-loss should be placed just above the resistance level.
Using Previous High-Low for Swing Trades:
The previous month’s high and low are important in commodities. They often act as barriers to price movement, so traders should look for breakouts or reversals near these levels.
Example:
Gold is trading at $1800, with a monthly pivot at $1780 and the previous month’s high at $1830. If the price pulls back to $1780 and starts moving up again, you enter a long trade with a target of $1830, placing your stop-loss below $1770.
Key Points Across All Strategies:
Multiple Timeframes: Always use a combination of timeframes for confirmation. For example, a daily chart may show a bullish setup, but the weekly pivot levels can provide a larger trend context.
Volume: Volume is key in confirming the strength of price movement. Always confirm breakouts or reversals with rising or declining volume.
Risk Management: Set tight stop-loss levels just below support or above resistance to minimize risk and lock in profits at pivot points.
Each of these strategies leverages the powerful pivot and high-low levels provided by the PPR indicator to give traders clear entry, exit, and risk management points across different markets
Liquidity strategy tester [Influxum]This tool is based on the concept of liquidity. It includes 10 methods for identifying liquidity in the market. Although this tool is presented as a strategy, we see it more as a data-gathering instrument.
Warning: This indicator/strategy is not intended to generate profitable strategies. It is designed to identify potential market advantages and help with identifying effective entry points to capitalize on those advantages.
Once again, we have advanced the methods of effectively searching for liquidity in the market. With strategies, defined by various entry methods and risk management, you can find your edge in the market. This tool is backed by thorough testing and development, and we plan to continue improving it.
In its current form, it can also be used to test well-known ICT or Smart Money concepts. Using various methods, you can define market structure and identify areas where liquidity is located.
Fair Value Gaps - one of the entry signal options is fair value gaps, where an imbalance between buyers and sellers in the market can be expected.
Time and Price Theory - you can test this by setting liquidity from a specific session and testing entries as that liquidity is grabbed
Judas Swing - can be tested as a market reversal after a breakout during the first hours of trading.
Power of Three - accumulation can be observed as the market moving within a certain range, identified as cluster liquidity in our tool, manipulation occurs with the break of liquidity, and distribution is the direction of the entry.
🟪 Methods of Identifying Liquidity
Pivot Liquidity
This refers to liquidity formed by local extremes – the highest or lowest prices reached in the market over a certain period. The period is defined by a pivot number and determines how many candles before and after the high/low were higher/lower. Simply put, the pivot number represents the number of adjacent candles to the left and right, with a lower high for a pivot high and a higher low for a pivot low. The higher the number, the more significant the high/low is. Behind these local market extremes, we expect to find orders waiting for breakout as well as stop-losses.
Gann Swing
Similar to pivot liquidity, Gann swing identifies significant market points. However, instead of candle highs and lows, it focuses on the closing prices. A Gann swing is formed when a candle closes above (or below) several previous closes (the number is again defined by a strength parameter).
Percentage Change
Apart from ticks, percentages are also a key unit of market movement. In the search for liquidity, we monitor when a local high or low is formed. For liquidity defined by percentage change, a high must be a certain percentage higher than the last low to confirm a significant high. Similarly, a low must be a defined percentage away from the last significant high to confirm a new low. With the right percentage settings, you can eliminate market noise.
Session Range (3x)
Session range is a popular concept for finding liquidity, especially in smart money concepts (SMC). You can set up liquidity visualization for the Asian, London, or New York sessions – or even all three at once. This tool allows you to work with up to three sessions, so you can easily track how and if the market reacts to liquidity grabs during these sessions.
Tip for traders: If you want to see the reaction to liquidity grab during a specific session at a certain time (e.g., the well-known killzone), you can set the Trading session in this tool to the exact time where you want to look for potential entries.
Unfinished Auction
Based on order flow theory, an unfinished auction occurs when the market reverses sharply without filling all pending orders. In price action terms, this can be seen as two candles at a local high or low with very similar or identical highs/lows. The maximum difference between these values is defined as Tolerance, with the default setting being 3 ticks. This setting is particularly useful for filtering out noise during slower market periods, like the Asian session.
Double Tops and Bottoms
A very popular concept not only from smart money concepts but also among price pattern traders is the double bottom and double top. This occurs when the market stops and reverses at a certain price twice in a row. In the tool, you can set how many candles apart these bottoms/tops can be by adjusting the Length parameter. According to some theories, double bottoms are more effective when there is a significant peak between the two bottoms. You can set this in the tool as the Swing value, which defines how large the movement (expressed in ticks) must be between the two peaks/bottoms. The final parameter you can adjust is Tolerance, which defines the possible price difference between the two peaks/bottoms, also expressed in ticks.
Range or Cluster Liquidity
When the market stays within a certain price range, there’s a chance that breakout orders and stop-losses are accumulating outside of this range. Our tool defines ranges in two ways:
Candle balance calculates the average price within a candle (open, high, low, and close), and it defines consolidation when the centers of candles are within a certain distance from each other.
Overlap confirms consolidation when a candle overlaps with the previous one by a set percentage.
Daily, Weekly, and Monthly Highs or Lows
These options simply define liquidity as the previous day’s, week’s, or month’s highs or lows.
Visual Settings
You can easily adjust how liquidity is displayed on the chart, choosing line style, color, and thickness. To display only uncollected liquidity, select "Delete grabbed liquidity."
Liquidity Duration
This setting allows you to control how long liquidity areas remain valid. You can cancel liquidity at the end of the day, the second day, or after a specific number of candles.
🟪 Strategy
Now we come to the part of working with strategies.
Max # of bars after liquidity grab – This parameter allows you to define how many candles you can search for entry signals from the moment liquidity is grabbed. If you are using engulfing as an entry signal, which consists of 2 candles, keep in mind that this number must be at least 2. In general, if you want to test a quick and sharp reaction, set this number as low as possible. If you want to wait for a structural change after the liquidity grab, which may require more candles, set the number a bit higher.
🟪 Strategy - entries
In this section, we define the signals or situations where we can enter the market after liquidity has been taken out.
Liquidity grab - This setup triggers a trade immediately after liquidity is grabbed, meaning the trade opens as the next candle forms.
Close below, close above - This refers to situations where the price closes below liquidity, but then reverses and closes above liquidity again, suggesting the liquidity grab was a false breakout.
Over bar - This occurs when the entire candle (high and low) passes beyond the liquidity level but then experiences a pullback.
Engulfing - A popular price action pattern that is included in this tool.
2HL - weak, medium, strong - A variation of a popular candlestick pattern.
Strong bar - A strong reactionary candle that forms after a liquidity grab. If liquidity is grabbed at a low, this would be a strong long candle that closes near its high and is significantly larger compared to typical volatility.
Naked bar - A candlestick pattern we’ve tested that serves as a good confirmation of market movement.
FVG (Fair Value Gap) - A currently popular concept. This is the only signal with additional settings. “Pending FVG order valid” means if a fair value gap forms after a liquidity grab, a limit order is placed, which remains valid for a set number of candles. “FVG minimal tick size” allows you to filter based on the gap size, measured in ticks. “GAP entry model” lets you decide whether to place the limit order at the gap close or its edge.
🟪 Strategy - General
Long, short - You can choose whether to focus on long or short trades. It’s interesting to see how long and short trades yield different results across various markets.
Pyramiding - By default, the tool opens only one trade at a time. If a new signal arises while a trade is open, it won’t enter another position unless the pyramiding box is checked. You also need to set the maximum number of open trades in the Properties.
Position size - Simply set the size of the traded position.
🟪 Strategy - Time
In this section, you can set time parameters for the strategy being tested.
Test since year - As the name implies, you can limit the testing to start from a specific year.
Trading session - Define the trading session during which you want to test entries. You can also visualize the background (BG) for confirmation.
Exclude session - You can set a session period during which you prefer not to search for trades. For example, when the New York session opens, volatility can sharply increase, potentially reducing the long-term success rate of the tested setup.
🟪 Strategy - Exits
This section lets you define risk management rules.
PT & SL - Set the profit target (PT) and stop loss (SL) here.
Lowest/highest since grab - This option sets the stop loss at the lowest point after a liquidity grab at a low or at the highest point after a liquidity grab at a high. Since markets usually overshoot during liquidity grabs, it’s good practice to place the stop loss at the furthest point after the grab. You can also set your risk-reward ratio (RRR) here. A value of 1 sets an RRR of 1:1, 2 means 2:1, and so on.
Lowest/highest last # bars - Similar to the previous option, but instead of finding the extreme after a liquidity grab, it identifies the furthest point within the last number of candles. You can set how far back to look using the # bars field (for an engulfing pattern, 2 is optimal since it’s made of two candles, and the stop loss can be placed at the edge of the engulfing pattern). The RRR setting works the same way as in the previous option.
Other side liquidity grab - If this option is checked, the trade will exit when liquidity is grabbed on the opposite side (i.e., if you entered on a liquidity grab at a low, the trade will exit when liquidity is grabbed at a high).
Exit after # bars - A popular exit strategy where you close the position after a set number of candles.
Exit after # bars in profit - This option exits the trade once the position is profitable for a certain number of consecutive candles. For example, if set to 5, the position will close when 5 consecutive candles are profitable. You can also set a maximum number of candles (in the max field), ensuring the trade is closed after a certain time even if the profit condition hasn’t been met.
🟪 Alerts
Alerts are a key tool for traders to ensure they don’t miss trading opportunities. They also allow traders to manage their time effectively. Who would want to sit in front of the computer all day waiting for a trading opportunity when they could be attending to other matters? In our tool, you currently have two options for receiving alerts:
Liquidity grabs alert – if you enable this feature and set an alert, the alert will be triggered every time a candle on the current timeframe closes and intersects with the displayed liquidity line.
Entry signals alert – this feature triggers an alert when a signal for entry is generated based on the option you’ve selected in the Entry type. It’s an ideal way to be notified only when a trading opportunity appears according to your predefined rules.
Nifty scalping 3 minutesOverview:
The "Nifty Scalping 3 Minutes" strategy is a uniquely tailored trading system for Nifty Futures traders, with a clear focus on capital preservation, dynamic risk management, and high-probability trade entries. This strategy uses unique combination of standard technical indicators like Jurik Moving Average (JMA), Exponential Moving Average (EMA), and Bollinger Bands, but it truly stands out through its Price-Volume Spike Detection system—a unique mechanism designed to trigger trades only during periods of high momentum and market participation. The strategy also incorporates robust risk management, ensuring that traders minimize losses while maximizing profits. in complete back test range max drawdown is less than 1%
Scalping Approach and Requirements:
The strategy focuses on quick in and out trades, aiming to capture small, quick profits during periods of heightened market activity. For optimal performance, traders should have ₹2,00,000 or more in capital available per trade. The dynamic lot calculation and risk controls require this level of capital to function effectively.
Small, frequent trades are the focus, and the strategy is ideal for traders comfortable with high-frequency executions. Traders with insufficient capital or those not comfortable with frequent trades may find this strategy unsuitable.
Default Properties for Publication:
Initial Capital: ₹2,000,000
Lot Size: 25 contracts (adjusted dynamically based on available margin)
Stop-Loss: Risk per trade capped at 1% of equity.
Slippage and Commission: Realistic values are factored into the backtesting.
Key Feature: Price-Volume Spike Detection
1. Condition: Trades are executed only when there is a significant price spike confirmed by a volume spike. The candle width is calculated by multiplying the price change (difference between the candle's open and close) by the volume, and this result is compared to a 126-period average of both price and volume.
A trade is triggered when the current price-volume spike exceeds this average by a preset volume multiplier (default set at 3). This ensures that both the price change and volume are unusually strong compared to normal market behavior.
2. Reasoning: Many traders fail to incorporate the relationship between price movement and volume effectively. By using this Price-Volume Spike Detection mechanism, the strategy ensures that it only enters trades during periods of strong market momentum when both price and volume confirm a real market move, not just noise or small fluctuations.
The 126-period moving average of volume is chosen specifically because it represents a complete trading session on the 3-minute chart. This ensures that the volume spike is compared against a realistic baseline of daily activity, making the detection more robust and reliable.
The volume multiplier allows flexibility in determining the threshold for a significant spike, enabling users to fine-tune the strategy according to their risk tolerance and market conditions.
Trade Placement Logic:
1. Trend Confirmation with JMA and EMA:
Condition: The strategy will only consider entering a trade when JMA crosses above EMA for a long trade or JMA crosses below EMA for a short trade.
Reasoning: The JMA is used for its low lag and responsiveness, allowing it to capture early trends, while the EMA adds a level of confirmation by weighing recent price action more heavily. This dual confirmation ensures that trades are entered only when a solid trend is in place.
2. Bollinger Bands for Volatility Breakouts:
Condition: In addition to the JMA-EMA crossover, the price must break outside the Bollinger Bands—above the upper band for long trades, or below the lower band for short trades.
Reasoning: Bollinger Bands are a volatility indicator. By requiring a price breakout beyond the bands, the strategy ensures that trades are placed during periods of high volatility, avoiding low-momentum, sideways markets.
3. Volume and Price Confirmation (Price-Volume Spike Detection):
Condition: A trade is only triggered if the price-volume spike condition is met. This ensures that the market move is backed by strong volume and that the price change is significant relative to the recent average activity.
Reasoning: This condition filters out low-volume environments where price movements are more likely to reverse or stall. By waiting for a spike in both price and volume, the strategy ensures that it enters trades during high-momentum periods, where follow-through is more likely.
Exit Logic and Risk Management:
1. Stop-Loss (SL) Placement:
Condition: Upon entering a trade, an initial stop-loss is placed below the candle low for long trades or above the candle high for short trades. This is adjusted if the risk exceeds 1% of total capital.
Reasoning: The stop-loss is placed at a logical level that accounts for recent price action, ensuring that the trade is given room to develop while protecting capital from unexpected market reversals.
2. Profit Target and Partial Profit Booking:
Condition: The first profit target is set at 2.1x the initial risk for long trades, and 2.5x the initial risk for short trades.
Reasoning: The 2.1x risk-reward ratio for long trades provides a solid return while maintaining a conservative risk profile. For short trades, the strategy uses a higher 2.5x risk-reward ratio because market falls tend to be sharper and quicker than rises, allowing for larger profit targets to be reached more reliably.
Partial Profit Booking: Once the first target is hit, 60% of the position is closed to lock in profits. The remaining 40% is left to run with a trailing stop.
3. ATR-Based Trailing Stop:
Condition: Once the first target is hit, the ATR (Average True Range) trailing stop is applied to the remaining position. This dynamically adjusts the stop-loss as the trade moves in a favorable direction.
Reasoning: The trailing stop allows the trade to capture further gains if the trend continues, while protecting profits if the momentum weakens. The ATR ensures that the stop adjusts according to the market's current volatility, providing flexibility and protection.
4. Time-Based Exit:
Condition: If a trade is still open by 3:20 PM, it is automatically closed to avoid end-of-day volatility.
Reasoning: The time-based exit ensures that trades are not held into the often-volatile closing minutes of the market, reducing the risk of unexpected price swings.
Capital and Risk Management:
1. Lot Size Calculation:
Condition: The strategy calculates the number of lots dynamically based on the available margin. It uses only 10% of total equity for each trade, and ensures that the maximum risk per trade does not exceed 1% of total capital.
Reasoning: This ensures that traders are not over-leveraged and that the risk is controlled for each trade. Capital protection is at the core of the strategy, ensuring that even during adverse market conditions, the trader’s capital is preserved.
2. Stop-Loss Protection:
Condition: The stop-loss is designed to ensure that no more than 1% of capital is at risk in any trade.
Reasoning: By limiting risk exposure, the strategy focuses on long-term capital preservation while still allowing for profitable trades in favorable market conditions.
STBT/BTST Facilitation:
1. Feature: The strategy allows traders the option to hold positions overnight, facilitating STBT (Sell Today Buy Tomorrow) and BTST (Buy Today Sell Tomorrow) trades.
Reasoning: Backtests show that holding positions overnight when all trade conditions are still valid can lead to beneficial outcomes. This feature allows traders to take advantage of overnight market movements, providing flexibility beyond intraday trades.
Why This Strategy Stands Out:
Price-Volume Spike Detection: Unlike traditional strategies, this one uniquely focuses on Price-Volume Spike Detection to filter out low-probability trades. By ensuring that both price and volume spikes are present, the strategy guarantees that trades are placed only when there is significant market momentum.
Risk Management with Capital Protection: The strategy strictly limits the risk per trade to 1% of capital, ensuring long-term capital preservation. This is especially important for traders who wish to avoid large drawdowns and prefer a sustainable approach to trading.
2.5x Risk-Reward for Short Trades: Recognizing the sharpness of market declines, the strategy employs a 2.5x risk-reward ratio for short trades, maximizing profits during bearish trends.
Dynamic Exit Strategy: With partial profit booking and ATR-based trailing stops, the strategy is designed to capture gains efficiently while protecting capital through dynamic exit conditions.
Summary of Execution:
Entry: Triggered when JMA crosses EMA, combined with Bollinger Band breakouts and Price-Volume Spike Detection.
Capital Management: Trades are executed with 10% of available capital, and the risk per trade is capped at 1%.
Exit: Trades exit when stop-loss, ATR trailing stop, or time-based exit conditions are met.
Profit Booking: 60% of the position is closed at the first target, with the remainder trailed using an ATR-based stop.
BTC 5 min SHBHilalimSB A Wedding Gift 🌙
What is HilalimSB🌙?
First of all, as mentioned in the title, HilalimSB is a wedding gift.
HilalimSB - Revealing the Secrets of the Trend
HilalimSB is a powerful indicator designed to help investors analyze market trends and optimize trading strategies. Designed to uncover the secrets at the heart of the trend, HilalimSB stands out with its unique features and impressive algorithm.
Hilalim Algorithm and Fixed ATR Value:
HilalimSB is equipped with a special algorithm called "Hilalim" to detect market trends. This algorithm can delve into the depths of price movements to determine the direction of the trend and provide users with the ability to predict future price movements. Additionally, HilalimSB uses its own fixed Average True Range (ATR) value. ATR is an indicator that measures price movement volatility and is often used to determine the strength of a trend. The fixed ATR value of HilalimSB has been tested over long periods and its reliability has been proven. This allows users to interpret the signals provided by the indicator more reliably.
ATR Calculation Steps
1.True Range Calculation:
+ The True Range (TR) is the greatest of the following three values:
1. Current high minus current low
2. Current high minus previous close (absolute value)
3. Current low minus previous close (absolute value)
2.Average True Range (ATR) Calculation:
-The initial ATR value is calculated as the average of the TR values over a specified period
(typically 14 periods).
-For subsequent periods, the ATR is calculated using the following formula:
ATRt=(ATRt−1×(n−1)+TRt)/n
Where:
+ ATRt is the ATR for the current period,
+ ATRt−1 is the ATR for the previous period,
+ TRt is the True Range for the current period,
+ n is the number of periods.
Pine Script to Calculate ATR with User-Defined Length and Multiplier
Here is the Pine Script code for calculating the ATR with user-defined X length and Y multiplier:
//@version=5
indicator("Custom ATR", overlay=false)
// User-defined inputs
X = input.int(14, minval=1, title="ATR Period (X)")
Y = input.float(1.0, title="ATR Multiplier (Y)")
// True Range calculation
TR1 = high - low
TR2 = math.abs(high - close )
TR3 = math.abs(low - close )
TR = math.max(TR1, math.max(TR2, TR3))
// ATR calculation
ATR = ta.rma(TR, X)
// Apply multiplier
customATR = ATR * Y
// Plot the ATR value
plot(customATR, title="Custom ATR", color=color.blue, linewidth=2)
This code can be added as a new Pine Script indicator in TradingView, allowing users to calculate and display the ATR on the chart according to their specified parameters.
HilalimSB's Distinction from Other ATR Indicators
HilalimSB emerges with its unique Average True Range (ATR) value, presenting itself to users. Equipped with a proprietary ATR algorithm, this indicator is released in a non-editable form for users. After meticulous testing across various instruments with predetermined period and multiplier values, it is made available for use.
ATR is acknowledged as a critical calculation tool in the financial sector. The ATR calculation process of HilalimSB is conducted as a result of various research efforts and concrete data-based computations. Therefore, the HilalimSB indicator is published with its proprietary ATR values, unavailable for modification.
The ATR period and multiplier values provided by HilalimSB constitute the fundamental logic of a trading strategy. This unique feature aids investors in making informed decisions.
Visual Aesthetics and Clear Charts:
HilalimSB provides a user-friendly interface with clear and impressive graphics. Trend changes are highlighted with vibrant colors and are visually easy to understand. You can choose colors based on eye comfort, allowing you to personalize your trading screen for a more enjoyable experience. While offering a flexible approach tailored to users' needs, HilalimSB also promises an aesthetic and professional experience.
Strong Signals and Buy/Sell Indicators:
After completing test operations, HilalimSB produces data at various time intervals. However, we would like to emphasize to users that based on our studies, it provides the best signals in 1-hour chart data. HilalimSB produces strong signals to identify trend reversals. Buy or sell points are clearly indicated, allowing users to develop and implement trading strategies based on these signals.
For example, let's imagine you wanted to open a position on BTC on 2023.11.02. You are aware that you need to calculate which of the buying or selling transactions would be more profitable. You need support from various indicators to open a position. Based on the analysis and calculations it has made from the data it contains, HilalimSB would have detected that the graph is more suitable for a selling position, and by producing a sell signal at the most ideal selling point at 08:00 on 2023.11.02 (UTC+3 Istanbul), it would have informed you of the direction the graph would follow, allowing you to benefit positively from a 2.56% decline.
Technology and Innovation:
HilalimSB aims to enhance the trading experience using the latest technology. With its innovative approach, it enables users to discover market opportunities and support their decisions. Thus, investors can make more informed and successful trades. Real-Time Data Analysis: HilalimSB analyzes market data in real-time and identifies updated trends instantly. This allows users to make more informed trading decisions by staying informed of the latest market developments. Continuous Update and Improvement: HilalimSB is constantly updated and improved. New features are added and existing ones are enhanced based on user feedback and market changes. Thus, HilalimSB always aims to provide the latest technology and the best user experience.
Social Order and Intrinsic Motivation:
Negative trends such as widespread illegal gambling and uncontrolled risk-taking can have adverse financial effects on society. The primary goal of HilalimSB is to counteract these negative trends by guiding and encouraging users with data-driven analysis and calculable investment systems. This allows investors to trade more consciously and safely.
What is BTC 5 min ☆SHB Strategy🌙?
BTC 5 min ☆SHB Strategy is a strategy supported by the HilalimSB algorithm created by the creator of HilalimSB. It automatically opens trades based on the data it receives, maintaining trades with its uniquely defined take profit and stop loss levels, and automatically closes trades when necessary. It stands out in the TradingView world with its unique take profit and stop loss markings. BTC 5 min ☆SHB Strategy is close to users' initiatives and is a strategy suitable for 5-minute trades and scalp operations developed on BTC.
What does the BTC 5 min ☆SHB Strategy target?
The primary goal of BTC 5 min ☆SHB Strategy is to close trades made by traders in short timeframes as profitably as possible and to determine the most effective trading points in low time periods, considering the commission rates of various brokerage firms. BTC 5 min ☆SHB Strategy is one of the rare profitable strategies released in short timeframes, with its useful interface, in addition to existing strategies in the markets. After extensive backtesting over a long period and achieving above-average success, BTC 5 min ☆SHB Strategy was decided to be released. Following the completion of test procedures under market conditions, it was presented to users with the unique visual effects of ☆SB.
BTC 5 min ☆SHB Strategy and Heikin Ashi
BTC 5 min ☆SHB Strategy produces data in Heikin-Ashi chart types, but since Heikin-Ashi chart types have their own calculation method, BTC 5 min ☆SHB Strategy has been published in a way that cannot produce data in this chart type due to BTC 5 min ☆SHB Strategy's ideology of appealing to all types of users, and any confusion that may arise is prevented in this way. Heikin-Ashi chart types, especially in short time intervals, carry significant risks considering the unique calculation methods involved. Thus, the possibility of being misled by the coder and causing financial losses has been completely eliminated. After the necessary conditions determined by the creator of BTC 5 min ☆SHB are met, BTC 5 min ☆SHB Heikin-Ashi will be shared exclusively with invited users only, upon request, to users who request an invitation.
Key Features:
+HilalimSHB Algorithm: This algorithm uses a dynamic ATR-based trend-following mechanism to identify the current market trend. The strategy detects trend reversals and takes positions accordingly.
+Heikin Ashi Compatibility: The strategy is optimized to work only with standard candlestick charts and automatically deactivates when Heikin Ashi charts are in use, preventing false signals.
+Advanced Chart Enhancements: The strategy offers clear graphical markers for buy/sell signals. Candlesticks are automatically colored based on trend direction, making market trends easier to follow.
Strategy Parameters:
+Take Profit (%): Defines the target price level for closing a position and automates profit-taking. The fixed value is set at 2%.
+Stop Loss (%): Specifies the stop-loss level to limit losses. The fixed value is set at 3%.
The shared image is a 5-minute chart of BTCUSDC.P with a fixed take profit value of 2% and a fixed stop loss value of 3%. The trades are opened with a commission rate of 0.063% set for the USDT trading pair on Binance.🌙
Configurable Level Trading StrategyThe Dynamic Level Reversal Strategy is a trading approach designed to capitalize on price movements between key support and resistance levels. This strategy leverages configurable levels the trader determines, allowing for flexibility and adaptation to different market conditions.
Key Features:
Configurable Levels:
The strategy uses three key levels: Level 1 (Support), Level 2 (Middle), and Level 3 (Resistance). These levels can be adjusted directly within the script settings, making the strategy adaptable to various trading scenarios.
Buy and Sell Signals:
A buy signal is triggered when the price touches Level 1 and shows signs of reversal. The trader enters a position and sets an initial stop-loss just below Level 1.
As the price moves upward, the stop-loss is dynamically adjusted to just below Level 2 and Level 3, locking in profits while managing risk.
A sell signal is generated if the price reverses and crosses below the current stop-loss level, ensuring the trader exits the position with minimized losses.
Iterative Process:
The strategy allows for iterative trades, where the trader re-enters positions at Level 1 or Level 2 if the price revisits these levels, continually adjusting stop-losses and take-profit targets as the price oscillates between the defined levels.
Ideal Use Cases:
Range-Bound Markets: The strategy is particularly effective in markets where the price tends to oscillate between well-defined support and resistance levels.
Volatile Markets: The dynamic adjustment of stop-loss levels helps protect against sudden price reversals, making it suitable for volatile market conditions.
How to Use:
Set the desired levels (Level 1, Level 2, Level 3) based on your market analysis.
The script will automatically generate buy and sell signals, and adjust stop-loss levels as the price moves through the levels.
Monitor the signals and execute trades according to the strategy's guidelines.
IsAlgo - Reverse Band Strategy► Overview:
The Reverse Band Strategy leverages a custom band indicator combined with a candlestick pattern for trade entries. The strategy initiates trades when a candle closes outside the bands, anticipating that the price will revert inside the bands and reach the opposite side.
► Description:
The Reverse Band Strategy is built around a sophisticated custom band indicator designed to identify potential reversal points in the market. The bands are calculated using a proprietary formula that factors in the trend's slope, the highest and lowest points within the trend, the average price movement, and the number of candles that form the trend. This advanced calculation allows for a dynamic and responsive band that adjusts to market conditions.
Once the band edges are identified, the strategy continuously monitors for candles that close outside these bands. When such a candle is detected, it signals a potential reversal, triggering an entry. The expectation is that the price will revert back inside the bands and move towards the opposite band edge.
How it Works:
Band Calculation: The strategy continuously updates the band edges using the aforementioned factors.aforementioned factors.
Signal Detection: It waits for a candle to close outside the bands.
Trade Entry: When an outside-close candle is detected, the strategy enters a trade expecting the price to revert to the opposite band edge.
Customization: Users can define the characteristics of the entry candle, such as its size relative to previous candles, to ensure it meets specific conditions before triggering a trade.
↑ Long Trade Example:
The entry candle closes below the lower band, indicating a potential upward reversal. The strategy enters a long position expecting the price to move towards the upper band.
↓ Short Trade Example:
The entry candle closes above the upper band, signaling a potential downward reversal. The strategy enters a short position anticipating the price to revert towards the lower band.
► Features and Settings:
⚙︎ Band Customization: Adjust band length, smoothness, and minimum distance to fit different market conditions and trading styles.
⚙︎ Entry Candle: Customize criteria such as candle size, body, and relative position to previous candles to ensure precise entry signals.
⚙︎ Trading Session: This feature allows users to define specific trading hours during which the strategy should operate, ensuring trades are executed only during preferred market periods.
⚙︎ Trading Days: Users can specify which days the strategy should be active, offering the flexibility to avoid trading on specific days of the week.
⚙︎ Backtesting: Enables a backtesting period during which the strategy can be tested over a selected start and end date. This feature can be deactivated if not needed.
⚙︎ Trades: Configure trade direction (long, short, or both), position sizing (fixed or percentage-based), maximum number of open trades, and trade limitations per day or based on band.
⚙︎ Trades Exit: Set profit/loss limits, specify trade duration, or exit based on band reversal signals.
⚙︎ Stop Loss: Various stop-loss methods are available, including a fixed number of pips, ATR-based, or using the highest or lowest price points within a specified number of previous candles. Additionally, trades can be closed after a specific number of candles move in the opposite direction of the trade.
⚙︎ Break Even: This feature adjusts the stop loss to a break-even point once certain conditions are met, such as reaching predefined profit levels, to protect gains.
⚙︎ Trailing Stop: The trailing stop feature adjusts the stop loss as the trade moves into profit, securing gains while potentially capturing further upside.
⚙︎ Take Profit: Up to three take-profit levels can be set using various methods, such as a fixed amount of pips, ATR, or risk-to-reward ratios based on the stop loss. Alternatively, users can specify a set number of candles moving in the direction of the trade.
⚙︎ Alerts: The strategy includes a comprehensive alert system that informs the user of all significant actions, such as trade openings and closings. It supports placeholders for dynamic values like take-profit levels and stop-loss prices.
⚙︎ Dashboard: A visual display provides detailed information about ongoing and past trades on the chart, helping users monitor the strategy's performance and make informed decisions.
► Backtesting Details:
Timeframe: 30-minute GBPUSD chart
Initial Balance: $10,000
Order Size: 5000 units
Commission: 0.02%
Slippage: 5 ticks
MetaFOX DCA (ASAP-RSI-BB%B-TV)Welcome To ' MetaFOX DCA (ASAP-RSI-BB%B-TV) ' Indicator.
This is not a Buy/Sell signals indicator, this is an indicator to help you create your own strategy using a variety of technical analyzing options within the indicator settings with the ability to do DCA (Dollar Cost Average) with up to 100 safety orders.
It is important when backtesting to get a real results, but this is impossible, especially when the time frame is large, because we don't know the real price action inside each candle, as we don't know whether the price reached the high or low first. but what I can say is that I present to you a backtest results in the worst possible case, meaning that if the same chart is repeated during the next period and you traded for the same period and with the same settings, the real results will be either identical to the results in the indicator or better (not worst). There will be no other factors except the slippage in the price when executing orders in the real trading, So I created a feature for that to increase the accuracy rate of the results. For more information, read this description.
Below I will explain all the properties and settings of the indicator:
A) 'Buy Strategies' Section: Your choices of strategies to Start a new trade: (All the conditions works as (And) not (OR), You have to choose one at least and you can choose more than one).
- 'ASAP (New Candle)': Start a trade as soon as possible at the opening of a new candle after exiting the previous trade.
- 'RSI': Using RSI as a technical analysis condition to start a trade.
- 'BB %B': Using BB %B as a technical analysis condition to start a trade.
- 'TV': Using tradingview crypto screener as a technical analysis condition to start a trade.
B) 'Exit Strategies' Section: Your choices of strategies to Exit the trades: (All the conditions works as (And) not (OR), You can choose more than one, But if you don't want to use any of them you have to activate the 'Use TP:' at least).
- 'ASAP (New Candle)': Exit a trade as soon as possible at the opening of a new candle after opening the previous trade.
- 'RSI': Using RSI as a technical analysis condition to exit a trade.
- 'BB %B': Using BB %B as a technical analysis condition to exit a trade.
- 'TV': Using tradingview crypto screener as a technical analysis condition to exit a trade.
C) 'Main Settings' Section:
- 'Trading Fees %': The Exchange trading fees in percentage (trading Commission).
- 'Entry Price Slippage %': Since real trading differs from backtest calculations, while in backtest results are calculated based on the open price of the candle, but in real trading there is a slippage from the open price of the candle resulting from the supply and demand in the real time trading, so this feature is to determine the slippage Which you think it is appropriate, then the entry prices of the trades will calculated higher than the open price of the start candle by the percentage of slippage that you set. If you don't want to calculate any slippage, just set it to zero, but I don't recommend that if you want the most realistic results.
Note: If (open price + slippage) is higher than the high of the candle then don't worry, I've kept this in consideration.
- 'Use SL': Activate to use stop loss percentage.
- 'SL %': Stop loss percentage.
- 'SL settings options box':
'SL From Base Price': Calculate the SL from the base order price (from the trade first entry price).
'SL From Avg. Price': Calculate the SL from the average price in case you use safety orders.
'SL From Last SO.': Calculate the SL from the last (lowest) safety order deviation.
ex: If you choose 'SL From Avg. Price' and SL% is 5, then the SL will be lower than the average price by 5% (in this case your SL will be dynamic until the price reaches all the safety orders unlike the other two SL options).
Note: This indicator programmed to be compatible with '3COMMAS' platform, but I added more options that came to my mind.
'3COMMAS' DCA bots uses 'SL From Base Price'.
- 'Use TP': Activate to use take profit percentage.
- 'TP %': Take profit percentage.
- 'Pure TP,SL': This feature was created due to the differences in the method of calculations between API tools trading platforms:
If the feature is not activated and (for example) the TP is 5%, this means that the price must move upward by only 5%, but you will not achieve a net profit of 5% due to the trading fees. but If the feature is activated, this means that you will get a net profit of 5%, and this means that the price must move upward by (5% for the TP + the equivalent of trading fees). The same idea is applied to the SL.
Note: '3COMMAS' DCA bots uses activated 'Pure TP,SL'.
- 'SO. Price Deviation %': Determines the decline percentage for the first safety order from the trade start entry price.
- 'SO. Step Scale': Determines the deviation multiplier for the safety orders.
Note: I'm using the same method of calculations for SO. (safety orders) levels that '3COMMAS' platform is using. If there is any difference between the '3COMMAS' calculations and the platform that you are using, please let me know.
'3COMMAS' DCA bots minimum 'SO. Price Deviation %' is (0.21)
'3COMMAS' DCA bots minimum 'SO. Step Scale' is (0.1)
- 'SO. Volume Scale': Determines the base order size multiplier for the safety orders sizes.
ex: If you used 10$ to buy at the trade start (base order size) and your 'SO. Volume Scale' is 2, then the 1st SO. size will be 20, the 2nd SO. size will be 40 and so on.
- 'SO. Count': Determines the number of safety orders that you want. If you want to trade without safety orders set it to zero.
'3COMMAS' DCA bots minimum 'SO. Volume Scale' is (0.1)
- 'Exchange Min. Size': The exchange minimum size per trade, It's important to prevent you from setting the base order Size less than the exchange limit. It's also important for the backtest results calculations.
ex: If you setup your strategy settings and it led to a loss to the point that you can't trade any more due to insufficient funds and your base order size share from the strategy becomes less than the exchange minimum trade size, then the indicator will show you a warning and will show you the point where you stopped the trading (It works in compatible with the initial capital). I recommend to set it a little bit higher than the real exchange minimum trade size especially if you trade without safety orders to not stuck in the trade if you hit the stop loss
- 'BO. Size': The base order size (funds you use at the trade entry).
- 'Initial Capital': The total funds allocated for trading using your strategy settings, It can be more than what is required in the strategy to cover the deficit in case of a loss, but it should not exceed the funds that you actually have for trading using this strategy settings, It's important to prevent you from setting up a strategy which requires funds more than what you have. It's also has other important benefits (refer to 'Exchange Min. Size' for more information).
- 'Accumulative Results': This feature is also called re-invest profits & risk reduction. If it's not activated then you will use the same funds size in each new trade whether you are in profit or loss till the (initial capitals + net results) turns insufficient. If it's activated then you will reuse your profits and losses in each new trade.
ex: The feature is active and your first trade ended with a net profit of 1000$, the next trade will add the 1000$ to the trade funds size and it will be distributed as a percentage to the BO. & SO.s according to your strategy settings. The same idea in case of a loss, the trade funds size will be reduced.
D) 'RSI Strategy' Section:
- 'Buy': RSI technical condition to start a trade. Has no effect if you don't choose 'RSI' option in 'Buy Strategies'.
- 'Exit': RSI technical condition to exit a trade. Has no effect if you don't choose 'RSI' option in 'Exit Strategies'.
E) 'TV Strategy' Section:
- 'Buy': TradingView Crypto Screener technical condition to start a trade. Has no effect if you don't choose 'TV' option in 'Buy Strategies'.
- 'Exit': TradingView Crypto Screener technical condition to exit a trade. Has no effect if you don't choose 'TV' option in 'Exit Strategies'.
F) 'BB %B Strategy' Section:
- 'Buy': BB %B technical condition to start a trade. Has no effect if you don't choose 'BB %B' option in 'Buy Strategies'.
- 'Exit': BB %B technical condition to exit a trade. Has no effect if you don't choose 'BB %B' option in 'Exit Strategies'.
G) 'Plot' Section:
- 'Signals': Plots buy and exit signals.
- 'BO': Plots the trade entry price (base order price).
- 'AVG': Plots the trade average price.
- 'AVG options box': Your choice to plot the trade average price type:
'Avg. With Fees': The trade average price including the trading fees, If you exit the trade at this price the trade net profit will be 0.00
'Avg. Without Fees': The trade average price but not including the trading fees, If you exit the trade at this price the trade net profit will be a loss equivalent to the trading fees.
- 'TP': Plots the trade take profit price.
- 'SL': Plots the trade stop loss price.
- 'Last SO': Plots the trade last safety order that the price reached.
- 'Exit Price': Plots a mark on the trade exit price, It plots in 3 colors as below:
Red (Default): Trade exit at a loss.
Green (Default): Trade exit at a profit.
Yellow (Default): Trade exit at a profit but this is a special case where we have to calculate the profits before reaching the safety orders (if any) on that candle (compatible with the idea of getting strategy results at the worst case).
- 'Result Table': Plots your strategy result table. The net profit percentage shown is a percentage of the 'initial capital'.
- 'TA Values': Plots your used strategies Technical analysis values. (Green cells means valid condition).
- 'Help Table': Plots a table to help you discover 100 safety orders with its deviations and the total funds needed for your strategy settings. Deviations shown in red is impossible to use because its price is <= 0.00
- 'Portfolio Chart': Plots your Portfolio status during the entire trading period in addition to the highest and lowest level reached. It's important when evaluating any strategy not only to look at the final result, but also to look at the change in results over the entire trading period. Perhaps the results were worryingly negative at some point before they rose again and made a profit. This feature helps you to see the whole picture.
- 'Welcome Message': Plots a welcome message and showing you the idea behind this indicator.
- 'Green Net Profit %': It plots the 'Net Profit %' in the result table in green color if the result is equal to or above the value that you entered.
- 'Green Win Rate %': It plots the 'Win Rate %' in the result table in green color if the result is equal to or above the value that you entered.
- 'User Notes Area': An empty text area, Feel free to use this area to write your notes so you don't forget them.
The indicator will take care of you. In some cases, warning messages will appear for you. Read them carefully, as they mean that you have done an illogical error in the indicator settings. Also, the indicator will sometimes stop working for the same reason mentioned above. If that happens then click on the red (!) next to the indicator name and read the message to find out what illogical error you have done.
Please enjoy the indicator and let me know your thoughts in the comments below.
[Opening Range Breakout] S&R Strategy with Backtest (TSO) S&R Strategy with Backtest (TSO)
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This indicator serves as a comprehensive full-cycle trading system, providing alerts at each stage of the trade, from opening to closure. The algorithm initiates by calculating the Opening/Pre-Market Price Range, waiting for a breakout to generate signals, and establishing TP (Take Profit and SL (Stop Loss) levels. The Opening/Pre-Market range, known for its robust support and resistance levels, is a key element. To filter out false breakouts and capture valid ones, the indicator incorporates a Smart Breakout feature, requiring confirmation through an initial breakout, a confirmation bounce, and a subsequent confirmation breakout. The indicator offers a variety of automated approaches for TP (Take-Profit) and SL (Stop-Loss) settings. These include leveraging opening range levels, both the most recent and historical S&R (Support and Resistance) levels, and an ATR (Average True Range) trailing stop-loss. This diverse set of tools ensure flexibility in tailoring TP (Take-Profit) and SL (Stop-Loss) parameters to different market conditions, contributing to a more adaptive and robust trading system. Additionally, a series of signal analysis tools, including candle bar analysis, divergence, and volume, enhance the precision of trading signals.
* Works with popular timeframes: 1M, 3M, 5M, 15M, 30M, 45M, 1H.
* Works best with Indices, Stocks, and Commodities, since there is pre-market price movement, which is used to obtain support and resistance price range.
* Every action of the trade is calculated on a confirmed closed candle bar state (barstate.isconfirmed), so the indicator will never repaint.
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Indicator visual examples with various instruments:
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Strategy Config: ORB_AAPL(NASDAQ)_15M
Example of Signal Cleanup confirmations via SMA and ATR. Take-Profit is calculated per optimal S&R (resistance) most recent levels.
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Strategy Config: ORB_AMD(NASDAQ)_5M
Example of optimal S&R (resistance) level from previous day for Take-Profit 1 target, which gets hit.
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Strategy Config: ORB_META(NASDAQ)_5M
Example of dynamic SL (Stop-Loss), which reduces the risk by moving to the new support level, which is at the same time is below the current price. Also Signal Cleanup confirmations via SMA, ATR and VWAP
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Strategy Config: ORB_MSFT(NASDAQ)_15M
Example of automated ATR Trail Stop-Loss activation at no optimal S&R (support) feature.
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Strategy Config: ORB_NFLX(NASDAQ)_3M
Example of a skipped LONG trade due to no optimal S&R (support) for Stop-Loss (can be seen per chart that it would be a loss trade). On another side, a SHORT SMA Confirmed trade hits all 3 profit targets.
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Strategy Config: ORB_NVDA(NASDAQ)_15M
Example of no optimal support for SHORT Take-Profit targets, with ATR Trail Stop-Loss.
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Strategy Config: ORB_SPY(AMEX)_15M
Example of several signal confirmations at the same time (SMA, VWAP, EWO) and S&R-TP-Entry-SL SL (Stop-Loss) system, which at trade open sets SL (Stop-Loss) per optimal S&R (since this is a LONG trade - support) and then moves to Entry at first take-profit.
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Trading open/close/TP/SL labels, plots and colors explanations:
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>>> Opening/Pre-Market range: White dashed lines show opening range/pre-market levels with dotted white line extend along the Trading Schedule (if Trading Schedule is turned off - it will extend until next day).
>>> Smart Breakout: 1) Initial Breakout: "init_Brekout" | 2) Confirmation Bounce: "conf_Bounce" | 3) Confirmation Breakout: "conf_Breakout" (additional lables on chart can be hidden with only Confirmation Breakout shown).
>>> Additional S&R (Support and Resistance) lines: yellow - support, blue - resistance (can be hidden).
>>>>> LONG open: green "house" looking arrow below candle bar.
>>>>> SHORT open: red "house" looking arrow above candle bar.
>>>>> LONG/SHORT take-profit target: green/red circles (multi-profit > TP2/3/4/5 smaller circles).
>>>>> LONG/SHORT stop-loss target: green/red + crosses.
>>>>> LONG/SHORT take-profit hits: green/red diamonds.
>>>>> LONG/SHORT stop-loss hits: green/red X-crosses.
>>>>> LONG/SHORT EOD (End of Day | Intraday style) close (profitable trade): green/red squares.
>>>>> LONG/SHORT EOD (End of Day | Intraday style) close (loss trade): green/red PLUS(+)-crosses.
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STATS TABLE ///////////////////////////////////////////////////////////////
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>>> Trading STATS table on the chart showing current trade direction, Last TP (Take-Profit) Taken, Current Trade PL (profit/loss in price difference from trade open to the very current state).
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CUSTOM TRADING DATE RANGE /////////////////////////////////////////////////
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>>>>> This feature can be used to manually set indicator trading range from and to a specific date and time. NOTE: This is not intended for a very long date range backtesting, utilize TradingView Strategy Tester for that.
* Use TradingView “Strategy Tester” to see Backtesting results
NOTE: If Strategy Tester does not show any results with Date Ranged fully unchecked, there may be an issue where a script opens a trade, but there is not enough TradingView power to set the Take-Profit and Stop-Loss and somehow an open trade gets stuck and never closes, so there are “no trades present”. In such case - manually check “Start”/“End” dates or use “Deep Backtesting” feature!
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INTRADAY/TRADING SCHEDULE | ET (EASTERN TIMEZONE) ////////////////////////
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>>> Trading Schedule - On/Off: This is where an Intraday Session or any custom session can be turned on and then scheduled.
>>>>> Trading Schedule - Time: Trade open Signals/Alerts time zone Hours. | NOTE: US Market Active Hours: 09:30 - 16:00 ET / Power Hour: 15:00 - 16:00 ET)
>>> Trading Schedule - EOD(End of Day) Close - On/Off: Close trade if still open by certain hour (set below).
>>>>> Trading Schedule - EOD(End of Day) Close - Hour (ET): US trading session closes at 4PM ET > 16:00.
Here is when the trade will close with EOD(End of Day) Close/Trading Cut Off Hour set to 16, which is end of US trading session:
1/3/5min > will close at 15:55pm ET
15min > will close at 15:45pm ET
30min > will close at 15:30pm ET
45min > will close at 15:45pm ET
60min > will close at 16:00pm ET
Here is when the trade will close with EOD(End of Day) Close/Trading Cut Off Hour set to 15, which is 1 hour before the end of US trading session (right before power hour starts):
1/3/5min > will close at 14:55pm ET
15min > will close at 14:45pm ET
30min > will close at 14:30pm ET
45min > will close at 14:45pm ET
60min > will close at 15:00pm ET
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TRADE SIGNAL CONFIGURATION ////////////////////////////////////////////////
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>>> Opening Range - Time Period (ET): Opening/Pre-Market Range time, which by default is set to US Session Pre-Market Range, can be customized to any time range as there are different market hours around the world and this setting can be customized to any time. Pre-Market Time/Price Range Hours(ET) | Pre-Market EU/Asia Hours: 4:00-9:30 ET | Pre-Market US (NY) Hours: 7:00-9:30 ET | Post-Market US Hours: 16:00-19:00 ET | First US Market Hour: 9:30-10:30 ET | Power Hour: 15:00-16:00)
>>> Opening Range - Levels Structure: determines how the price range is calculated, based on the highest/lowest price zones or based on the candle body bar.
>>> Opening Range - Breakout System: "Simple": bar close price has to simply break the opening range level | "Smart": After initial breakout (which is basically 'Simple' Breakout), a price come back is expected to the opening range level, a bounce, then a confirmation breakout with price closing ahead of the initial breakout.
>>>>> Opening Range - Smart Breakout: # of bars until Initial Breakout becomes invalid
>>>>> Opening Range - Smart Breakout: Bounce Settings, "Cross-Return" - LONG: Price has to cross down the initial breakout S&R, but never close below it; SHORT: Price has to cross up the initial breakout S&R, but then close above it; ||| "Cross-Close-Return" - LONG: At least 1 candle has to close below initial breakout S&R; SHORT: At least 1 candle has to close above initial breakout S&R.
>>>>> Alerts - Opening Range - Smart Breakout: Confirmation Bounce Alert. Trigger an alert at confirmation bounce. This is for live trading (especially scalping) Smart Breakout approach - to get ready to open the trade in the correct direction.
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TAKE-PROFIT/STOP-LOSS CONFIGURATION ///////////////////////////////////////
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>>> TP (Take-Profit) and SL (Stop-Loss): S&R Search - Left Bars: This setting is for calculating optimal S&R (Support and Resistance) levels (in combination with below - Right Bars) for S&R (Support and Resistance) TP (Take-Profit) levels calculations. NOTE: if at any point - there will be no available S&R (Support & Resistance) found for SL (Stop-Loss, 'S&R-Dynamic-SL' or 'S&R-Static-SL' setting, since both settings search for optimal SL (Stop-Loss) at trade open) or TP (Take-Profit, at any setting, since at trade open, an optimal TP (Take-Profit) level is searched) > SL (Stop-Loss) will automatically switch to trailing ATR-Trailing-SL and the trade will continue to run until it either hits ATR-Trailing-SL (Stop-Loss) or closes at EOD (End of Day).
>>> TP (Take-Profit) and SL (Stop-Loss): S&R Search - Right Bars: This setting is for calculating optimal S&R (Support and Resistance) levels (in combination with above - Left Bars) for S&R (Support and Resistance) TP (Take-Profit) levels calculations. NOTE: if at any point - there will be no available S&R (Support & Resistance) found for SL (Stop-Loss, 'S&R-Dynamic-SL' or 'S&R-Static-SL' setting, since both settings search for optimal SL (Stop-Loss) at trade open) or TP (Take-Profit, at any setting, since at trade open, an optimal TP (Take-Profit) level is searched) > SL (Stop-Loss) will automatically switch to trailing ATR-Trailing-SL and the trade will continue to run until it either hits ATR-Trailing-SL (Stop-Loss) or closes at EOD (End of Day).
>>> TP (Take-Profit) and SL (Stop-Loss): S&R Search - Custom Resolution: This is a custom timeframe setting specifically for S&R Search, it disregards current chart timeframe. This is great to use for scalping, for example: with main chart set to 1min and the custom timeframe set to 3min or 5min - there will be stronger support/resistance levels with more detailed price action.
>>> TP (Take-Profit) and SL (Stop-Loss): # of Bars (5000 max) to search back for optimal Support and Resistance levels: This is how many candles will be searched backwards for previous S&Rs (Support and Resistance) to find the optimal levels for TP (Take-Profit) and SL (Stop-Loss). NOTE: If SL (Stop-Loss) System is set to 'ATR-Trailing-SL' - this setting is only relevant for searching TP (Take-Profit) levels.
>>> TP (Take-Profit) and SL (Stop-Loss): At Trade Open - No S&R (Support and Resistance) found behavior: 'Skip Trade': If at trade open there are no S&R (Support and Resistance) levels for TP1 (Take-Profit 1) or SL (Stop-Loss) - trade is skipped. 'Open/ATR-Trailing-SL': If at trade open there are no S&R (Support and Resistance) levels for TP1 (Take-Profit 1) or SL (Stop-Loss), the trade will still be open with SL (Stop-Loss) set to 'ATR-Trailing-SL'.
>>> TP (Take-Profit) System: Pre-Market-Range-TP: All TP (Take-Profit) targets are calculated at trade open using the distance between Support and Resistance per Opening Pre-market Range and then divided by TP (Take-Profit) Divider, which can be set below; S&R-Current-Optimal-TP1: TP1 (Take-Profit) level is set per currently available S&R (Support & Resistance), if none available - historical S&R (Support & Resistance) levels will be searched, remaining TP (Take-Profit) targets (if selected, up to 5 # of TPs) are searched through most recent closest historical S&R (Support & Resistance) levels; S&R-Historic-Optimal-TP1: TP1 (Take-Profit) level is set per historically most recent closest available S&R (Support & Resistance) to the Entry price, remaining TP (Take-Profit) targets (if selected, up to 5 # of TPs) are searched through historical S&R (Support & Resistance) levels as well.
>>> TP (Take-Profit, Pre-Market-Range-TP) Divider #: This is for 'Pre-Market-Range-TP' setting only, where TP (Take-Profit) level is the distance between top/bottom levels of the opening range. It can be reduced by the divider #. (1 - full distance; 2 - 1/2 distance; 3 - 1/3 distance; etc.
>>> TP (Take-Profit) # of targets: It is wise to divide the trade into several profit targets. With this setting - up to 5 TP (Take-Profit) targets can be approached. The trade will be equally divided up by the selected # of TP (Take-Profit) targets.
>>> TP (Take-Profit) target(s) Consumed: Signal Bar consuming Take-Profits - trade signal bar is big enough to 'consume'/close ahead of the first TP setting > the signal can either be skipped, or all Take-Profit targets pushed ahead by average bar size).
>>> TP (Take-Profit) Offset - On/Off: This is a feature where TP (Take-Profit) target will be considered taken even if the price never crosses the target(s), but comes close enough (based on the offset amount). Set the offset amount below.
>>>>> TP (Take-Profit) Offset - Amount: Some Examples: (for SPY 0.1 would be $0.10 offset - if TP1 is $400 and price hits $399.90 > TP1 considered taken/signal shown/alert) | NOTE: For EURUSD, it is very different and if wrong will show TP1 immediately at trade open, typical good offset for EURUSD is: 0.0005 | Similar for BTCUSD, for example: 10 - $10 offset, if TP is $15,000 > $14,990.
>>> SL (Stop-Loss) System: 'Pre-Market-Range-SL': SL (Stop-Loss) is set to the opposite market range level from trade direction; 'S&R-Static-SL': SL (Stop-Loss) is set at trade open per optimal most recent S&R level and remains there until trade closes; 'S&R-Dynamic-SL': SL (Stop-Loss) is set at a trade open per optimal S&R (Support and Resistance) level from the most recent AND historical S&Rs (Support and Resistance), with every bar closed it will check if there are new S&Rs (Support and Resistance) levels, if these levels appear closer to the current price then current level - it will move SL (Stop-Loss) to that level, therefore reducing the risk; 'ATR-Trailing-SL': SL (Stop-Loss) is trail-following the ATR (Average True Range) line, NOTE: If at signal trigger, ATR will be against the trade direction - trade open signal will be skipped; 'S&R-TP-Entry-SL': SL (Stop-Loss) initially is set per S&R, then moves to Entry price at the very first TP (Take-Profit) hit and remains there until trade closes; 'S&R-TP-Trail-SL': SL (Stop-Loss) initially is set per S&R, then moves to Entry at TP1 (Take-Profit 1) hit, then keeps trailing per previously taken profit targets (TP2 taken, SL moves to TP1 | TP3 taken, SL moves to TP2 | TP4 taken, SL moves to TP3). NOTE: 'ATR-Trailing-SL' will not switch automatically if 'S&R-Dynamic-SL', S&R-TP-Entry-SL', 'S&R-TP-Trail-SL' system is selected, as already the most optimal SL (Stop-Loss) level is calculated - it will switch automatically only with 'S&R-Static-SL' system.
>>> SL (Stop-Loss) - On/Off: Without SL (Stop-Loss), unless EOD (End of Day) Close is turned on - there will be no SL (Stop-Loss) at all!
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SIGNAL ANALYSIS AND CLEANUP ///////////////////////////////////////////////
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>>> Signal Cleanup - Bar Color: Include Bar Color (bullish/bearish) confirmation, LONG signal will only be opened if signal bar is green/bullish, SHORT if red/bearish.
>>> Signal Cleanup - Bar Directional Structure: Skip opposite bar structure types signals (For example: bearish green hammer).
>>> Signal Cleanup - Bar Doji Skip: Skip doji (indecisive) candles signals.
>>> Signal Cleanup - EWO (Elliott Wave Oscillator): Include EWO (Elliott Wave Oscillator), LONG will only be opened if EWO is bullish / SHORT if EWO is bearish.
>>> Signal Cleanup - VWAP (Volume-Weighted Average Price): Include VWAP (Volume-Weighted Average Price), LONG will only be opened if price is above VWAP / SHORT if price is below VWAP.
>>> Signal Cleanup - MA (Moving Average) Confirmation: Include MA (Moving Average), LONG will only be opened if MA is bullish / SHORT if MA is bearish.
>>> Signal Cleanup - ATR (Average True Range): Include ATR (Average True Range) confirmation, LONG will only be opened if ATR is bullish / SHORT if ATR is bearish.
>>> Signal Cleanup - Divergence(RSI + MACD): Include Divergence (RSI + MACD ) confirmation, LONG will only be opened if Divergence is bullish / SHORT if Divergence is bearish.
>>> Signal Cleanup - Volume % Strength: Include Volume strength/percentage confirmation, LONG/SHORT will only be opened with strong Volume matching the signal direction | By default, strong Volume percentage is set to 150% and weak to 50%.
>>> Signal Cleanup - Volume Above Average: Include Volume Above Moving Average (Volume closing bar closes above volume moving average) confirmation, LONG/SHORT will only be opened with Volume above average - Volume closed bar color must match the closed price color (bullish/bearish direction) + Volume bar must be closed above volume MA line).
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TP System - VERY IMPORTANT INFO!
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"TP PERCENTAGE" - amount by which current trade/position needs to be reduced/partially closed/sold.
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TP System: Dynamic
"TP PERCENTAGE" - will always be the same amount (trade/position size divided by the # of take-profit(TP) targets) and percentage to be closed will always be of the ORIGINAL trade/position.
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TP System: Static
"TP PERCENTAGE" - will always be the same amount IF take-profit(TP) targets are hit 1-by-1 (TP1 > TP2 > TP3 > TP4 > TP5), otherwise it will vary and unless it is a 1st take-profit(TP1), the REMAINING trade/position size will always be smaller than original and therefore the percentage to be closed will always be of the REMAINING trade/position and NOT the original one!
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"TP PERCENTAGE" CheatSheet (these are the only percentages you may see)
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TP PERCENTAGE---Close/Sell Amount-------------Example (trade size: 50 stocks)
20%-------------trade size * 0.2--------------50 * 0.2 = 10 stocks
25%-------------trade size * 0.25-------------50 * 0.25 = 12.5(~13) stocks
34%-------------trade size * 0.34-------------50 * 0.34 = 17 stocks
40%-------------trade size * 0.4--------------50 * 0.4 = 20 stocks
50%-------------trade size * 0.5--------------50 * 0.5 = 25 stocks
60%-------------trade size * 0.6--------------50 * 0.6 = 30 stocks
66%-------------trade size * 0.66-------------50 * 0.66 = 33 stocks
75%-------------trade size * 0.75-------------50 * 0.75 = 37.5(~38) stocks
80%-------------trade size * 0.8--------------50 * 0.8 = 40 stocks
100%------------trade size--------------------50 = 50 stocks
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If for any reason a portion of the current/remaining trade closed at such occurrence was slightly wrong, it is not an issue. Such occurrences are rare and with slight difference in partial TP closed is not significant to overall performance of our algorithms.
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Alert Settings (you don’t have to touch this section unless you will be using TradingView alerts through a Webhook to use with trading bot)
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Here is how a LONG OPEN alert looks like.
NOTE: Each label , , etc. is customizable, you can change the text of it within indicator Input settings.
ALERT >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
COIN: BTCUSD
TIMEFRAME: 15M
LONG: OPEN
ENTRY: 20000
TP1: 20500
TP2: 21000
TP3: 21500
TP4: 22500
TP5: 23500
SL: 19000
Leverage: 0
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Here is how a TP1 alert will look with 5 TPs breakdown of the trade.
NOTE1: Next to TP1 taken it will show at which price it was triggered.
NOTE2: Next to "TP Percentage" it shows how much of the CURRENT/ACTIVE/REMAINING trade needs to be closed.
NOTE2: If TP2/3/4/5 comes before TP1 - the alert will tell you exactly how many percent of the trade needs to be closed!
ALERT >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
COIN: BTCUSD
TIMEFRAME: 15M
LONG: TP1
TP1: 20500
TP Percentage: 20%
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Here is how an alert will look for LONG - STOP-LOSS.
ALERT >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
COIN: BTCUSD
TIMEFRAME: 15M
ENTRY: 20000
LONG: SL
SL: 19000
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Here is how an alert will look for LONG - EOD (End of Day) In Profit close.
ALERT >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
COIN: BTCUSD
TIMEFRAME: 15M
LONG: EOD-Close (profit)
ENTRY: 20000
EOD-Close: 21900
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Adding Alerts in TradngView
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-Add indicator to chart and make sure the correct strategy is configured (check Backtesting results)
-Right-click anywhere on the TradingView chart
-Click on Add alert
-Condition: Select this indicator by it’s name
-Immediately below, change it to "alert() function calls only", as other wise there will be 2 alerts for every alert!
-Expiration: Open-ended (that may require higher tier TradingView account, otherwise the alert will need to be occasionally re-triggered)
-Alert name: Whatever you desire
-Hit “Create”
-Note: If you change ANY Settings within the indicator – you must DELETE the current alert and create a new one per steps above, otherwise it will continue triggering alerts per old Settings!
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If you have any questions or issues with the indicator, please message me directly via TradingView.
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Good Luck! (NOTE: Trading is very risky, past performance is not necessarily indicative of future results, so please trade responsibly!)
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NOTE: There seems to be a strange glitch when strategy is running live, it will show "double-take" take-profits labels on the chart. This is not affecting the script logic and backtesting results, if you simply change the timeframe real quick to something else then back - it will no longer show the duplicate orders... this must be some sort of a glitch as every alert was thoroughly tested to make sure everything is working!
Backtest Strategy Optimizer AdapterBacktest Strategy Optimizer Adapter
With this library, you will be able to run one or multiple backtests with different variables (combinations). For example, you can run 100 backtests of Supertrend at once with an increment factor of 0.1. This way, you can easily fetch the most profitable settings and apply them to your strategy.
To get a better understanding of the code, you can check the code below.
Single backtest results
= backtest.results(date_start, date_end, long_entry, long_exit, take_profit_percentage, stop_loss_percentage, atr_length, initial_capital, order_size, commission)
Add backtest results to a table
backtest.table(initial_capital, profit_and_loss, open_balance, winrate, entries, exits, wins, losses, backtest_table_position, backtest_table_margin, backtest_table_transparency, backtest_table_cell_color, backtest_table_title_cell_color, backtest_table_text_color)
Backtest result without chart labels
= backtest.run(date_start, date_end, long_entry, long_exit, take_profit_percentage, stop_loss_percentage, atr_length, initial_capital, order_size, commission)
Backtest result profit
profit = backtest.profit(date_start, date_end, long_entry, long_exit, take_profit_percentage, stop_loss_percentage, atr_length, initial_capital, order_size, commission)
Backtest result winrate
winrate = backtest.winrate(date_start, date_end, long_entry, long_exit, take_profit_percentage, stop_loss_percentage, atr_length, initial_capital, order_size, commission)
Start Date
You can set the start date either by using a timestamp or a number that refers to the number of bars back.
Stop Loss / Take Profit Issue
Unfortunately, I did not manage to achieve 100% accuracy for the take profit and stop loss. The original TradingView backtest can stop at the correct position within a bar using the strategy.exit stop and limit variables. However, it seems unachievable with a crossunder/crossover function in PineScript unless it is calculated on every tick (which would make the backtesting results invalid). So far, I have not found a workaround, and I would be grateful if someone could solve this issue, if it is even possible. If you have any solutions or fixes, please let me know!
Multiple Backtest Results / Optimizer
You can run multiple backtests in a single strategy or indicator, but there are certain requirements for placing the correct code in the right way. To view examples of running multiple backtests, you can refer to the links provided in the updates I posted below. In the samples I have also explained how you can auto-generate code for your backtest strategy.
Pineconnector Strategy Template (Connect Any Indicator)Hello traders,
If you're tired of manual trading and looking for a solid strategy template to pair with your indicators, look no further.
This Pine Script v5 strategy template is engineered for maximum customization and risk management.
Best part?
It’s optimized for Pineconnector, allowing seamless integration with MetaTrader 4 and 5.
This powerful tool gives a lot of power to those who don't know how to code in Pinescript and are looking to automate their indicators' signals on Metatrader 4/5.
IMPORTANT NOTES
Pineconnector is a trading bot software that forwards TradingView alerts to your Metatrader 4/5 for automating trading.
Many traders don't know how to dynamically create Pineconnector-compatible alerts using the data from their TradingView scripts.
Traders using trading bots want their alerts to reflect the stop-loss/take-profit/trailing-stop/stop-loss to break options from your script and then create the orders accordingly.
This script showcases how to create Pineconnector alerts dynamically.
Pineconnector doesn't support alerts with multiple Take Profits.
As a workaround, for 2 TPs, I had to open two trades.
It's not optimal, as we end up paying more spreads for that extra trade - however, depending on your trading strategy, it may not be a big deal.
TRADINGVIEW ALERTS
1) You'll have to create one alert per asset X timeframe = 1 chart.
Example: 1 alert for EUR/USD on the 5 minutes chart, 1 alert for EUR/USD on the 15-minute chart (assuming you want your bot to trade the EUR/USD on the 5 and 15-minute timeframes)
2) Select the Order fills and alert() function calls condition
3) For each alert, the alert message is pre-configured with the text below
{{strategy.order.alert_message}}
Please leave it as it is.
It's a TradingView native variable that will fetch the alert text messages built by the script.
4) Don't forget to set the Pineconnector webhook URL in the Notifications tab of the TradingView alerts UI.
You’ll find the URL on the Pineconnector documentation website.
EA CONFIGURATION
1) The Pyramiding in the EA on Metatrader must be set to 2 if you want to trade with 2 TPs => as it's opening 2 trades.
If you only want 1 TP, set the EA Pyramiding to 1.
Regarding the other EA settings, please refer to the Pineconnector documentation on their website.
2) In the EA, you can set a risk (= position size type) in %/lots/USD, as in the TradingView backtest settings.
KEY FEATURES
I) Modular Indicator Connection
* plug in your existing indicator into the template.
* Only two lines of code are needed for full compatibility.
Step 1: Create your connector
Adapt your indicator with only 2 lines of code and then connect it to this strategy template.
To do so:
1) Find in your indicator where the conditions print the long/buy and short/sell signals.
2) Create an additional plot as below
I'm giving an example with a Two moving averages cross.
Please replicate the same methodology for your indicator, whether it's a MACD , ZigZag , Pivots , higher-highs, lower-lows, or whatever indicator with clear buy and sell conditions.
//@version=5
indicator("Supertrend", overlay = true, timeframe = "", timeframe_gaps = true)
atrPeriod = input.int(10, "ATR Length", minval = 1)
factor = input.float(3.0, "Factor", minval = 0.01, step = 0.01)
= ta.supertrend(factor, atrPeriod)
supertrend := barstate.isfirst ? na : supertrend
bodyMiddle = plot(barstate.isfirst ? na : (open + close) / 2, display = display.none)
upTrend = plot(direction < 0 ? supertrend : na, "Up Trend", color = color.green, style = plot.style_linebr)
downTrend = plot(direction < 0 ? na : supertrend, "Down Trend", color = color.red, style = plot.style_linebr)
fill(bodyMiddle, upTrend, color.new(color.green, 90), fillgaps = false)
fill(bodyMiddle, downTrend, color.new(color.red, 90), fillgaps = false)
buy = ta.crossunder(direction, 0)
sell = ta.crossunder(direction, 0)
//////// CONNECTOR SECTION ////////
Signal = buy ? 1 : sell ? -1 : 0
plot(Signal, title = "Signal", display = display.data_window)
//////// CONNECTOR SECTION ////////
Important Notes
🔥 The Strategy Template expects the value to be exactly 1 for the bullish signal and -1 for the bearish signal
Now, you can connect your indicator to the Strategy Template using the method below or that one.
Step 2: Connect the connector
1) Add your updated indicator to a TradingView chart
2) Add the Strategy Template as well to the SAME chart
3) Open the Strategy Template settings, and in the Data Source field, select your 🔌Connector🔌 (which comes from your indicator)
Note it doesn’t have to be named 🔌Connector🔌 - you can name it as you want - however, I recommend an explicit name you can easily remember.
From then, you should start seeing the signals and plenty of other stuff on your chart.
🔥 Note that whenever you update your indicator values, the strategy statistics and visuals on your chart will update in real-time
II) Customizable Risk Management
- Choose between percentage or USD modes for maximum drawdown.
- Set max consecutive losing days and max losing streak length.
- I used the code from my friend @JosKodify for the maximum losing streak. :)
Will halt the EA and backtest orders fill whenever either of the safeguards above are “broken”
III) Intraday Risk Management
- Limit the maximum intraday losses both in percentage or USD.
- Option to set a maximum number of intraday trades.
- If your EA gets halted on an intraday chart, auto-restart it the next day.
IV) Spread and Account Filters
- Trade only if the spread is below a certain pip value.
- Set requirements based on account balance or equity.
V) Order Types and Position Sizing
- Choose between market, limit, or stop orders.
- Set your position size directly in the template.
Please use the position size from the “Inputs” and not the “Properties” tab.
Reason : The template sends the order on the same candle as the entry signals - at those entry signals candles, the position size isn’t computed yet, and the template can’t then send it to Pineconnector.
However, you can use the position size type (USD, contracts, %) from the “Properties” tab for backtesting.
In the EA, you can define the position size type for your orders in USD or lots or %.
VI) Advanced Take-Profit and Stop-Loss Options
- Choose to set your SL/TP in either pips or percentages.
- Option for multiple take-profit levels and trailing stop losses.
- Move your stop loss to break even +/- offset in pips for “risk-free” trades.
VII) Logger
The Pineconnector commands are logged in the TradingView logger.
You'll find more information about it in this TradingView blog post .
WHY YOU MIGHT NEED THIS TEMPLATE
1) Transform your indicator into a Pineconnector trading bot more easily than before
Connect your indicator to the template
Create your alerts
Set your EA settings
2) Save Time
Auto-generated alert messages for Pineconnector.
I tested them all, and I checked with the support team what could/can’t be done
3) Be in Control
Manage your trading risks with advanced features.
4) Customizable
Fits various trading styles and asset classes.
REQUIREMENTS
* Make sure you have your Pineconnector license ID.
* Create your alerts with the Pineconnector webhook URL
* If there is any issue with the template, ask me in the comments section - I’ll answer quickly.
BACKTEST RESULTS FROM THIS POST
1) I connected this strategy template to a dummy Supertrend script.
I could have selected any other indicator or concept for this script post.
I wanted to share an example of how you can quickly upgrade your strategy, making it compatible with Pineconnector.
2) The backtest results aren't relevant for this educational script publication.
I used realistic backtesting data but didn't look too much into optimizing the results, as this isn't the point of why I'm publishing this script.
This strategy is a template to be connected to any indicator - the sky is the limit. :)
3) This template is made to take 1 trade per direction at any given time.
Pyramiding is set to 1 on TradingView.
The strategy default settings are:
* Initial Capital: 100000 USD
* Position Size: 1 contract
* Commission Percent: 0.075%
* Slippage: 1 tick
* No margin/leverage used
WHAT’S COMING NEXT FOR YOU GUYS?
I’ll make the same template for ProfitView, then for AutoView, and then for Alertatron.
All of those are free and open-source.
I have no affiliations with any of those companies - I'm publishing those templates as they will be useful to many of you.
Dave
EMA Envelope - Signal with Stoploss and Takeprofit LevelsDescription:
This Pine Script indicator implements the EMA Envelope strategy, which utilizes Exponential Moving Averages (EMA) to create an envelope around the price chart. The strategy generates buy and sell signals based on the crossing of the price above and below the upper and lower EMA envelopes, respectively. It also incorporates additional features such as stop-loss and take-profit levels for risk management.
Indicator Settings:
EMA Length: Specifies the period for the short-term Exponential Moving Average.
Long Term EMA Length: Defines the period for the long-term Exponential Moving Average used for signal filtering.
Take Profit Ratio: Determines the ratio for calculating the take-profit levels based on the stop-loss.
Filter Signal on Long Term EMA: Enables or disables the filtering of buy/sell signals using the long-term EMA.
Show only recent signal: When enabled, shows only the most recent buy/sell signals.
Buy and Sell Signals:
The indicator generates buy signals when the price crosses above the upper EMA envelope and the previous low was below the upper EMA envelope. Additionally, you can choose to filter buy signals based on whether the closing price is above the long-term EMA.
Conversely, sell signals are generated when the price crosses below the lower EMA envelope, and the previous high was above the lower EMA envelope. Similar to buy signals, sell signals can also be filtered using the long-term EMA.
Note: Signal works well on Higher Timeframes like Daily/8hrs/4hrs/1hr.
Stop-Loss and Take-Profit Levels:
For buy signals, the stop-loss is set at the lower EMA level, while the take-profit level is calculated by adding a specified ratio of the difference between the low and the stop-loss level to the low price.
For sell signals, the stop-loss is set at the upper EMA level, and the take-profit level is calculated by subtracting a specified ratio of the difference between the stop-loss level and the high price from the high price.
Disclaimer:
This indicator is provided for educational and informational purposes only. Trading involves significant risk, and past performance does not guarantee future results. Users are solely responsible for their trading decisions and should conduct their own research and risk management. The author shall not be held liable for any losses or damages arising from the use of this indicator.
Note: Always test the indicator thoroughly on historical data and consider paper trading before applying it to live trading environments.
Moving Average Rainbow (Stormer)This strategy is based and shown by trader and investor Alexandre Wolwacz "Stormer".
Overview
The strategy uses 12 moving averages (default EMA) to identify trends and generate trading signals opening positions.
Allowing to select the type of moving average and length to be used.
The conditions includes relationship between moving averages, the position of the current price relative to the moving averages, and the occurrence of certain price patterns.
Calculation
The mean moving averages is calculated by adding all the 12 moving averages and dividing by 12, the value is used to help to identify trend and possible condition to open position.
The 12 moving averages is spliced by 3 ranges, initial range (moving average lines 1 to 4), middle range (moving average lines 5 to 8) and end range (moving average lines 9 to 12). These ranges helps to identify potential trend and market turn over.
The moving average touch price is a relationship between the low price (uptrend) or high price (downtrend) with the moving average lines, it identifies where the price (low/high) has reached the the moving average line. Fetching the value to help for opening position, set stop loss and take profit.
Since the stop loss is based and set from the previous moving average touch price value, when position is about to be open and setting the stop loss value, there is a verification to check both current and previous moving average touch price to recalculate the stop loss value.
The turnover trend checks for a possible market turnover event, setting up a new profit target, this setting when enabled is to be helpful when a turnover occurs against the position to exit position with some profit based on highest high price if long or lowest low price if short.
The turnover signal is similar to turnover trend. The difference is that when this setting is enabled and it triggers, it simply exit the current position and opens up a reverse position, long goes short and short goes long. And there is an complement optional that checks current price exit profitable.
Entry Position
Long Position:
Price is higher than the mean moving averages. Meaning possible uptrend.
The lines of the middle range from the moving averages are in increasing order. Meaning possible uptrend.
The current high pierced up previous high.
Fetch the previous value of the moving average touch price. Meaning the low price has touched one of the moving average lines, which that value is conditioning to open position.
Short Position:
Price is lower than the mean moving averages. Meaning possible downtrend.
The lines of the middle range from the moving averages are in decreasing order. Meaning possible downtrend.
The current low pierced down previous low.
Fetch the previous value of the moving average touch price. Meaning the high price has touched one of the moving average lines, which that value is conditioning to open position.
Risk Management
Stop Loss:
The stop loss is based from the previous moving average touch price value, high price for short and low price for long or occurs an verification to check for both current and previous moving average touch price value and a recalculation is done to set the stop loss.
Take Profit:
According to the author, the profit target should be at least 1:1.6 the risk, so to have the strategy mathematically positive.
The profit target is configured input, can be increased or decreased.
It calculates the take profit based on the price of the stop loss with the profit target input.
Turnover Trend
Long Position:
The moving averages initial range lines signals a possible market turnover. Meaning long might be going short.
Fetches the highest high hit since the opening of the position, setting that value to the new profit target.
Short Position:
The moving averages initial range lines signals a possible market turnover. Meaning short might be going long.
Fetches the lowest low hit since the opening of the position, setting that value to the new profit target.
GKD-M Baseline Optimizer [Loxx]Giga Kaleidoscope GKD-M Baseline Optimizer is a Metamorphosis module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
The Baseline Optimizer enables traders to backtest over 60 moving averages using variable period inputs. It then exports the baseline with the highest cumulative win rate per candle to any baseline-enabled GKD backtest. To perform the backtesting, the trader selects an initial period input (default is 60) and a skip value that increments the initial period input up to seven times. For instance, if a skip value of 5 is chosen, the Baseline Optimizer will run the backtest for the selected moving average on periods such as 60, 65, 70, 75, and so on, up to 90. If the user selects an initial period input of 45 and a skip value of 2, the Baseline Optimizer will conduct backtests for the chosen moving average on periods like 45, 47, 49, 51, and so forth, up to 57.
The Baseline Optimizer provides a table displaying the output of the backtests for a specified date range. The table output represents the cumulative win rate for the given date range.
On the Metamorphosis side of the Baseline Optimizer, a cumulative backtest is calculated for each candle within the date range. This means that each candle may exhibit a different distribution of period inputs with the highest win rate for a particular moving average. The Baseline Optimizer identifies the period input combination with the highest win rates for long and short positions and creates a win-rate adaptive long and short moving average chart. The moving average used for shorts differs from the moving average used for longs, and the moving average for each candle may vary from any other candle. This customized baseline can then be exported to all baseline-enabled GKD backtests.
The backtest employed in the Baseline Optimizer is a Solo Confirmation Simple, allowing only one take profit and one stop loss to be set.
Lastly, the Baseline Optimizer incorporates Goldie Locks Zone filtering, which can be utilized for signal generation in advanced GKD backtests.
█ Moving Averages included in the Baseline Optimizer
Adaptive Moving Average - AMA
ADXvma - Average Directional Volatility Moving Average
Ahrens Moving Average
Alexander Moving Average - ALXMA
Deviation Scaled Moving Average - DSMA
Donchian
Double Exponential Moving Average - DEMA
Double Smoothed Exponential Moving Average - DSEMA
Double Smoothed FEMA - DSFEMA
Double Smoothed Range Weighted EMA - DSRWEMA
Double Smoothed Wilders EMA - DSWEMA
Double Weighted Moving Average - DWMA
Exponential Moving Average - EMA
Fast Exponential Moving Average - FEMA
Fractal Adaptive Moving Average - FRAMA
Generalized DEMA - GDEMA
Generalized Double DEMA - GDDEMA
Hull Moving Average (Type 1) - HMA1
Hull Moving Average (Type 2) - HMA2
Hull Moving Average (Type 3) - HMA3
Hull Moving Average (Type 4) - HMA4
IE /2 - Early T3 by Tim Tilson
Integral of Linear Regression Slope - ILRS
Kaufman Adaptive Moving Average - KAMA
Leader Exponential Moving Average
Linear Regression Value - LSMA ( Least Squares Moving Average )
Linear Weighted Moving Average - LWMA
McGinley Dynamic
McNicholl EMA
Non-Lag Moving Average
Ocean NMA Moving Average - ONMAMA
One More Moving Average - OMA
Parabolic Weighted Moving Average
Probability Density Function Moving Average - PDFMA
Quadratic Regression Moving Average - QRMA
Regularized EMA - REMA
Range Weighted EMA - RWEMA
Recursive Moving Trendline
Simple Decycler - SDEC
Simple Jurik Moving Average - SJMA
Simple Moving Average - SMA
Sine Weighted Moving Average
Smoothed LWMA - SLWMA
Smoothed Moving Average - SMMA
Smoother
Super Smoother
T3
Three-pole Ehlers Butterworth
Three-pole Ehlers Smoother
Triangular Moving Average - TMA
Triple Exponential Moving Average - TEMA
Two-pole Ehlers Butterworth
Two-pole Ehlers smoother
Variable Index Dynamic Average - VIDYA
Variable Moving Average - VMA
Volume Weighted EMA - VEMA
Volume Weighted Moving Average - VWMA
Zero-Lag DEMA - Zero Lag Exponential Moving Average
Zero-Lag Moving Average
Zero Lag TEMA - Zero Lag Triple Exponential Moving Average
Adaptive Moving Average - AMA
The Adaptive Moving Average (AMA) is a moving average that changes its sensitivity to price moves depending on the calculated volatility. It becomes more sensitive during periods when the price is moving smoothly in a certain direction and becomes less sensitive when the price is volatile.
ADXvma - Average Directional Volatility Moving Average
Linnsoft's ADXvma formula is a volatility-based moving average, with the volatility being determined by the value of the ADX indicator.
The ADXvma has the SMA in Chande's CMO replaced with an EMA , it then uses a few more layers of EMA smoothing before the "Volatility Index" is calculated.
A side effect is, those additional layers slow down the ADXvma when you compare it to Chande's Variable Index Dynamic Average VIDYA .
The ADXVMA provides support during uptrends and resistance during downtrends and will stay flat for longer, but will create some of the most accurate market signals when it decides to move.
Ahrens Moving Average
Richard D. Ahrens's Moving Average promises "Smoother Data" that isn't influenced by the occasional price spike. It works by using the Open and the Close in his formula so that the only time the Ahrens Moving Average will change is when the candlestick is either making new highs or new lows.
Alexander Moving Average - ALXMA
This Moving Average uses an elaborate smoothing formula and utilizes a 7 period Moving Average. It corresponds to fitting a second-order polynomial to seven consecutive observations. This moving average is rarely used in trading but is interesting as this Moving Average has been applied to diffusion indexes that tend to be very volatile.
Deviation Scaled Moving Average - DSMA
The Deviation-Scaled Moving Average is a data smoothing technique that acts like an exponential moving average with a dynamic smoothing coefficient. The smoothing coefficient is automatically updated based on the magnitude of price changes. In the Deviation-Scaled Moving Average, the standard deviation from the mean is chosen to be the measure of this magnitude. The resulting indicator provides substantial smoothing of the data even when price changes are small while quickly adapting to these changes.
Donchian
Donchian Channels are three lines generated by moving average calculations that comprise an indicator formed by upper and lower bands around a midrange or median band. The upper band marks the highest price of a security over N periods while the lower band marks the lowest price of a security over N periods.
Double Exponential Moving Average - DEMA
The Double Exponential Moving Average ( DEMA ) combines a smoothed EMA and a single EMA to provide a low-lag indicator. It's primary purpose is to reduce the amount of "lagging entry" opportunities, and like all Moving Averages, the DEMA confirms uptrends whenever price crosses on top of it and closes above it, and confirms downtrends when the price crosses under it and closes below it - but with significantly less lag.
Double Smoothed Exponential Moving Average - DSEMA
The Double Smoothed Exponential Moving Average is a lot less laggy compared to a traditional EMA . It's also considered a leading indicator compared to the EMA , and is best utilized whenever smoothness and speed of reaction to market changes are required.
Double Smoothed FEMA - DSFEMA
Same as the Double Exponential Moving Average (DEMA), but uses a faster version of EMA for its calculation.
Double Smoothed Range Weighted EMA - DSRWEMA
Range weighted exponential moving average (EMA) is, unlike the "regular" range weighted average calculated in a different way. Even though the basis - the range weighting - is the same, the way how it is calculated is completely different. By definition this type of EMA is calculated as a ratio of EMA of price*weight / EMA of weight. And the results are very different and the two should be considered as completely different types of averages. The higher than EMA to price changes responsiveness when the ranges increase remains in this EMA too and in those cases this EMA is clearly leading the "regular" EMA. This version includes double smoothing.
Double Smoothed Wilders EMA - DSWEMA
Welles Wilder was frequently using one "special" case of EMA (Exponential Moving Average) that is due to that fact (that he used it) sometimes called Wilder's EMA. This version is adding double smoothing to Wilder's EMA in order to make it "faster" (it is more responsive to market prices than the original) and is still keeping very smooth values.
Double Weighted Moving Average - DWMA
Double weighted moving average is an LWMA (Linear Weighted Moving Average). Instead of doing one cycle for calculating the LWMA, the indicator is made to cycle the loop 2 times. That produces a smoother values than the original LWMA
Exponential Moving Average - EMA
The EMA places more significance on recent data points and moves closer to price than the SMA ( Simple Moving Average ). It reacts faster to volatility due to its emphasis on recent data and is known for its ability to give greater weight to recent and more relevant data. The EMA is therefore seen as an enhancement over the SMA .
Fast Exponential Moving Average - FEMA
An Exponential Moving Average with a short look-back period.
Fractal Adaptive Moving Average - FRAMA
The Fractal Adaptive Moving Average by John Ehlers is an intelligent adaptive Moving Average which takes the importance of price changes into account and follows price closely enough to display significant moves whilst remaining flat if price ranges. The FRAMA does this by dynamically adjusting the look-back period based on the market's fractal geometry.
Generalized DEMA - GDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages.". Instead of using fixed multiplication factor in the final DEMA formula, the generalized version allows you to change it. By varying the "volume factor" form 0 to 1 you apply different multiplications and thus producing DEMA with different "speed" - the higher the volume factor is the "faster" the DEMA will be (but also the slope of it will be less smooth). The volume factor is limited in the calculation to 1 since any volume factor that is larger than 1 is increasing the overshooting to the extent that some volume factors usage makes the indicator unusable.
Generalized Double DEMA - GDDEMA
The double exponential moving average (DEMA), was developed by Patrick Mulloy in an attempt to reduce the amount of lag time found in traditional moving averages. It was first introduced in the February 1994 issue of the magazine Technical Analysis of Stocks & Commodities in Mulloy's article "Smoothing Data with Faster Moving Averages''. This is an extension of the Generalized DEMA using Tim Tillsons (the inventor of T3) idea, and is using GDEMA of GDEMA for calculation (which is the "middle step" of T3 calculation). Since there are no versions showing that middle step, this version covers that too. The result is smoother than Generalized DEMA, but is less smooth than T3 - one has to do some experimenting in order to find the optimal way to use it, but in any case, since it is "faster" than the T3 (Tim Tillson T3) and still smooth, it looks like a good compromise between speed and smoothness.
Hull Moving Average (Type 1) - HMA1
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMA for smoothing.
Hull Moving Average (Type 2) - HMA2
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses EMA for smoothing.
Hull Moving Average (Type 3) - HMA3
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses LWMA for smoothing.
Hull Moving Average (Type 4) - HMA4
Alan Hull's HMA makes use of weighted moving averages to prioritize recent values and greatly reduce lag whilst maintaining the smoothness of a traditional Moving Average. For this reason, it's seen as a well-suited Moving Average for identifying entry points. This version uses SMMA for smoothing.
IE /2 - Early T3 by Tim Tilson and T3 new
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
Integral of Linear Regression Slope - ILRS
A Moving Average where the slope of a linear regression line is simply integrated as it is fitted in a moving window of length N (natural numbers in maths) across the data. The derivative of ILRS is the linear regression slope. ILRS is not the same as a SMA ( Simple Moving Average ) of length N, which is actually the midpoint of the linear regression line as it moves across the data.
Kaufman Adaptive Moving Average - KAMA
Developed by Perry Kaufman, Kaufman's Adaptive Moving Average (KAMA) is a moving average designed to account for market noise or volatility. KAMA will closely follow prices when the price swings are relatively small and the noise is low.
Leader Exponential Moving Average
The Leader EMA was created by Giorgos E. Siligardos who created a Moving Average which was able to eliminate lag altogether whilst maintaining some smoothness. It was first described during his research paper "MACD Leader" where he applied this to the MACD to improve its signals and remove its lagging issue. This filter uses his leading MACD's "modified EMA" and can be used as a zero lag filter.
Linear Regression Value - LSMA ( Least Squares Moving Average )
LSMA as a Moving Average is based on plotting the end point of the linear regression line. It compares the current value to the prior value and a determination is made of a possible trend, eg. the linear regression line is pointing up or down.
Linear Weighted Moving Average - LWMA
LWMA reacts to price quicker than the SMA and EMA . Although it's similar to the Simple Moving Average , the difference is that a weight coefficient is multiplied to the price which means the most recent price has the highest weighting, and each prior price has progressively less weight. The weights drop in a linear fashion.
McGinley Dynamic
John McGinley created this Moving Average to track prices better than traditional Moving Averages. It does this by incorporating an automatic adjustment factor into its formula, which speeds (or slows) the indicator in trending, or ranging, markets.
McNicholl EMA
Dennis McNicholl developed this Moving Average to use as his center line for his "Better Bollinger Bands" indicator and was successful because it responded better to volatility changes over the standard SMA and managed to avoid common whipsaws.
Non-lag moving average
The Non Lag Moving average follows price closely and gives very quick signals as well as early signals of price change. As a standalone Moving Average, it should not be used on its own, but as an additional confluence tool for early signals.
Ocean NMA Moving Average - ONMAMA
Created by Jim Sloman, the NMA is a moving average that automatically adjusts to volatility without being programmed to do so. For more info, read his guide "Ocean Theory, an Introduction"
One More Moving Average (OMA)
The One More Moving Average (OMA) is a technical indicator that calculates a series of Jurik-style moving averages in order to reduce noise and provide smoother price data. It uses six exponential moving averages to generate the final value, with the length of the moving averages determined by an adaptive algorithm that adjusts to the current market conditions. The algorithm calculates the average period by comparing the signal to noise ratio and using this value to determine the length of the moving averages. The resulting values are used to generate the final value of the OMA, which can be used to identify trends and potential changes in trend direction.
Parabolic Weighted Moving Average
The Parabolic Weighted Moving Average is a variation of the Linear Weighted Moving Average . The Linear Weighted Moving Average calculates the average by assigning different weights to each element in its calculation. The Parabolic Weighted Moving Average is a variation that allows weights to be changed to form a parabolic curve. It is done simply by using the Power parameter of this indicator.
Probability Density Function Moving Average - PDFMA
Probability density function based MA is a sort of weighted moving average that uses probability density function to calculate the weights. By its nature it is similar to a lot of digital filters.
Quadratic Regression Moving Average - QRMA
A quadratic regression is the process of finding the equation of the parabola that best fits a set of data. This moving average is an obscure concept that was posted to Forex forums in around 2008.
Regularized EMA - REMA
The regularized exponential moving average (REMA) by Chris Satchwell is a variation on the EMA (see Exponential Moving Average) designed to be smoother but not introduce too much extra lag.
Range Weighted EMA - RWEMA
This indicator is a variation of the range weighted EMA. The variation comes from a possible need to make that indicator a bit less "noisy" when it comes to slope changes. The method used for calculating this variation is the method described by Lee Leibfarth in his article "Trading With An Adaptive Price Zone".
Recursive Moving Trendline
Dennis Meyers's Recursive Moving Trendline uses a recursive (repeated application of a rule) polynomial fit, a technique that uses a small number of past values estimations of price and today's price to predict tomorrow's price.
Simple Decycler - SDEC
The Ehlers Simple Decycler study is a virtually zero-lag technical indicator proposed by John F. Ehlers. The original idea behind this study (and several others created by John F. Ehlers) is that market data can be considered a continuum of cycle periods with different cycle amplitudes. Thus, trending periods can be considered segments of longer cycles, or, in other words, low-frequency segments. Applying the right filter might help identify these segments.
Simple Loxx Moving Average - SLMA
A three stage moving average combining an adaptive EMA, a Kalman Filter, and a Kauffman adaptive filter.
Simple Moving Average - SMA
The SMA calculates the average of a range of prices by adding recent prices and then dividing that figure by the number of time periods in the calculation average. It is the most basic Moving Average which is seen as a reliable tool for starting off with Moving Average studies. As reliable as it may be, the basic moving average will work better when it's enhanced into an EMA .
Sine Weighted Moving Average
The Sine Weighted Moving Average assigns the most weight at the middle of the data set. It does this by weighting from the first half of a Sine Wave Cycle and the most weighting is given to the data in the middle of that data set. The Sine WMA closely resembles the TMA (Triangular Moving Average).
Smoothed LWMA - SLWMA
A smoothed version of the LWMA
Smoothed Moving Average - SMMA
The Smoothed Moving Average is similar to the Simple Moving Average ( SMA ), but aims to reduce noise rather than reduce lag. SMMA takes all prices into account and uses a long lookback period. Due to this, it's seen as an accurate yet laggy Moving Average.
Smoother
The Smoother filter is a faster-reacting smoothing technique which generates considerably less lag than the SMMA ( Smoothed Moving Average ). It gives earlier signals but can also create false signals due to its earlier reactions. This filter is sometimes wrongly mistaken for the superior Jurik Smoothing algorithm.
Super Smoother
The Super Smoother filter uses John Ehlers’s “Super Smoother” which consists of a Two pole Butterworth filter combined with a 2-bar SMA ( Simple Moving Average ) that suppresses the 22050 Hz Nyquist frequency: A characteristic of a sampler, which converts a continuous function or signal into a discrete sequence.
Three-pole Ehlers Butterworth
The 3 pole Ehlers Butterworth (as well as the Two pole Butterworth) are both superior alternatives to the EMA and SMA . They aim at producing less lag whilst maintaining accuracy. The 2 pole filter will give you a better approximation for price, whereas the 3 pole filter has superior smoothing.
Three-pole Ehlers smoother
The 3 pole Ehlers smoother works almost as close to price as the above mentioned 3 Pole Ehlers Butterworth. It acts as a strong baseline for signals but removes some noise. Side by side, it hardly differs from the Three Pole Ehlers Butterworth but when examined closely, it has better overshoot reduction compared to the 3 pole Ehlers Butterworth.
Triangular Moving Average - TMA
The TMA is similar to the EMA but uses a different weighting scheme. Exponential and weighted Moving Averages will assign weight to the most recent price data. Simple moving averages will assign the weight equally across all the price data. With a TMA (Triangular Moving Average), it is double smoother (averaged twice) so the majority of the weight is assigned to the middle portion of the data.
Triple Exponential Moving Average - TEMA
The TEMA uses multiple EMA calculations as well as subtracting lag to create a tool which can be used for scalping pullbacks. As it follows price closely, its signals are considered very noisy and should only be used in extremely fast-paced trading conditions.
Two-pole Ehlers Butterworth
The 2 pole Ehlers Butterworth (as well as the three pole Butterworth mentioned above) is another filter that cuts out the noise and follows the price closely. The 2 pole is seen as a faster, leading filter over the 3 pole and follows price a bit more closely. Analysts will utilize both a 2 pole and a 3 pole Butterworth on the same chart using the same period, but having both on chart allows its crosses to be traded.
Two-pole Ehlers smoother
A smoother version of the Two pole Ehlers Butterworth. This filter is the faster version out of the 3 pole Ehlers Butterworth. It does a decent job at cutting out market noise whilst emphasizing a closer following to price over the 3 pole Ehlers .
Variable Index Dynamic Average - VIDYA
Variable Index Dynamic Average Technical Indicator ( VIDYA ) was developed by Tushar Chande. It is an original method of calculating the Exponential Moving Average ( EMA ) with the dynamically changing period of averaging.
Variable Moving Average - VMA
The Variable Moving Average (VMA) is a study that uses an Exponential Moving Average being able to automatically adjust its smoothing factor according to the market volatility.
Volume Weighted EMA - VEMA
An EMA that uses a volume and price weighted calculation instead of the standard price input.
Volume Weighted Moving Average - VWMA
A Volume Weighted Moving Average is a moving average where more weight is given to bars with heavy volume than with light volume. Thus the value of the moving average will be closer to where most trading actually happened than it otherwise would be without being volume weighted.
Zero-Lag DEMA - Zero Lag Double Exponential Moving Average
John Ehlers's Zero Lag DEMA's aim is to eliminate the inherent lag associated with all trend following indicators which average a price over time. Because this is a Double Exponential Moving Average with Zero Lag, it has a tendency to overshoot and create a lot of false signals for swing trading. It can however be used for quick scalping or as a secondary indicator for confluence.
Zero-Lag Moving Average
The Zero Lag Moving Average is described by its creator, John Ehlers , as a Moving Average with absolutely no delay. And it's for this reason that this filter will cause a lot of abrupt signals which will not be ideal for medium to long-term traders. This filter is designed to follow price as close as possible whilst de-lagging data instead of basing it on regular data. The way this is done is by attempting to remove the cumulative effect of the Moving Average.
Zero-Lag TEMA - Zero Lag Triple Exponential Moving Average
Just like the Zero Lag DEMA , this filter will give you the fastest signals out of all the Zero Lag Moving Averages. This is useful for scalping but dangerous for medium to long-term traders, especially during market Volatility and news events. Having no lag, this filter also has no smoothing in its signals and can cause some very bizarre behavior when applied to certain indicators.
█ Volatility Goldie Locks Zone
The Goldie Locks Zone volatility filter is the standard first-pass filter used in all advanced GKD backtests (Complex, Super Complex, and Full GKd). This filter requires the price to fall within a range determined by multiples of volatility. The Goldie Locks Zone is separate from the core Baseline and utilizes its own moving average with Loxx's Exotic Source Types you can read about below.
On the chart, you will find green and red dots positioned at the top, indicating whether a candle qualifies for a long or short trade respectively. Additionally, green and red triangles are located at the bottom of the chart, signifying whether the trigger has crossed up or down and qualifies within the Goldie Locks zone. The Goldie Locks zone is represented by a white color on the mean line, indicating low volatility levels that are not suitable for trading.
█ Volatility Types Included in the Baseline Optimizer
The GKD system utilizes volatility-based take profits and stop losses. Each take profit and stop loss is calculated as a multiple of volatility. Users can also adjust the multiplier values in the settings.
This module includes 17 types of volatility:
Close-to-Close
Parkinson
Garman-Klass
Rogers-Satchell
Yang-Zhang
Garman-Klass-Yang-Zhang
Exponential Weighted Moving Average
Standard Deviation of Log Returns
Pseudo GARCH(2,2)
Average True Range
True Range Double
Standard Deviation
Adaptive Deviation
Median Absolute Deviation
Efficiency-Ratio Adaptive ATR
Mean Absolute Deviation
Static Percent
Various volatility estimators and indicators that investors and traders can use to measure the dispersion or volatility of a financial instrument's price. Each estimator has its strengths and weaknesses, and the choice of estimator should depend on the specific needs and circumstances of the user.
Close-to-Close
Close-to-Close volatility is a classic and widely used volatility measure, sometimes referred to as historical volatility.
Volatility is an indicator of the speed of a stock price change. A stock with high volatility is one where the price changes rapidly and with a larger amplitude. The more volatile a stock is, the riskier it is.
Close-to-close historical volatility is calculated using only a stock's closing prices. It is the simplest volatility estimator. However, in many cases, it is not precise enough. Stock prices could jump significantly during a trading session and return to the opening value at the end. That means that a considerable amount of price information is not taken into account by close-to-close volatility.
Despite its drawbacks, Close-to-Close volatility is still useful in cases where the instrument doesn't have intraday prices. For example, mutual funds calculate their net asset values daily or weekly, and thus their prices are not suitable for more sophisticated volatility estimators.
Parkinson
Parkinson volatility is a volatility measure that uses the stock’s high and low price of the day.
The main difference between regular volatility and Parkinson volatility is that the latter uses high and low prices for a day, rather than only the closing price. This is useful as close-to-close prices could show little difference while large price movements could have occurred during the day. Thus, Parkinson's volatility is considered more precise and requires less data for calculation than close-to-close volatility.
One drawback of this estimator is that it doesn't take into account price movements after the market closes. Hence, it systematically undervalues volatility. This drawback is addressed in the Garman-Klass volatility estimator.
Garman-Klass
Garman-Klass is a volatility estimator that incorporates open, low, high, and close prices of a security.
Garman-Klass volatility extends Parkinson's volatility by taking into account the opening and closing prices. As markets are most active during the opening and closing of a trading session, it makes volatility estimation more accurate.
Garman and Klass also assumed that the process of price change follows a continuous diffusion process (Geometric Brownian motion). However, this assumption has several drawbacks. The method is not robust for opening jumps in price and trend movements.
Despite its drawbacks, the Garman-Klass estimator is still more effective than the basic formula since it takes into account not only the price at the beginning and end of the time interval but also intraday price extremes.
Researchers Rogers and Satchell have proposed a more efficient method for assessing historical volatility that takes into account price trends. See Rogers-Satchell Volatility for more detail.
Rogers-Satchell
Rogers-Satchell is an estimator for measuring the volatility of securities with an average return not equal to zero.
Unlike Parkinson and Garman-Klass estimators, Rogers-Satchell incorporates a drift term (mean return not equal to zero). As a result, it provides better volatility estimation when the underlying is trending.
The main disadvantage of this method is that it does not take into account price movements between trading sessions. This leads to an underestimation of volatility since price jumps periodically occur in the market precisely at the moments between sessions.
A more comprehensive estimator that also considers the gaps between sessions was developed based on the Rogers-Satchel formula in the 2000s by Yang-Zhang. See Yang Zhang Volatility for more detail.
Yang-Zhang
Yang Zhang is a historical volatility estimator that handles both opening jumps and the drift and has a minimum estimation error.
Yang-Zhang volatility can be thought of as a combination of the overnight (close-to-open volatility) and a weighted average of the Rogers-Satchell volatility and the day’s open-to-close volatility. It is considered to be 14 times more efficient than the close-to-close estimator.
Garman-Klass-Yang-Zhang
Garman-Klass-Yang-Zhang (GKYZ) volatility estimator incorporates the returns of open, high, low, and closing prices in its calculation.
GKYZ volatility estimator takes into account overnight jumps but not the trend, i.e., it assumes that the underlying asset follows a Geometric Brownian Motion (GBM) process with zero drift. Therefore, the GKYZ volatility estimator tends to overestimate the volatility when the drift is different from zero. However, for a GBM process, this estimator is eight times more efficient than the close-to-close volatility estimator.
Exponential Weighted Moving Average
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, with the main applications being technical analysis and volatility modeling.
The moving average is designed such that older observations are given lower weights. The weights decrease exponentially as the data point gets older – hence the name exponentially weighted.
The only decision a user of the EWMA must make is the parameter lambda. The parameter decides how important the current observation is in the calculation of the EWMA. The higher the value of lambda, the more closely the EWMA tracks the original time series.
Standard Deviation of Log Returns
This is the simplest calculation of volatility. It's the standard deviation of ln(close/close(1)).
Pseudo GARCH(2,2)
This is calculated using a short- and long-run mean of variance multiplied by ?.
?avg(var;M) + (1 ? ?) avg(var;N) = 2?var/(M+1-(M-1)L) + 2(1-?)var/(M+1-(M-1)L)
Solving for ? can be done by minimizing the mean squared error of estimation; that is, regressing L^-1var - avg(var; N) against avg(var; M) - avg(var; N) and using the resulting beta estimate as ?.
Average True Range
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
The true range indicator is taken as the greatest of the following: current high less the current low; the absolute value of the current high less the previous close; and the absolute value of the current low less the previous close. The ATR is then a moving average, generally using 14 days, of the true ranges.
True Range Double
A special case of ATR that attempts to correct for volatility skew.
Standard Deviation
Standard deviation is a statistic that measures the dispersion of a dataset relative to its mean and is calculated as the square root of the variance. The standard deviation is calculated as the square root of variance by determining each data point's deviation relative to the mean. If the data points are further from the mean, there is a higher deviation within the data set; thus, the more spread out the data, the higher the standard deviation.
Adaptive Deviation
By definition, the Standard Deviation (STD, also represented by the Greek letter sigma ? or the Latin letter s) is a measure that is used to quantify the amount of variation or dispersion of a set of data values. In technical analysis, we usually use it to measure the level of current volatility.
Standard Deviation is based on Simple Moving Average calculation for mean value. This version of standard deviation uses the properties of EMA to calculate what can be called a new type of deviation, and since it is based on EMA, we can call it EMA deviation. Additionally, Perry Kaufman's efficiency ratio is used to make it adaptive (since all EMA type calculations are nearly perfect for adapting).
The difference when compared to the standard is significant--not just because of EMA usage, but the efficiency ratio makes it a "bit more logical" in very volatile market conditions.
Median Absolute Deviation
The median absolute deviation is a measure of statistical dispersion. Moreover, the MAD is a robust statistic, being more resilient to outliers in a data set than the standard deviation. In the standard deviation, the distances from the mean are squared, so large deviations are weighted more heavily, and thus outliers can heavily influence it. In the MAD, the deviations of a small number of outliers are irrelevant.
Because the MAD is a more robust estimator of scale than the sample variance or standard deviation, it works better with distributions without a mean or variance, such as the Cauchy distribution.
For this indicator, a manual recreation of the quantile function in Pine Script is used. This is so users have a full inside view into how this is calculated.
Efficiency-Ratio Adaptive ATR
Average True Range (ATR) is a widely used indicator for many occasions in technical analysis. It is calculated as the RMA of the true range. This version adds a "twist": it uses Perry Kaufman's Efficiency Ratio to calculate adaptive true range.
Mean Absolute Deviation
The mean absolute deviation (MAD) is a measure of variability that indicates the average distance between observations and their mean. MAD uses the original units of the data, which simplifies interpretation. Larger values signify that the data points spread out further from the average. Conversely, lower values correspond to data points bunching closer to it. The mean absolute deviation is also known as the mean deviation and average absolute deviation.
This definition of the mean absolute deviation sounds similar to the standard deviation (SD). While both measure variability, they have different calculations. In recent years, some proponents of MAD have suggested that it replace the SD as the primary measure because it is a simpler concept that better fits real life.
█ Loxx's Expanded Source Types Included in Baseline Optimizer
This indicator allows you to select from 33 source types. They are as follows:
Close
Open
High
Low
Median
Typical
Weighted
Average
Average Median Body
Trend Biased
Trend Biased (Extreme)
HA Close
HA Open
HA High
HA Low
HA Median
HA Typical
HA Weighted
HA Average
HA Average Median Body
HA Trend Biased
HA Trend Biased (Extreme)
HAB Close
HAB Open
HAB High
HAB Low
HAB Median
HAB Typical
HAB Weighted
HAB Average
HAB Average Median Body
HAB Trend Biased
HAB Trend Biased (Extreme)
What are Heiken Ashi "better" candles?
Heiken Ashi "better" candles are a modified version of the standard Heiken Ashi candles, which are a popular charting technique used in technical analysis. Heiken Ashi candles help traders identify trends and potential reversal points by smoothing out price data and reducing market noise. The "better formula" was proposed by Sebastian Schmidt in an article published by BNP Paribas in Warrants & Zertifikate, a German magazine, in August 2004. The aim of this formula is to further improve the smoothing of the Heiken Ashi chart and enhance its effectiveness in identifying trends and reversals.
Standard Heiken Ashi candles are calculated using the following formulas:
Heiken Ashi Close = (Open + High + Low + Close) / 4
Heiken Ashi Open = (Previous Heiken Ashi Open + Previous Heiken Ashi Close) / 2
Heiken Ashi High = Max (High, Heiken Ashi Open, Heiken Ashi Close)
Heiken Ashi Low = Min (Low, Heiken Ashi Open, Heiken Ashi Close)
The "better formula" modifies the standard Heiken Ashi calculation by incorporating additional smoothing, which can help reduce noise and make it easier to identify trends and reversals. The modified formulas for Heiken Ashi "better" candles are as follows:
Better Heiken Ashi Close = (Open + High + Low + Close) / 4
Better Heiken Ashi Open = (Previous Better Heiken Ashi Open + Previous Better Heiken Ashi Close) / 2
Better Heiken Ashi High = Max (High, Better Heiken Ashi Open, Better Heiken Ashi Close)
Better Heiken Ashi Low = Min (Low, Better Heiken Ashi Open, Better Heiken Ashi Close)
Smoothing Factor = 2 / (N + 1), where N is the chosen period for smoothing
Smoothed Better Heiken Ashi Open = (Better Heiken Ashi Open * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Open * (1 - Smoothing Factor))
Smoothed Better Heiken Ashi Close = (Better Heiken Ashi Close * Smoothing Factor) + (Previous Smoothed Better Heiken Ashi Close * (1 - Smoothing Factor))
The smoothed Better Heiken Ashi Open and Close values are then used to calculate the smoothed Better Heiken Ashi High and Low values, resulting in "better" candles that provide a clearer representation of the market trend and potential reversal points.
Heiken Ashi "better" candles, as mentioned previously, provide a clearer representation of market trends and potential reversal points by reducing noise and smoothing out price data. When using these candles in conjunction with other technical analysis tools and indicators, traders can gain valuable insights into market behavior and make more informed decisions.
To effectively use Heiken Ashi "better" candles in your trading strategy, consider the following tips:
-Trend Identification: Heiken Ashi "better" candles can help you identify the prevailing trend in the market. When the majority of the candles are green (or another color, depending on your chart settings) and there are no or few lower wicks, it may indicate a strong uptrend. Conversely, when the majority of the candles are red (or another color) and there are no or few upper wicks, it may signal a strong downtrend.
-Trend Reversals: Look for potential trend reversals when a change in the color of the candles occurs, especially when accompanied by longer wicks. For example, if a green candle with a long lower wick is followed by a red candle, it could indicate a bearish reversal. Similarly, a red candle with a long upper wick followed by a green candle may suggest a bullish reversal.
-Support and Resistance: You can use Heiken Ashi "better" candles to identify potential support and resistance levels. When the candles are consistently moving in one direction and then suddenly change color with longer wicks, it could indicate the presence of a support or resistance level.
-Stop-Loss and Take-Profit: Using Heiken Ashi "better" candles can help you manage risk by determining optimal stop-loss and take-profit levels. For instance, you can place your stop-loss below the low of the most recent green candle in an uptrend or above the high of the most recent red candle in a downtrend.
-Confirming Signals: Heiken Ashi "better" candles should be used in conjunction with other technical indicators, such as moving averages, oscillators, or chart patterns, to confirm signals and improve the accuracy of your analysis.
In this implementation, you have the choice of AMA, KAMA, or T3 smoothing. These are as follows:
Kaufman Adaptive Moving Average (KAMA)
The Kaufman Adaptive Moving Average (KAMA) is a type of adaptive moving average used in technical analysis to smooth out price fluctuations and identify trends. The KAMA adjusts its smoothing factor based on the market's volatility, making it more responsive in volatile markets and smoother in calm markets. The KAMA is calculated using three different efficiency ratios that determine the appropriate smoothing factor for the current market conditions. These ratios are based on the noise level of the market, the speed at which the market is moving, and the length of the moving average. The KAMA is a popular choice among traders who prefer to use adaptive indicators to identify trends and potential reversals.
Adaptive Moving Average
The Adaptive Moving Average (AMA) is a type of moving average that adjusts its sensitivity to price movements based on market conditions. It uses a ratio between the current price and the highest and lowest prices over a certain lookback period to determine its level of smoothing. The AMA can help reduce lag and increase responsiveness to changes in trend direction, making it useful for traders who want to follow trends while avoiding false signals. The AMA is calculated by multiplying a smoothing constant with the difference between the current price and the previous AMA value, then adding the result to the previous AMA value.
T3
The T3 moving average is a type of technical indicator used in financial analysis to identify trends in price movements. It is similar to the Exponential Moving Average (EMA) and the Double Exponential Moving Average (DEMA), but uses a different smoothing algorithm.
The T3 moving average is calculated using a series of exponential moving averages that are designed to filter out noise and smooth the data. The resulting smoothed data is then weighted with a non-linear function to produce a final output that is more responsive to changes in trend direction.
The T3 moving average can be customized by adjusting the length of the moving average, as well as the weighting function used to smooth the data. It is commonly used in conjunction with other technical indicators as part of a larger trading strategy.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
8. Metamorphosis - a technical indicator that produces a compound signal from the combination of other GKD indicators*
*(not part of the NNFX algorithm)
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
What is an Metamorphosis indicator?
The concept of a metamorphosis indicator involves the integration of two or more GKD indicators to generate a compound signal. This is achieved by evaluating the accuracy of each indicator and selecting the signal from the indicator with the highest accuracy. As an illustration, let's consider a scenario where we calculate the accuracy of 10 indicators and choose the signal from the indicator that demonstrates the highest accuracy.
The resulting output from the metamorphosis indicator can then be utilized in a GKD-BT backtest by occupying a slot that aligns with the purpose of the metamorphosis indicator. The slot can be a GKD-B, GKD-C, or GKD-E slot, depending on the specific requirements and objectives of the indicator. This allows for seamless integration and utilization of the compound signal within the GKD-BT framework.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
6. GKD-M - Metamorphosis module (Metamorphosis, Number 8 in the NNFX algorithm, but not part of the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal.
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Full GKD Backtest
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Kase Peak Oscillator
Confirmation 2: uf2018
Continuation: Vortex
Exit: Rex Oscillator
Metamorphosis: Baseline Optimizer as shown on the chart above
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, GKD-M, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
█ Giga Kaleidoscope Modularized Trading System Signals
Standard Entry
1. GKD-C Confirmation gives signal
2. Baseline agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
1-Candle Standard Entry
1a. GKD-C Confirmation gives signal
2a. Baseline agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Baseline Entry
1. GKD-B Basline gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
7. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
1-Candle Baseline Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Volatility/Volume Entry
1. GKD-V Volatility/Volume gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Volatility/Volume Entry
1a. GKD-V Volatility/Volume gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSVVC Bars Back' prior
Next Candle
1b. Price retraced
2b. Volatility/Volume agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Baseline agrees
Confirmation 2 Entry
1. GKD-C Confirmation 2 gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Volatility/Volume agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Confirmation 2 Entry
1a. GKD-C Confirmation 2 gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSC2C Bars Back' prior
Next Candle
1b. Price retraced
2b. Confirmation 2 agrees
3b. Confirmation 1 agrees
4b. Volatility/Volume agrees
5b. Baseline agrees
PullBack Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price is beyond 1.0x Volatility of Baseline
Next Candle
1b. Price inside Goldie Locks Zone Minimum
2b. Price inside Goldie Locks Zone Maximum
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Continuation Entry
1. Standard Entry, 1-Candle Standard Entry, Baseline Entry, 1-Candle Baseline Entry, Volatility/Volume Entry, 1-Candle Volatility/Volume Entry, Confirmation 2 Entry, 1-Candle Confirmation 2 Entry, or Pullback entry triggered previously
2. Baseline hasn't crossed since entry signal trigger
4. Confirmation 1 agrees
5. Baseline agrees
6. Confirmation 2 agrees
█ Connecting to Backtests
All GKD indicators are chained indicators meaning you export the value of the indicators to specialized backtest to creat your GKD trading system. Each indicator contains a proprietary signal generation algo that will only work with GKD backtests. You can find these backtests using the links below.
GKD-BT Giga Confirmation Stack Backtest:
GKD-BT Giga Stacks Backtest:
GKD-BT Full Giga Kaleidoscope Backtest:
GKD-BT Solo Confirmation Super Complex Backtest:
GKD-BT Solo Confirmation Complex Backtest:
GKD-BT Solo Confirmation Simple Backtest:
