Bullish Reversal Bar Strategy [Skyrexio]Overview
Bullish Reversal Bar Strategy leverages the combination of candlestick pattern Bullish Reversal Bar (description in Methodology and Justification of Methodology), Williams Alligator indicator and Williams Fractals to create the high probability setups. Candlestick pattern is used for the entering into trade, while the combination of Williams Alligator and Fractals is used for the trend approximation as close condition. Strategy uses only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator or the candlestick pattern invalidation to identify when current uptrend is likely to be over (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Trend Trade Filter: strategy uses Alligator and Fractal combination as high probability trend filter.
Methodology
The strategy opens long trade when the following price met the conditions:
1.Current candle's high shall be below the Williams Alligator's lines (Jaw, Lips, Teeth)(all details in "Justification of Methodology" paragraph)
2.Price shall create the candlestick pattern "Bullish Reversal Bar". Optionally if MFI and AO filters are enabled current candle shall have the decreasing AO and at least one of three recent bars shall have the squat state on the MFI (all details in "Justification of Methodology" paragraph)
3.If price breaks through the high of the candle marked as the "Bullish Reversal Bar" the long trade is open at the price one tick above the candle's high
4.Initial stop loss is placed at the Bullish Reversal Bar's candle's low
5.If price hit the Bullish Reversal Bar's low before hitting the entry price potential trade is cancelled
6.If trade is active and initial stop loss has not been hit, trade is closed when the combination of Alligator and Williams Fractals shall consider current trend change from upward to downward.
Strategy settings
In the inputs window user can setup strategy setting:
Enable MFI (if true trades are filtered using Market Facilitation Index (MFI) condition all details in "Justification of Methodology" paragraph), by default = false)
Enable AO (if true trades are filtered using Awesome Oscillator (AO) condition all details in "Justification of Methodology" paragraph), by default = false)
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. The first and key concept is the Bullish Reversal Bar candlestick pattern. This is just the single bar pattern. The rules are simple:
Candle shall be closed in it's upper half
High of this candle shall be below all three Alligator's lines (Jaw, Lips, Teeth)
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy.
How do these tools work together in this strategy? Let’s consider an example of an uptrend.
When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish.
The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals.
How we can use all these indicators in this strategy? This strategy is a counter trend one. Candle's high shall be below all Alligator's lines. During this market stage the bullish reversal bar candlestick pattern shall be printed. This bar during the downtrend is a high probability setup for the potential reversal to the upside: bulls were able to close the price in the upper half of a candle. The breaking of its high is a high probability signal that trend change is confirmed and script opens long trade. If market continues going down and break down the bullish reversal bar's low potential trend change has been invalidated and strategy close long trade.
If market really reversed and started moving to the upside strategy waits for the trend change form the downtrend to the uptrend according to approximation of Alligator and Fractals combination. If this change happens strategy close the trade. This approach helps to stay in the long trade while the uptrend continuation is likely and close it if there is a high probability of the uptrend finish.
Optionally users can enable MFI and AO filters. First of all, let's briefly explain what are these two indicators. The Awesome Oscillator (AO), created by Bill Williams, is a momentum-based indicator that evaluates market momentum by comparing recent price activity to a broader historical context. It assists traders in identifying potential trend reversals and gauging trend strength.
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
This indicator is filtering signals in the following way: if current AO bar is decreasing this candle can be interpreted as a bullish reversal bar. This logic is applicable because initially this strategy is a trend reversal, it is searching for the high probability setup against the current trend. Decreasing AO is the additional high probability filter of a downtrend.
Let's briefly look what is MFI. The Market Facilitation Index (MFI) is a technical indicator that measures the price movement per unit of volume, helping traders gauge the efficiency of price movement in relation to trading volume. Here's how you can calculate it:
MFI = (High−Low)/Volume
MFI can be used in combination with volume, so we can divide 4 states. Bill Williams introduced these to help traders interpret the interaction between volume and price movement. Here’s a quick summary:
Green Window (Increased MFI & Increased Volume): Indicates strong momentum with both price and volume increasing. Often a sign of trend continuation, as both buying and selling interest are rising.
Fake Window (Increased MFI & Decreased Volume): Shows that price is moving but with lower volume, suggesting weak support for the trend. This can signal a potential end of the current trend.
Squat Window (Decreased MFI & Increased Volume): Shows high volume but little price movement, indicating a tug-of-war between buyers and sellers. This often precedes a breakout as the pressure builds.
Fade Window (Decreased MFI & Decreased Volume): Indicates a lack of interest from both buyers and sellers, leading to lower momentum. This typically happens in range-bound markets and may signal consolidation before a new move.
For our purposes we are interested in squat bars. This is the sign that volume cannot move the price easily. This type of bar increases the probability of trend reversal. In this indicator we added to enable the MFI filter of reversal bars. If potential reversal bar or two preceding bars have squat state this bar can be interpret as a reversal one.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.12.31. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 50%
Maximum Single Position Loss: -5.29%
Maximum Single Profit: +29.99%
Net Profit: +5472.66 USDT (+54.73%)
Total Trades: 103 (33.98% win rate)
Profit Factor: 1.634
Maximum Accumulated Loss: 1231.15 USDT (-8.32%)
Average Profit per Trade: 53.13 USDT (+0.94%)
Average Trade Duration: 76 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h ETH/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
지표 및 전략
BITCOIN BTC Machine Learning Approximation Strategy by NHBPRODHey everyone, here's a new trading strategy script for Bitcoin, and I’m super excited to share it with you. It’s called the "BITCOIN BTC Machine Learning Approximation Strategy by NHBPROD." It employs a simplified machine learning technique referred to as K-means clustering approximation. It plots the mean price, upper cluster, and lower cluster, and prints a green and yellow background to visually cue you when to buy and when to sell. This is the strategy script, but I also have the indicator script which can be used to automate buy and sell signals directly to your phone, email, or your bot.
What It Does
The script calculates a dynamic mean price using linear regression and defines upper and lower zones based on standard deviation. These zones help identify potential support, resistance, or trend reversal areas on a chart. It visualizes the mean and clusters with plots and highlights significant areas where price moves above or below the clusters. Alerts are triggered when the price crosses these critical levels, enabling traders to stay informed about key market movements.
Backtest Results
Some notables:
Seemingly consistent profits on BTC 1 day chart.
I included slippage & I included commission.
100+, and covers the maximum amount of time allowed in tradingview.
The script is ready for BITCOIN and I deploy it on the 1 day timeframe because I feel like 1 day bars get enough data to make solid judgements for this type of indicator.
How to Use It
Look at the background—it’s color-coded and easy to spot.
green background = buy
red background = sell
This strategy (and the pairing indicator script) is able to be used to trade long only.
Fibonacci Trend - Aynet1. Inputs
lookbackPeriod: Defines the number of bars to consider for calculating swing highs and lows. Default is 20.
fibLevel1 to fibLevel5: Fibonacci retracement levels to calculate price levels (23.6%, 38.2%, 50%, 61.8%, 78.6%).
useTime: Enables or disables time-based Fibonacci projections.
riskPercent: Defines the percentage of risk for trading purposes (currently not used in calculations).
2. Functions
isSwingHigh(index): Identifies a swing high at the given index, where the high of that candle is higher than both its previous and subsequent candles.
isSwingLow(index): Identifies a swing low at the given index, where the low of that candle is lower than both its previous and subsequent candles.
3. Variables
swingHigh and swingLow: Store the most recent swing high and swing low prices.
swingHighTime and swingLowTime: Store the timestamps of the swing high and swing low.
fib1 to fib5: Fibonacci levels based on the difference between swingHigh and swingLow.
4. Swing Point Detection
The script checks if the last bar is a swing high or swing low using the isSwingHigh() and isSwingLow() functions.
If a swing high is detected:
The high price is stored in swingHigh.
The timestamp of the swing high is stored in swingHighTime.
If a swing low is detected:
The low price is stored in swingLow.
The timestamp of the swing low is stored in swingLowTime.
5. Fibonacci Levels Calculation
If both swingHigh and swingLow are defined, the script calculates the Fibonacci retracement levels (fib1 to fib5) based on the price difference (priceDiff = swingHigh - swingLow).
6. Plotting Fibonacci Levels
Fibonacci levels (fib1 to fib5) are plotted as horizontal lines using the line.new() function.
Labels (e.g., "23.6%") are added near the lines to indicate the level.
Lines and labels are color-coded:
23.6% → Blue
38.2% → Green
50.0% → Yellow
61.8% → Orange
78.6% → Red
7. Filling Between Fibonacci Levels
The plot() function creates lines for each Fibonacci level.
The fill() function is used to fill the space between two levels with semi-transparent colors:
Blue → Between fib1 and fib2
Green → Between fib2 and fib3
Yellow → Between fib3 and fib4
Orange → Between fib4 and fib5
8. Time-Based Fibonacci Projections
If useTime is enabled:
The time difference (timeDiff) between the swing high and swing low is calculated.
Fibonacci time projections are added based on multiples of 23.6%.
If the current time reaches a projected time, a label (e.g., "T1", "T2") is displayed near the high price.
9. Trading Logic
Two placeholder variables are defined for trading logic:
longCondition: Tracks whether a condition for a long trade is met (currently not implemented).
shortCondition: Tracks whether a condition for a short trade is met (currently not implemented).
These variables can be extended to define entry/exit signals based on Fibonacci levels.
How It Works
Detect Swing Points: It identifies recent swing high and swing low points on the chart.
Calculate Fibonacci Levels: Based on the swing points, it computes retracement levels.
Visualize Levels: Plots the levels on the chart with labels and fills between them.
Time Projections: Optionally calculates time-based projections for future price movements.
Trading Opportunities: The framework provides tools for detecting potential reversal or breakout zones using Fibonacci levels.
Dynamic Support and Resistance Pivot Strategy The Dynamic Support and Resistance Pivot Strategy is a flexible and adaptive tool designed to identify short-term support and resistance levels using the concept of price pivots.
### Key Elements of the Strategy
1. Pivot points as support and resistance levels
Pivots are significant turning points on the price chart, often marking local highs and lows where the price has reversed direction. A pivot high occurs when the price forms a local peak, while a pivot low occurs when the price forms a local trough. When a new pivot high is formed, it creates a resistance level. Conversely, when a new pivot low is formed, it creates a support level.
The strategy continuously updates these levels as new pivots are detected, ensuring they remain relevant to the current market conditions. By identifying these price levels, the strategy dynamically adjusts to market conditions, allowing it to adapt to both trending and ranging markets, since it has a long target and can perform reversal operations.
2. Entry Criteria
- Buy (Long): A long position is triggered when the price is near the support level and then crosses it from below to above. This suggests that the price has found support and may start moving upwards.
- Sell (Short): A short position is triggered when the price is near the resistance level and then crosses it from above to below. This indicates that the price may be reversing and moving downward.
3. Support/Resistance distance (%)
- This parameter establishes a percentage range around the identified support and resistance level. For example, if the Support Resistance Distance is 0.4% (default), the closing price must be within a range of 0.4% above support or below the resistance to be considered "close" and trigger a trade.
4. Exit criteria
- Take profit = 27 %
- Stop loss = 10 %
- Reversal if a new entry point is identified in the opposite direction
5. No Repainting
- The Dynamic Support and Resistance Pivot Strategy is not subject to repainting.
6. Position Sizing by Equity and risk management
- This strategy has a default configuration to operate with 35% of the equity. The stop loss is set to 10% from the entry price. This way, the strategy is putting at risk about 10% of 35% of equity, that is, around 3.5% of equity for each trade. The percentage of equity and stop loss can be adjusted by the user according to their risk management.
7. Backtest results
- This strategy was subjected to backtest and operations in replay mode on **1000000MOGUSDT.P**, with the inclusion of transaction fees at 0.12% and slipagge of 5 ticks, and the past results have shown consistent profitability. Past results are no guarantee of future results. The strategy's backtest results may even be due to overfitting with past data.
8. Chart Visualization
- Support and resistance levels are displayed as green (support) and red (resistance) lines.
- Pivot prices are displayed as green (pivot low) and red (pivot high) labels.
In this image above, the Support/Resistance distance (%) parameter was set to 0.8.
9. Default Configuration
Chart Timeframe: 1h
Pivot Lengh: 2
Support/Resistance distance (%): 0.4*
Stop Loss: 10 %
Take Profit: 27 %
* This parameter can alternatively be set to 0.8.
10. Alternative Configuration
Chart Timeframe: 20 min
Pivot Lengh: 4
Support/Resistance distance (%): 0.1
Stop Loss: 10 %
Take Profit: 25 %
BYBIT:1000000MOGUSDT.P
1h apertura de New_Yorkprobando apertura de new york ., miramos vela horaria anterior a la apertura y entramos en sentido contrario a esa vela.,
gestionamos stop loss y take proffit en % ., modificandolos en caso d eser necesario por activo
Bollinger Bands Breakout Strategy by Finesseking27Bollinger Bands Breakout Strategy by Finesseking27
Forex Hammer and Hanging Man StrategyThe strategy is based on two key candlestick chart patterns: Hammer and Hanging Man. These chart patterns are widely used in technical analysis to identify potential reversal points in the market. Their relevance in the Forex market, known for its high liquidity and volatile price movements, is particularly pronounced. Both patterns provide insights into market sentiment and trader psychology, which are critical in currency trading, where short-term volatility plays a significant role.
1. Hammer:
• Typically occurs after a downtrend.
• Signals a potential trend reversal to the upside.
• A Hammer has:
• A small body (close and open are close to each other).
• A long lower shadow, at least twice as long as the body.
• No or a very short upper shadow.
2. Hanging Man:
• Typically occurs after an uptrend.
• Signals a potential reversal to the downside.
• A Hanging Man has:
• A small body, similar to the Hammer.
• A long lower shadow, at least twice as long as the body.
• A small or no upper shadow.
These patterns are a manifestation of market psychology, specifically the tug-of-war between buyers and sellers. The Hammer reflects a situation where sellers tried to push the price down but were overpowered by buyers, while the Hanging Man shows that buyers failed to maintain the upward movement, and sellers could take control.
Relevance of Chart Patterns in Forex
In the Forex market, chart patterns are vital tools because they offer insights into price action and market sentiment. Since Forex trading often involves large volumes of trades, chart patterns like the Hammer and Hanging Man are important for recognizing potential shifts in market momentum. These patterns are a part of technical analysis, which aims to forecast future price movements based on historical data, relying on the psychology of market participants.
Scientific Literature on the Relevance of Candlestick Patterns
1. Behavioral Finance and Candlestick Patterns:
Research on behavioral finance supports the idea that candlestick patterns, such as the Hammer and Hanging Man, are relevant because they reflect shifts in trader psychology and sentiment. According to Lo, Mamaysky, and Wang (2000), patterns like these could be seen as representations of collective investor behavior, influenced by overreaction, optimism, or pessimism, and can often signal reversals in market trends.
2. Statistical Validation of Chart Patterns:
Studies by Brock, Lakonishok, and LeBaron (1992) explored the profitability of technical analysis strategies, including candlestick patterns, and found evidence that certain patterns, such as the Hammer, can have predictive value in financial markets. While their study primarily focused on stock markets, their findings are generally applicable to the Forex market as well.
3. Market Efficiency and Candlestick Patterns:
The efficient market hypothesis (EMH) posits that all available information is reflected in asset prices, but some studies suggest that markets may not always be perfectly efficient, allowing for profitable exploitation of certain chart patterns. For instance, Jegadeesh and Titman (1993) found that momentum strategies, which often rely on price patterns and trends, could generate significant returns, suggesting that patterns like the Hammer or Hanging Man may provide a slight edge, particularly in short-term Forex trading.
Testing the Strategy in Forex Using the Provided Script
The provided script allows traders to test and evaluate the Hammer and Hanging Man patterns in Forex trading by entering positions when these patterns appear and holding the position for a specified number of periods. This strategy can be tested to assess its performance across different currency pairs and timeframes.
1. Testing on Different Timeframes:
• The effectiveness of candlestick patterns can vary across different timeframes, as market dynamics change with the level of detail in each timeframe. Shorter timeframes may provide more frequent signals, but with higher noise, while longer timeframes may produce more reliable signals, but with fewer opportunities. This multi-timeframe analysis could be an area to explore to enhance the strategy’s robustness.
2. Exit Strategies:
• The script incorporates an exit strategy where positions are closed after holding them for a specified number of periods. This is useful for testing how long the reversal patterns typically take to play out and when the optimal exit occurs for maximum profitability. It can also help to adjust the exit logic based on real-time market behavior.
Conclusion
The Hammer and Hanging Man patterns are widely recognized in technical analysis as potential reversal signals, and their application in Forex trading is valuable due to the market’s high volatility and liquidity. This strategy leverages these candlestick patterns to enter and exit trades based on shifts in market sentiment and psychology. Testing and optimization, as offered by the script, can help refine the strategy and improve its effectiveness.
For further refinement, it could be valuable to consider combining candlestick patterns with other technical indicators or using multi-timeframe analysis to confirm patterns and increase the probability of successful trades.
References:
• Lo, A. W., Mamaysky, H., & Wang, J. (2000). Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation. The Journal of Finance, 55(4), 1705-1770.
• Brock, W., Lakonishok, J., & LeBaron, B. (1992). Simple Technical Trading Rules and the Stochastic Properties of Stock Returns. The Journal of Finance, 47(5), 1731-1764.
• Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. The Journal of Finance, 48(1), 65-91.
This provides a theoretical basis for the use of candlestick patterns in trading, supported by academic literature and research on market psychology and efficiency.
Autonomous 5-Minute RobotKey Components of the Strategy:
Trend Detection:
A 50-period simple moving average (SMA) is used to define the market trend. If the current close is above the SMA, the market is considered to be in an uptrend (bullish), and if it's below, it's considered a downtrend (bearish).
The strategy also looks at the trend over the last 30 minutes (6 candles in a 5-minute chart). The strategy compares the previous close with the current close to detect an uptrend or downtrend.
Volume Analysis:
The strategy calculates buyVolume and sellVolume based on price movement within each candle.
The condition for entering a long position is when the market is in an uptrend, and the buy volume is greater than the sell volume.
The condition for entering a short position is when the market is in a downtrend, and the sell volume is greater than the buy volume.
Trade Execution:
The strategy enters a long position when the trend is up and the buy volume is higher than the sell volume.
The strategy enters a short position when the trend is down and the sell volume is higher than the buy volume.
Positions are closed based on stop-loss and take-profit conditions.
Stop-loss is set at 3% below the entry price.
Take-profit is set at 29% above the entry price.
Exit Conditions:
Long trades will be closed if the price falls 3% below the entry price or rises 29% above the entry price.
Short trades will be closed if the price rises 3% above the entry price or falls 29% below the entry price.
Visuals:
The SMA (50-period) is plotted on the chart to show the trend.
Buy and sell signals are marked with labels on the chart for easy identification.
With this being said this algo is still being worked on to be autonomous
Analyze the Market Direction: Determine whether the market is in an uptrend or downtrend over the past 30 minutes (using the last 6 candles in a 5-minute chart).
Use Trend Indicators and Volume: Implement trend-following indicators like moving averages or the SMA/EMA crossover and consider volume to decide when to enter or exit a trade.
Enter and Exit Trades: The robot will enter long positions when the trend is up and short positions when the trend is down. Additionally, it will close positions based on volume signals and price action (e.g., volume spikes, price reversals).
BTCUSDT with bullish_entryAs an experienced crypto day trader, it's essential to analyze current market conditions, historical data, and emerging trends to identify optimal trading opportunities. With a capital of 200 USDT, focusing on liquid assets with significant volatility can enhance profitability. Below is a comprehensive analysis of selected cryptocurrencies, including recent price action, technical indicators, and relevant news, followed by recommended entry points, stop-loss levels, and target prices.
1. Bitcoin (BTC)
Current Price: $75,690
Recent Price Action: Bitcoin has surged to record highs, recently reaching $75,000, influenced by favorable political developments and increased institutional interest.
THE SUN
Technical Indicators:
Relative Strength Index (RSI): Currently at 70, indicating overbought conditions.
Moving Averages: The 50-day moving average is at $68,000, and the 200-day moving average is at $60,000, showing a strong upward trend.
News Impact: The recent U.S. election results have positively impacted Bitcoin's price, with expectations of a more crypto-friendly regulatory environment.
INVESTOPEDIA
Trading Strategy:
Entry Point: $74,500
Stop-Loss: $73,000
Target Price: $78,000
2. Ethereum (ETH)
Current Price: $2,918.96
Recent Price Action: Ethereum has experienced a significant rise, correlating with Bitcoin's upward movement and increased activity in decentralized finance (DeFi) platforms.
Technical Indicators:
RSI: At 65, approaching overbought territory.
Moving Averages: The 50-day moving average is at $2,500, and the 200-day moving average is at $2,200, indicating a bullish trend.
News Impact: The growth of DeFi and non-fungible tokens (NFTs) continues to drive demand for Ethereum.
Trading Strategy:
Entry Point: $2,900
Stop-Loss: $2,800
Target Price: $3,100
3. Solana (SOL)
Current Price: $201.40
Recent Price Action: Solana has shown strong performance, reaching new highs, driven by its scalability and growing ecosystem.
Technical Indicators:
RSI: At 72, indicating overbought conditions.
Moving Averages: The 50-day moving average is at $180, and the 200-day moving average is at $150, reflecting a strong uptrend.
News Impact: Increased adoption of Solana's blockchain for DeFi projects and NFTs has contributed to its price surge.
Pamplona Enhanced TP/SL ToggleableName: Pamplona Enhanced TP/SL Toggleable
Type: Strategy
Description:
This strategy introduces flexibility and innovation in managing Take Profit (TP) and Stop Loss (SL) levels, making it a valuable tool for traders. It offers three configurable modes: Tick-Based, Dollar-Based, and Risk-Reward Ratio-Based, allowing users to toggle between them based on trading preferences. The strategy combines robust technical indicators to identify optimal trade opportunities and improves reliability by entering trades only on the second signal.
Key Features:
TP/SL Modes:
Tick-Based: Uses a fixed number of ticks to calculate TP/SL.
Dollar-Based: Uses fixed dollar amounts for TP/SL.
Risk-Reward Ratio-Based: Calculates TP/SL based on a user-defined ratio.
The user can toggle one mode at a time for precise control.
Trade Logic:
Long Trades: Triggered when price trends above the 200 EMA, the Madrid Ribbon turns bullish, and price exceeds the Donchian Channel high. The trade is confirmed only after the second valid signal.
Short Trades: Triggered when price trends below the 200 EMA, the Madrid Ribbon turns bearish, and price breaks the Donchian Channel low. The trade is confirmed only after the second valid signal.
Dynamic Configuration:
Adjustable ticks, dollar amounts, and risk-reward ratios in the settings.
Allows users to define contract size and Donchian Channel length.
Originality and Usefulness:
This strategy enhances common trading methodologies by:
Offering a configurable multi-mode TP/SL system that adapts to diverse trading styles.
Using a confirmation-based entry system, which reduces false signals and increases reliability.
Combining widely used indicators (EMA, Madrid Ribbon, Donchian Channel) into a practical framework for trend-following strategies.
How to Use:
Set TP/SL Mode:
In the settings, enable only one mode (Tick-Based, Dollar-Based, or Risk-Reward).
Adjust relevant parameters for the selected mode (e.g., ticks, dollar values, or risk-reward ratio).
Customize Trade Settings:
Define the contract size and Donchian Channel period.
The default configuration is suited for swing trading but can be adapted to other timeframes.
Understand Trade Logic:
The background highlights potential long (green) and short (red) zones.
Long entries occur when all conditions align bullishly, confirmed on the second signal.
Short entries occur when all conditions align bearishly, confirmed on the second signal.
Review Backtesting Results:
Use realistic commission, slippage, and risk values.
Ensure settings align with your trading style and risk management rules.
Notes:
No repainting: The script operates entirely on historical and current data without lookahead bias.
Backtesting: Test the strategy across multiple assets and timeframes to ensure robustness.
Customizability: The toggling system and configurable parameters make this strategy highly adaptable.
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反彈三次突破策略策略說明 (Strategy Explanation)
英文 (English)
This strategy is called "反彈三次突破策略" (Three Rebound Breakthrough Strategy). It is designed to identify and trade based on three consecutive price drops followed by a rebound, ensuring certain conditions are met before entering a trade. The key components and conditions of this strategy are as follows:
Moving Averages (MAs):
Fast MA: The short-term moving average (e.g., 5 periods).
Slow MA: The long-term moving average (e.g., 20 periods).
The crossover of these MAs generates buy (long) and sell (short) signals.
Average True Range (ATR):
Used to calculate volatility and set stop-loss and take-profit levels.
Three Consecutive Drops and Rebounds:
The strategy identifies three consecutive drops in price, each creating a new lower low (low1, low2, low3).
After the third drop, the price must rebound and break above the previous low's rebound height.
Parallel Channel:
A parallel channel is drawn between the lowest points (low1 and low3) to visualize the price range.
Two lines (lower and upper) form the channel.
Entry and Exit Conditions:
Entry signals are based on MA crossovers and the three rebound condition.
Stop-loss and take-profit levels are set using ATR-based calculations.
Labels are added to the chart to indicate stop-loss and take-profit points.
中文 (Chinese)
這個策略叫做 "反彈三次突破策略"。其目的是識別並基於三次連續價格下跌後的反彈進行交易，並確保在進行交易之前滿足某些條件。該策略的關鍵組成部分和條件如下：
移動平均線 (MAs):
快速均線：短期移動平均線（例如，5 期）。
慢速均線：長期移動平均線（例如，20 期）。
這些均線的交叉產生買入（做多）和賣出（做空）信號。
真實波動範圍 (ATR):
用於計算波動性並設置止損和止盈水平。
三次連續下跌和反彈：
該策略識別連續三次的價格下跌，每次都創下更低的低點（low1、low2、low3）。
在第三次下跌後，價格必須反彈並突破前一個低點的反彈高度。
平行通道：
在最低點（low1 和 low3）之間繪製平行通道，以可視化價格區間。
兩條線（下邊界和上邊界）形成通道。
進出場條件：
進場信號基於均線交叉和三次反彈條件。
使用基於 ATR 的計算設置止損和止盈水平。
在圖表上添加標籤以指示止損和止盈點。
profit factor 1.5 great tradesgreat strategy to get a good profit factor as it involves less indicators and is a proven strategy
Reliance 30-Minute Third Candle Breakouthere we are talking about reliance 30 min candle break out it an give you clear break out most of the time
Swing Trading StrategyThis Swing Trading Strategy combines technical indicators and Fibonacci retracement levels to identify potential buy and sell opportunities in the market. It uses key tools like RSI, MACD, moving averages, and Fibonacci levels for precision and trend confirmation.
Key Indicators:
1. RSI (14): Identifies overbought (>70) and oversold (<30) conditions.
2. MACD: Detects momentum shifts with bullish or bearish crossovers.
3. Moving Averages: A short-term MA (50) and long-term MA (200) determine uptrends and downtrends.
4. Fibonacci Levels (0.382, 0.5, 0.618): Calculate dynamic support and resistance zones based on recent highs and lows.
Entry and Exit Conditions:
• Long Entry: In an uptrend, RSI < 30, MACD bullish crossover, and price within Fibonacci levels.
• Short Entry: In a downtrend, RSI > 70, MACD bearish crossover, and price within Fibonacci levels.
• Exits: Positions close if the trend reverses (via MACD) or RSI reaches extreme levels.
Visualization:
The strategy dynamically plots Fibonacci levels and moving averages for enhanced decision-making.
This strategy is ideal for swing traders, leveraging trend and momentum to identify profitable short- to medium-term opportunities.
Martingale Shorthjgfidjgioajfiodjgiofjsdgojdfiosgjidosfjgiodfsjgsjiogjiodfsjgoifjdsgijsgodfhjgoidjfsgiodjfgjdsfoigjdsogjdiosg
RVM - MA Bounce Low Cheat Strategy with LLS SignalsYellow triangle represent candles which bounc off of 10d MA or 21d EMA or 50d Ma with long lower wick and small body bullish candle. respresnting potential upside.
If the price breaches the clandle close price of the yellow candle in the next successive 5 sessions there will be a buy green triangle triggered.
Dynamic Volatility Differential Model (DVDM)The Dynamic Volatility Differential Model (DVDM) is a quantitative trading strategy designed to exploit the spread between implied volatility (IV) and historical (realized) volatility (HV). This strategy identifies trading opportunities by dynamically adjusting thresholds based on the standard deviation of the volatility spread. The DVDM is versatile and applicable across various markets, including equity indices, commodities, and derivatives such as the FDAX (DAX Futures).
Key Components of the DVDM:
1. Implied Volatility (IV):
The IV is derived from options markets and reflects the market’s expectation of future price volatility. For instance, the strategy uses volatility indices such as the VIX (S&P 500), VXN (Nasdaq 100), or RVX (Russell 2000), depending on the target market. These indices serve as proxies for market sentiment and risk perception (Whaley, 2000).
2. Historical Volatility (HV):
The HV is computed from the log returns of the underlying asset’s price. It represents the actual volatility observed in the market over a defined lookback period, adjusted to annualized levels using a multiplier of \sqrt{252} for daily data (Hull, 2012).
3. Volatility Spread:
The difference between IV and HV forms the volatility spread, which is a measure of divergence between market expectations and actual market behavior.
4. Dynamic Thresholds:
Unlike static thresholds, the DVDM employs dynamic thresholds derived from the standard deviation of the volatility spread. The thresholds are scaled by a user-defined multiplier, ensuring adaptability to market conditions and volatility regimes (Christoffersen & Jacobs, 2004).
Trading Logic:
1. Long Entry:
A long position is initiated when the volatility spread exceeds the upper dynamic threshold, signaling that implied volatility is significantly higher than realized volatility. This condition suggests potential mean reversion, as markets may correct inflated risk premiums.
2. Short Entry:
A short position is initiated when the volatility spread falls below the lower dynamic threshold, indicating that implied volatility is significantly undervalued relative to realized volatility. This signals the possibility of increased market uncertainty.
3. Exit Conditions:
Positions are closed when the volatility spread crosses the zero line, signifying a normalization of the divergence.
Advantages of the DVDM:
1. Adaptability:
Dynamic thresholds allow the strategy to adjust to changing market conditions, making it suitable for both low-volatility and high-volatility environments.
2. Quantitative Precision:
The use of standard deviation-based thresholds enhances statistical reliability and reduces subjectivity in decision-making.
3. Market Versatility:
The strategy’s reliance on volatility metrics makes it universally applicable across asset classes and markets, ensuring robust performance.
Scientific Relevance:
The strategy builds on empirical research into the predictive power of implied volatility over realized volatility (Poon & Granger, 2003). By leveraging the divergence between these measures, the DVDM aligns with findings that IV often overestimates future volatility, creating opportunities for mean-reversion trades. Furthermore, the inclusion of dynamic thresholds aligns with risk management best practices by adapting to volatility clustering, a well-documented phenomenon in financial markets (Engle, 1982).
References:
1. Christoffersen, P., & Jacobs, K. (2004). The importance of the volatility risk premium for volatility forecasting. Journal of Financial and Quantitative Analysis, 39(2), 375-397.
2. Engle, R. F. (1982). Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987-1007.
3. Hull, J. C. (2012). Options, Futures, and Other Derivatives. Pearson Education.
4. Poon, S. H., & Granger, C. W. J. (2003). Forecasting volatility in financial markets: A review. Journal of Economic Literature, 41(2), 478-539.
5. Whaley, R. E. (2000). The investor fear gauge. Journal of Portfolio Management, 26(3), 12-17.
This strategy leverages quantitative techniques and statistical rigor to provide a systematic approach to volatility trading, making it a valuable tool for professional traders and quantitative analysts.
Moving Average Channel (MAC)The strategy uses two Simple Moving Averages (SMA): an upper MA based on the high price and a lower MA based on the low price. Key features include:
Entry Condition: Enter a long position after five consecutive bars close above the upper MA.
Exit Conditions:
Close the position if five consecutive bars close below the lower MA.
Close the position if the price drops below 25% of the highest price recorded since entry (stop-loss).
Key Features:
Dynamic Entry: Long position is triggered only after consistent strength in price (5 bars above the upper MA).
Dynamic Exit:
Tracks weakness (5 bars below the lower MA) for exit.
Implements a stop-loss based on 25% retracement from the highest price recorded post-entry.
Customizable Parameters: MA lengths and stop-loss percentage are adjustable to fit different trading styles and market conditions.
This script provides a simple yet effective trend-following strategy with built-in risk management.
Demo GPT - MACD and RSI Short Strategy//@version=5
strategy("Demo GPT - MACD and RSI Short Strategy", overlay=true, commission_type=strategy.commission.percent, commission_value=0.1, slippage=3)
// Inputs for start and end dates
start_date = input.time(timestamp("2018-01-01 00:00"), title="Start Date")
end_date = input.time(timestamp("2069-12-31 23:59"), title="End Date")
// Inputs for MACD and RSI
macd_short_length = input.int(12, title="MACD Short Length")
macd_long_length = input.int(26, title="MACD Long Length")
macd_signal_length = input.int(9, title="MACD Signal Length")
rsi_length = input.int(14, title="RSI Length")
rsi_overbought = input.int(70, title="RSI Overbought Level")
// Calculate MACD and Signal Line
= ta.macd(close, macd_short_length, macd_long_length, macd_signal_length)
// Fill gaps in MACD and Signal Line
macd_line := na(macd_line) ? macd_line : macd_line
signal_line := na(signal_line) ? signal_line : signal_line
// Calculate RSI
rsi = ta.rsi(close, rsi_length)
// Fill gaps in RSI
rsi := na(rsi) ? rsi : rsi
// Strategy logic: Short when MACD crosses below Signal Line and RSI is above 70
short_condition = ta.crossover(signal_line, macd_line) and rsi > rsi_overbought
// Ensure the strategy only runs between the selected date range
if (time >= start_date and time <= end_date)
if short_condition
strategy.entry("Short", strategy.short, qty=100)
strategy.close("Short")
// Plotting MACD and RSI for reference
plot(macd_line - signal_line, color=color.red, title="MACD Histogram", linewidth=2)
hline(0, "Zero Line", color=color.gray)
plot(rsi, color=color.blue, title="RSI", linewidth=2)
hline(rsi_overbought, "RSI Overbought", color=color.red)
AI - Bull Market Support BandChatGPT Bull Market Support Band based on the weekly sma Length = 20 emaLength = 21
Bollinger Bands Breakout Strategy by Finesseking27Bollinger Bands Breakout Strategy by Finesseking27
Pamplona Enhanced TP/SL ToggleableName: Pamplona Enhanced TP/SL Toggleable
Type: Strategy
Description:
This strategy introduces flexibility and innovation in managing Take Profit (TP) and Stop Loss (SL) levels, making it a valuable tool for traders. It offers three configurable modes: Tick-Based, Dollar-Based, and Risk-Reward Ratio-Based, allowing users to toggle between them based on trading preferences. The strategy combines robust technical indicators to identify optimal trade opportunities and improves reliability by entering trades only on the second signal.
Key Features:
TP/SL Modes:
Tick-Based: Uses a fixed number of ticks to calculate TP/SL.
Dollar-Based: Uses fixed dollar amounts for TP/SL.
Risk-Reward Ratio-Based: Calculates TP/SL based on a user-defined ratio.
The user can toggle one mode at a time for precise control.
Trade Logic:
Long Trades: Triggered when price trends above the 200 EMA, the Madrid Ribbon turns bullish, and price exceeds the Donchian Channel high. The trade is confirmed only after the second valid signal.
Short Trades: Triggered when price trends below the 200 EMA, the Madrid Ribbon turns bearish, and price breaks the Donchian Channel low. The trade is confirmed only after the second valid signal.
Dynamic Configuration:
Adjustable ticks, dollar amounts, and risk-reward ratios in the settings.
Allows users to define contract size and Donchian Channel length.
Originality and Usefulness:
This strategy enhances common trading methodologies by:
Offering a configurable multi-mode TP/SL system that adapts to diverse trading styles.
Using a confirmation-based entry system, which reduces false signals and increases reliability.
Combining widely used indicators (EMA, Madrid Ribbon, Donchian Channel) into a practical framework for trend-following strategies.
How to Use:
Set TP/SL Mode:
In the settings, enable only one mode (Tick-Based, Dollar-Based, or Risk-Reward).
Adjust relevant parameters for the selected mode (e.g., ticks, dollar values, or risk-reward ratio).
Customize Trade Settings:
Define the contract size and Donchian Channel period.
The default configuration is suited for swing trading but can be adapted to other timeframes.
Understand Trade Logic:
The background highlights potential long (green) and short (red) zones.
Long entries occur when all conditions align bullishly, confirmed on the second signal.
Short entries occur when all conditions align bearishly, confirmed on the second signal.
Review Backtesting Results:
Use realistic commission, slippage, and risk values.
Ensure settings align with your trading style and risk management rules.
Notes:No repainting: The script operates entirely on historical and current data without lookahead bias.
Backtesting: Test the strategy across multiple assets and timeframes to ensure robustness.
Customizability: The toggling system and configurable parameters make this strategy highly adaptable.
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