BabyShark VWAP Strategy What the code does:
This Pine Script implements a trading strategy based on two indicators: Volume Weighted Average Price (VWAP) and On Balance Volume (OBV) Relative Strength Index (RSI). The strategy aims to identify potential buy and sell signals based on deviations from VWAP and OBV RSI crossing certain threshold levels.
How it does it:
**VWAP Calculation**: The script calculates the VWAP using either standard deviation or average deviation over a specified length. It then plots the VWAP and its upper and lower deviation bands.
**OBV RSI Calculation**: It computes the OBV and then calculates the RSI using the cumulative changes in OBV. The RSI is plotted and compared against predefined levels.
**Table Visibility and Occurrence Counting**: It allows the user to display a table showing the number of occurrences where the price is above Upper Dev 2, below Lower Dev 2, crosses above a higher RSI level, or crosses below a lower RSI level.
**Entries**: Long and short entry conditions are defined based on the position of the price relative to the VWAP deviation bands and the color of the OBV RSI. Entries are made when specific conditions are met, and there hasn't been a recent entry.
**Exit Conditions**: The script includes stop-loss and take-profit mechanisms. It exits positions based on price crossing the VWAP or a certain percentage, and it prevents further trading after a certain number of consecutive losses.
What traders can use it for:
**Trend Identification**: Traders can use the VWAP and its deviation bands to identify potential trend reversals or continuations.
**Volume Confirmation**: The inclusion of OBV RSI provides confirmation of price movements based on volume changes.
**Entry and Exit Signals**: The script generates buy and sell signals based on the specified conditions, allowing traders to enter and exit positions with defined stop-loss and take-profit levels.
**Statistical Analysis**: The visibility of occurrence counts in the table allows traders to perform statistical analysis on the frequency of price movements relative to the VWAP and OBV RSI levels.
지표 및 전략
INFINITY ALGO🆕Meet the updated version of our flagship indicator, now it's INFINITY ALGO!
🏃🏻 QUICK START
In very simple terms, our indicator generates complex trading signals on your chart (buy/sell), including Entry Point, Take Profit levels, Stop Loss level
To start, you need to add our indicator to your chart , choose a timeframe (we recommend 13min,15min and 4h but you can try any, these only have the best results) and set up notifications (how to do it told below) and that's it, you can work with it even without changing the settings!
Of course, to improve the accuracy of signals you will have to choose the optimal settings of the script for each trading pair and timeframe (you can find a guide below)
📊 SIGNALS
This script will generate complex trading recommendations, both Long and Short (signals); signals include:
- Entry Point:
Calculated based on pivot levels with confirmation by EMA/SMA (you can select this in the settings); also bullish/bearish cup is checked to confirm the entry.
Additionally, in the settings you can enable Heiken Ashi calculation mode (it shows much better on some trading pairs).
Why do we mashup these components and how they work together?
- The main indicator in our script is pivot levels, it is enabled by default and cannot be disabled. Auxiliary indicators (which you can switch on and off in the script settings) are EMA/SMA and Heiken Ashi. We have used pivot levels, which mark potential support and resistance zones based on previous price action. We have also used EMA/SMA that smooth out price fluctuations and show the direction of the trend. We have added an option to use Heiken Ashi that filters out noise and highlights the trend. We have also checked for bullish/bearish cup patterns, which are reversal patterns that indicate a change in momentum. By combining these indicators, we have created a more robust entry point that considers multiple factors such as price levels, trend, noise, and momentum.
- 6 Take Profit levels:
It is also possible to change in the settings (It is also possible to change the values for Short or Long positions separately), it will be fixed values in % (The default Take Profits for Long&Short are as follows: TP1-0.3%; TP2-1%; TP3-2%; TP4-3%; TP5-7.5%; TP6-16.5%)
- Stop Loss Level:
As with Take Profits, this is a fixed % value that you can customise to suit your risk management needs (It is also possible to change the values for Short or Long positions separately, by default is 4.5% for Long&Short positions)
*When trading on these signals, we strongly recommend that you exit the position in parts at each take profit or close your entire position at one particular take profit. Our script was designed specifically for exiting a position on take profits
⚙️ SETTINGS
Now let's talk about the settings of this script, which allow you to customise the signals quite a lot. In general, we recommend selecting the settings for each trading pair and timeframe separately, this will allow you to achieve better targets accuracy (the default settings are universal, you can trade with them without changing them if you want)
-> IMAGE <-
1. Period - minimum value of 2. Increasing this parameter will increase the accuracy of signals, but will reduce their number (accordingly, lowering the parameter will do the opposite). For the majority of trading pairs and timeframes the optimal period will be between 5 and 10 (the default value is 5).
2. Maximum Breakout length (in bars) - for most trading pairs you can set the value from 200 to 300 and it will be optimal. Below 200 is not recommended
3. T hreshold Rate % - this value also affects the accuracy and the number of signals - the higher this value is, the more often signals will be generated, but it can negatively affect the accuracy. The minimum value is 3, and the maximum value is 10. We recommend to try values in the range from 4 to 7 for most tickers
4. Minimum Number of tests - the number of level checks is required, we recommend to try 2, and only for some timeframes increase to 3
5. MA type & MA filter - The shorter the length of moving averages, the faster they react to trend changes, and show more local trends than global ones. If the length of MAs is longer, more global trends are shown. By default, the most optimal values are set.
By the way, you can ask us for a ready-made preset for any pair and we will be happy to help you!
📄 BACKTESTING
Now let's talk about how to properly test the settings and evaluate their effectiveness. Our script has a c ustom built-in backtester that shows statistics on the current trading pair and allows you to calculate the accuracy of each take profit target, as well as calculate values such as Gross profit/loss, net profit, and the ratio of initial deposit to profit. (you can enable/disable backtester "statistics" label in main settings)
In the main settings you can change the values for: initial deposit (Deposit $), trade size $ and leverage (by the way, it also affects the display of the label "Peak profit", which is calculated with this leverage)
-> IMAGE <-
Now let's look at the backtester - it shows detailed statistics for each Take Profit level, including: accuracy in % and number of trades; gross profit & loss; net profit in % and $ (based on selected settings); deposit to profit ratio in % and $.
Why did we choose such properties in the backtest for publication?
- Well, as the initial capital we took 5000$ and deposit 3% (150$) of the initial capital in each trade. For the fee was taken the value from the exchange Binance, which is 0.06% per trade (Taker + Maker, for a user without VIP on Binance and without taking into account additional fees such as funding, leverage fees, etc).
- Please also take a look at our inbuilt backtester ( IMAGE ) which counts the accuracy to each Take Profit. Also note that our inbuilt backtester does not take any fees into account. Pay attention to the last field "Deposit with Profit" it shows the value if you would close all positions at a certain target. For example, we can see that the most optimal is TP3 at these settings for this trading pair and timeframe, as the deposit to profit ratio will be +61.2%
- Also the script is more designed for swing and long term trading, so on most trading pairs you will be able to see statistics for 60-90 trades dataset
*disclaimer: please note that past results does not guarantee future performance! The accuracy of take profit targets in our backtester is calculated on past results, keep this in mind please
📥 NOTIFICATIONS
We have provided notifications that will deliver the latest signals to you in a convenient format in TradingView. The notification looks like this: It contains the entry point, Take Profits, Stop Loss, and a bit of advice on risk management. -> IMAGE <-
To set up notifications:
1. Select the script settings, trading pair and timeframe
2. Click "add alert on InfinityAlgo", then select "alert () function calls only" in the settings
-> IMAGE <-
3. That's it, now all that's left is to wait for a fresh alert
🔑 HOW TO GET ACCESS
We hope you will like this script :) We are always ready to help you with customisation, just let us know! To learn more about our scripts & get access - check out the “Author’s instructions” below 👇🏼
Trend Deviation strategy - BTC [IkkeOmar]Intro:
This is an example if anyone needs a push to get started with making strategies in pine script. This is an example on BTC, obviously it isn't a good strategy, and I wouldn't share my own good strategies because of alpha decay.
This strategy integrates several technical indicators to determine market trends and potential trade setups. These indicators include:
Directional Movement Index (DMI)
Bollinger Bands (BB)
Schaff Trend Cycle (STC)
Moving Average Convergence Divergence (MACD)
Momentum Indicator
Aroon Indicator
Supertrend Indicator
Relative Strength Index (RSI)
Exponential Moving Average (EMA)
Volume Weighted Average Price (VWAP)
It's crucial for you guys to understand the strengths and weaknesses of each indicator and identify synergies between them to improve the strategy's effectiveness.
Indicator Settings:
DMI (Directional Movement Index):
Length: This parameter determines the number of bars used in calculating the DMI. A higher length may provide smoother results but might lag behind the actual price action.
Bollinger Bands:
Length: This parameter specifies the number of bars used to calculate the moving average for the Bollinger Bands. A longer length results in a smoother average but might lag behind the price action.
Multiplier: The multiplier determines the width of the Bollinger Bands. It scales the standard deviation of the price data. A higher multiplier leads to wider bands, indicating increased volatility, while a lower multiplier results in narrower bands, suggesting decreased volatility.
Schaff Trend Cycle (STC):
Length: This parameter defines the length of the STC calculation. A longer length may result in smoother but slower-moving signals.
Fast Length: Specifies the length of the fast moving average component in the STC calculation.
Slow Length: Specifies the length of the slow moving average component in the STC calculation.
MACD (Moving Average Convergence Divergence):
Fast Length: Determines the number of bars used to calculate the fast EMA (Exponential Moving Average) in the MACD.
Slow Length: Specifies the number of bars used to calculate the slow EMA in the MACD.
Signal Length: Defines the number of bars used to calculate the signal line, which is typically an EMA of the MACD line.
Momentum Indicator:
Length: This parameter sets the number of bars over which momentum is calculated. A longer length may provide smoother momentum readings but might lag behind significant price changes.
Aroon Indicator:
Length: Specifies the number of bars over which the Aroon indicator calculates its values. A longer length may result in smoother Aroon readings but might lag behind significant market movements.
Supertrend Indicator:
Trendline Length: Determines the length of the period used in the Supertrend calculation. A longer length results in a smoother trendline but might lag behind recent price changes.
Trendline Factor: Specifies the multiplier used in calculating the trendline. It affects the sensitivity of the indicator to price changes.
RSI (Relative Strength Index):
Length: This parameter sets the number of bars over which RSI calculates its values. A longer length may result in smoother RSI readings but might lag behind significant price changes.
EMA (Exponential Moving Average):
Fast EMA: Specifies the number of bars used to calculate the fast EMA. A shorter period results in a more responsive EMA to recent price changes.
Slow EMA: Determines the number of bars used to calculate the slow EMA. A longer period results in a smoother EMA but might lag behind recent price changes.
VWAP (Volume Weighted Average Price):
Default settings are typically used for VWAP calculations, which consider the volume traded at each price level over a specific period. This indicator provides insights into the average price weighted by trading volume.
backtest range and rules:
You can specify the start date for backtesting purposes.
You can can select the desired trade direction: Long, Short, or Both.
Entry and Exit Conditions:
LONG:
DMI Cross Up: The Directional Movement Index (DMI) indicates a bullish trend when the positive directional movement (+DI) crosses above the negative directional movement (-DI).
Bollinger Bands (BB): The price is below the upper Bollinger Band, indicating a potential reversal from the upper band.
Momentum Indicator: Momentum is positive, suggesting increasing buying pressure.
MACD (Moving Average Convergence Divergence): The MACD line is above the signal line, indicating bullish momentum.
Supertrend Indicator: The Supertrend indicator signals an uptrend.
Schaff Trend Cycle (STC): The STC indicates a bullish trend.
Aroon Indicator: The Aroon indicator signals a bullish trend or crossover.
When all these conditions are met simultaneously, the strategy considers it a favorable opportunity to enter a long trade.
SHORT:
DMI Cross Down: The Directional Movement Index (DMI) indicates a bearish trend when the negative directional movement (-DI) crosses above the positive directional movement (+DI).
Bollinger Bands (BB): The price is above the lower Bollinger Band, suggesting a potential reversal from the lower band.
Momentum Indicator: Momentum is negative, indicating increasing selling pressure.
MACD (Moving Average Convergence Divergence): The MACD line is below the signal line, signaling bearish momentum.
Supertrend Indicator: The Supertrend indicator signals a downtrend.
Schaff Trend Cycle (STC): The STC indicates a bearish trend.
Aroon Indicator: The Aroon indicator signals a bearish trend or crossover.
When all these conditions align, the strategy considers it an opportune moment to enter a short trade.
Disclaimer:
THIS ISN'T AN OPTIMAL STRATEGY AT ALL! It was just an old project from when I started learning pine script!
The backtest doesn't promise the same results in the future, always do both in-sample and out-of-sample testing when backtesting a strategy. And make sure you forward test it as well before implementing it!
Furthermore this strategy uses both trend and mean-reversion systems, that is usually a no-go if you want to build robust trend systems .
Don't hesitate to comment if you have any questions or if you have some good notes for a beginner.
Aroon and ASH strategy - ETHERIUM [IkkeOmar]Intro:
This post introduces a Pine Script strategy, as an example if anyone needs a push to get started. This example is a strategy on ETH, obviously it isn't a good strategy, and I wouldn't share my own good strategies because of alpha decay. This strategy combines two technical indicators: Aroon and Absolute Strength Histogram (ASH).
Overview:
The strategy employs the Aroon indicator alongside the Absolute Strength Histogram (ASH) to determine market trends and potential trade setups. Aroon helps identify the strength and direction of a trend, while ASH provides insights into the strength of momentum. By combining these indicators, the strategy aims to capture profitable trading opportunities in Ethereum markets. Normally when developing strats using indicators, you want to find some good indicators, but you NEED to understand their strengths and weaknesses, other indicators can be incorporated to minimize the downs of another indicator. Try to look for synergy in your indicators!
Indicator settings:
Aroon Indicator:
- Two sets of parameters are used for the Aroon indicator:
- For Long Positions: Aroon periods are set to 56 (upper) and 20 (lower).
- For Short Positions: Aroon periods are set to 17 (upper) and 55 (lower).
Absolute Strength Histogram (ASH):
ASH is calculated with a length of 9 bars using the closing price as the data source.
Trading Conditions:
The strategy incorporates specific conditions to initiate and exit trades:
Start Date:
Traders can specify the start date for backtesting purposes.
Trade Direction:
Traders can select the desired trade direction: Long, Short, or Both.
Entry and Exit Conditions:
1. Long Position Entry: A long position is initiated when the Aroon indicator crosses over (crossover) the lower Aroon threshold, indicating a potential uptrend.
2. Long Position Exit: A long position is closed when the Aroon indicator crosses under (crossunder) the lower Aroon threshold.
3. Short Position Entry: A short position is initiated when the Aroon indicator crosses under (crossunder) the upper Aroon threshold, signaling a potential downtrend.
4. Short Position Exit: A short position is closed when the Aroon indicator crosses over (crossover) the upper Aroon threshold.
Disclaimer:
THIS ISN'T AN OPTIMAL STRATEGY AT ALL! It was just an old project from when I started learning pine script!
The backtest doesn't promise the same results in the future, always do both in-sample and out-of-sample testing when backtesting a strategy. And make sure you forward test it as well before implementing it!
EMA Crossover Strategy with RSI Filter BIGTIME 5mThis script essentially creates a trading strategy that goes long when there is an EMA crossover, but only if the RSI is below a certain overbought level. It goes short when there is an EMA crossunder, but only if the RSI is above a certain oversold level. The moving averages are plotted on the chart for visual reference.
SCALPING 5m
Pairs: BIGTIME/USDT--- API3/USDT---BAKE/USDT--- ZIL/USDT
How to force strategies fire exit alerts not reversalsPineScript has gone a long way, from very simple and little-capable scripting language to a robust coding platform with reliable execution endpoints. However, this one small intuitivity glitch is still there and is likely to stay, because it is traditionally justified and quite intuitive for significant group of traders. I'm sharing this workaround in response to frequent inquiries about it.
What's the glitch? When setting alerts on strategies to be synchronized with TradingView's Strategy Tester events, using simple alert messages such as "buy" or "sell" based on entry direction seems straightforward by inserting {{strategy.order.action}} into the Create Alert's "Message" field. Because "buy" or "sell" are exactly the strings produced by {{strategy.order.action}} placeholder. However, complications arise when attempting to EXIT positions without reversing, whether triggered by price levels like Stop Loss or Take Profit, or logical conditions to close trades. Those bricks fall apart, because on such events {{strategy.order.action}} sends the same "sell" for exiting buy positions and "buy" for exiting sell positions, instead of something more differentiating like "closebuy" or "closesell". As a result reversal trades are opened, instead of simply closing the open ones.
This convention harkens back to traditional stock market practices, where traders either bought shares to enter positions or sold them to exit. However, modern trading encompasses diverse instruments like CFDs, indices, and Forex, alongside advanced features such as Stop Loss, reshaping the landscape. Despite these advancements, the traditional nomenclature persists.
And is poised to stay on TradingView as well, so we need a workaround to get a simple strategy going. Luckily it is here and is called alert_message . It is a parameter, which needs to be added into each strategy.entry() / strategy.exit() / strategy.close() function call - each call, which causes Strategy Tester to produce entry or exit orders. As in this example script:
line 12: strategy.entry(... alert_message ="buy")
line 14: strategy.entry(... alert_message ="sell")
line 19: strategy.exit(... alert_message ="closebuy")
line 20: strategy.exit(... alert_message ="closesell")
line 24: strategy.close(... alert_message ="closebuy")
line 26: strategy.close(... alert_message ="closesell")
These alert messages are compatible with the Alerts Syntax of TradingConnector - a tool facilitating auto-execution of TradingView alerts in MetaTrader 4 or 5. Yes, simple alert messages like "buy" / "sell" / "closebuy" / "closesell" suffice to carry the execution of simple strategy, without complex JSON files with multiple ids and such. Other parameters can be added (actually plenty), but they are only option and that's not a part of this story :)
Last thing left to do is to replace "Message" in Create Alert popup with {{strategy.order.alert_message}} . This placeholder transmits the string defined in the PineScript alert_message= parameter, as outlined in this publication. With this workaround, executing closing alerts becomes seamless within PineScript strategies on TradingView.
Disclaimer: this content is purely educational, especially please don't pay attention to backtest results on any timeframe/ticker.
Strategy / Connectable [Azullian]The connectable strategy serves as a foundational component in our indicator system on TradingView, designed for intuitive testing, visualization, and construction of trading strategies. In concert with the connectable signal filter , it forms a cohesive unit that allows for efficient signal processing and strategy implementation. This integration enables the strategy to receive and act on weighted signals from various connectable indicators, making it a versatile tool for both novice and experienced traders.
Let's review the separate parts of this indicator.
█ STRATEGY INPUTS
We've provided an input to connect a signal filter or indicators or chains (→) which is set to 'Close' by default.
An input has several controls:
• Input: Connect indicators or signal filter here, choose indicators with a compatible : Signal connector.
• SM - Signal Mode: Choose a trading direction compatible with the settings in your signal filter
█ POSITION INVESTMENT
Determine the percentage of your trading budget you would like to use in each position based on the strategy's profit or loss.
• LINVB - Loss Investment Base: Choose which base to use to determine the investment percentage when the strategy is in a loss.
○ Equity: Use the equity as the base for percentage calculation.
○ Initial capital: Use the initial capital as the base for percentage calculation.
• LINV% - Loss Investment Percentage: Set a percentage of the chosen investment base as the investment for a new position.
○ For example, when 10% in loss, and a initial capital of $100, and the investment base is set to equity with a percentage of 50%, your investment will be 50% of $90, $45.
• PINVB - Profit Investment Base: Choose which base to use to determine the investment percentage when the strategy is in profit.
○ Equity: Use the equity as the base for percentage calculation.
○ Initial capital: Use the initial capital as the base for percentage calculation.
• PINV% - Profit Investment Percentage: Set a percentage of the chosen investment base as the investment for a new position.
○ For example, when 10% in profit, and an initial capital of $100, and the investment base is set to equity with a percentage of 100%, your investment will be 100% of $110, $110.
• RISK% - Risk Percentage:
○ Determine how much of the calculated position investment is at risk when the stop-loss is hit.
- For example, 1% of $45 represents a maximum loss of $0.45.
○ Risk percentage works together with the stop loss and the max leverage.
• MXLVG - Maximum Leverage:
○ Investigate the trading rules for your trading pair and use the maximum allowed amount of leverage.
○ To determine the number of contracts to be bought or sold, considering the stop loss and the specified risk percentage, the maximum leverage available will constrain the amount of leverage utilized to ensure that the maximum risk threshold is not exceeded. For instance, suppose the stop loss is set at 1%, and the risk percentage is defined as 10%. Initially, the calculated leverage to be used would be 10. However, if there is a maximum leverage cap set at 5, it would constrain the calculated leverage of 10 to adhere to the maximum limit of 5.
█ EXIT STOP LOSS
Determine the Stop Loss price based on your selected configuration.
As the stop loss is an integral part of the ordered contracts calculation used in conjunction with the Risk and Max leverage, you'll always need to provide a stop loss price.
• SLB - Stop Loss Base: Choose a stop loss mode for calculating stop loss prices.
○ Risk: Determines the price using the Risk parameter (RISK%) and maximum leverage (MXLVG). In this case, SLB% will not have any impact.
○ Price Entry + Offset: Calculates the stop loss price based on a offset percentage (SLB%) from the entry price of the position.
• SLB% - Stop Loss Base Percentage: Define an offset percentage that will be applied in the price entry + offset stop loss mode.
• SLT - Stop Loss Trailing:
○ Fixed: The initial stop loss will be kept and no trailing stop loss will be applied.
○ Trail Price: Computes the trailing stop loss price based on an offset percentage (SLT%) from the closing price of the current candle.
- If a better stop loss price is calculated, it will be set as the new stop loss price.
○ Trail Incr: Adapts the trailing stop loss price based on the offset percentage (SLT%).
- Each price change in favor of your position will incrementally adapt the trailing stop loss with SLT%.
• SLT% - Stop Loss Trailing Percentage: This percentage serves as an offset or increment depending on your chosen trailing mode.
█ EXIT TAKE PROFIT
Determine the Take Profit price based on your selected configuration.
• TPB - Take Profit Base: Choose a take profit mode for calculating take profit prices.
○ Reward: Determines the take profit price using the Risk parameter (RISK%) and the calculated Stop Loss price and the set reward percentage (TPB%).
- For example: Risk 1%, Calculated Stop loss price: $90, Entry price: $100, Reward (TPB%): 2%, will result in a take profit price on $120.
○ Price Entry + Offset: Calculates the take profit price based on a offset percentage (TPB%) from the entry price of the position.
- For example: Entry price: $100, Offset (TPB%): 2%, will result in a take profit price on $102.
• TPB% - Take Profit Base Percentage: Define an offset percentage that will be applied in the price entry + offset take profit mode.
• TPT - Take Profit Trailing:
○ Fixed: The initial take profit will be kept and no trailing take profit will be applied.
○ Trail Price: Computes the trailing take profit price based on an offset percentage (TPT%) from the closing price of the current candle.
- If an applicable take profit price is calculated, it will be set as the new take profit price.
○ Trail Incr: Adapts the trailing take profit price based on the offset percentage (TPT%). Each price change against your position will incrementally adapt the trailing take profit with TPT%.
• TPT% - Take Profit Trailing Percentage: This percentage serves as an offset or increment depending on your chosen trailing mode.
█ STRATEGY CONDITIONS
Specify when the strategy is permitted to execute trades.
• DATE: Enable the Date Range filter to restrict entries to a specific date range.
○ START: Set a start date and hour to commence trading.
○ END: Set an end date and hour to conclude trading within the defined range.
■ VISUALS
• LINE: Activate a colored dashed diagonal line to visually connect the entry and exit points of positions.
• SLTP: Enable visualization of stop loss, take profit, and break-even levels.
• PNL: Enable Break-Even and Close Lines along with a colored area in between to visualize profit and loss.
• ☼: Brightness % : Adjust the opacity of the plotted trading visuals.
• P - Profit Color : Choose the color for profit-related elements.
• L - Loss Color: Choose the color for loss-related elements.
• B - Breakeven Color : Select the color for break-even points.
• EL - Long Color: Specify the color for long positions.
• ES - Short Color: Specify the color for short positions.
• TRADE LABELING: For better analysis we've labeled all entries and exits conform with the type of order your strategy has executed, some examples:
○ XL-TP-150: Exit Long - Take Profit - Position 150
○ XS-TP-154: Exit Short - Take Profit - Position 154
○ XL-SL-160: Exit Long - Stop Loss - Position 160
○ XS-SL-164: Exit Short - Stop Loss - Position 164
█ USAGE OF CONNECTABLE INDICATORS
■ Connectable chaining mechanism
Connectable indicators can be connected directly to the signal monitor, signal filter or strategy , or they can be daisy chained to each other while the last indicator in the chain connects to the signal monitor, signal filter or strategy. When using a signal filter you can chain the filter to the strategy input to make your chain complete.
• Direct chaining: Connect an indicator directly to the signal monitor, signal filter or strategy through the provided inputs (→).
• Daisy chaining: Connect indicators using the indicator input (→). The first in a daisy chain should have a flow (⌥) set to 'Indicator only'. Subsequent indicators use 'Both' to pass the previous weight. The final indicator connects to the signal monitor, signal filter, or strategy.
■ Set up the strategy with a signal filter and an RSI indicator
Let's connect the Strategy to a connectable signal filter and a connectable RSI indicator :
1. Load all relevant indicators
• Load RSI / Connectable
• Load Signal filter / Connectable
• Load Strategy / Connectable
2. Signal Filter: Connect the RSI to the Signal Filter
• Open the signal filter settings
• Choose one of the three input dropdowns (1→, 2→, 3→) and choose : RSI / Connectable: Signal Connector
• Toggle the enable box before the connected input to enable the incoming signal
3. Signal Filter: Update the filter signals settings if needed
• The default settings of the filter enable EL (Enter Long), XL (Exit Long), ES (Enter Short) and XS (Exit Short).
4. Signal Filter: Update the weight threshold settings if needed
• All connectable indicators load by default with a score of 6 for each direction (EL, XL, ES, XS)
• By default, weight threshold (TH) is set at 5. This allows each occurrence to score, as the default score in each connectable indicator is 1 point above the threshold. Adjust to your liking.
5. Strategy: Connect the strategy to the signal filter in the strategy settings
• Select the strategy input → and select the Signal filter: Signal connector
6. Strategy: Enable filter compatible directions
• Set the signal mode of the strategy to a compatible direction with the signal filter.
Now that everything is connected, you'll notice green spikes in the signal filter representing long signals, and red spikes indicating short signals. Trades will also appear on the chart, complemented by a performance overview. Your journey is just beginning: delve into different scoring mechanisms, merge diverse connectable indicators, and craft unique chains. Instantly test your results and discover the potential of your configurations. Dive deep and enjoy the process!
█ BENEFITS
• Adaptable Modular Design: Arrange indicators in diverse structures via direct or daisy chaining, allowing tailored configurations to align with your analysis approach.
• Streamlined Backtesting: Simplify the iterative process of testing and adjusting combinations, facilitating a smoother exploration of potential setups.
• Intuitive Interface: Navigate TradingView with added ease. Integrate desired indicators, adjust settings, and establish alerts without delving into complex code.
• Signal Weight Precision: Leverage granular weight allocation among signals, offering a deeper layer of customization in strategy formulation.
• Advanced Signal Filtering: Define entry and exit conditions with more clarity, granting an added layer of strategy precision.
• Clear Visual Feedback: Distinct visual signals and cues enhance the readability of charts, promoting informed decision-making.
• Standardized Defaults: Indicators are equipped with universally recognized preset settings, ensuring consistency in initial setups across different types like momentum or volatility.
• Reliability: Our indicators are meticulously developed to prevent repainting. We strictly adhere to TradingView's coding conventions, ensuring our code is both performant and clean.
█ COMPATIBLE INDICATORS
Each indicator that incorporates our open-source 'azLibConnector' library and adheres to our conventions can be effortlessly integrated and used as detailed above.
For clarity and recognition within the TradingView platform, we append the suffix ' / Connectable' to every compatible indicator.
█ COMMON MISTAKES AND CLARIFICATIONS
• Removing an indicator from a chain: Deleting a linked indicator and confirming the "remove study tree" alert will also remove all underlying indicators in the object tree. Before removing one, disconnect the adjacent indicators and move it to the object stack's bottom.
• Point systems: The azLibConnector provides 500 points for each direction (EL: Enter long, XL: Exit long, ES: Enter short, XS: Exit short) Remember this cap when devising a point structure.
• Flow misconfiguration: In daisy chains the first indicator should always have a flow (⌥) setting of 'indicator only' while other indicator should have a flow (⌥) setting of 'both'.
• Recalculate: While this strategy has undergone extensive testing, enabling recalculation options like 'After order is filled' or 'On every tick' may lead to unexpected behavior.
• Fill orders: The strategy is thoroughly tested, yet enabling fill order options such as 'Using bar magnifier', 'On bar close', or 'Using standard OHLC' might result in unexpected outcomes.
• Layout and abbreviations: To maintain a consistent structure, we use abbreviations for each input. While this may initially seem complex, you'll quickly become familiar with them. Each abbreviation is also explained in the inline tooltips.
• Optimized for crypto trading: While many principles are common across markets, this strategy is specifically optimized and tested for crypto trading.
• Inputs: Connecting a connectable indicator directly to the strategy delivers the raw signal without a weight threshold, meaning every signal will trigger a trade.
█ A NOTE OF GRATITUDE
Through years of exploring TradingView and Pine Script, we've drawn immense inspiration from the community's knowledge and innovation. Thank you for being a constant source of motivation and insight.
█ RISK DISCLAIMER
Azullian's content, tools, scripts, articles, and educational offerings are presented purely for educational and informational uses. Please be aware that past performance should not be considered a predictor of future results.
Bitcoin Leverage Sentiment - Strategy [presentTrading]█ Introduction and How it is Different
The "Bitcoin Leverage Sentiment - Strategy " represents a novel approach in the realm of cryptocurrency trading by focusing on sentiment analysis through leveraged positions in Bitcoin. Unlike traditional strategies that primarily rely on price action or technical indicators, this strategy leverages the power of Z-Score analysis to gauge market sentiment by examining the ratio of leveraged long to short positions. By assessing how far the current sentiment deviates from the historical norm, it provides a unique lens to spot potential reversals or continuation in market trends, making it an innovative tool for traders who wish to incorporate market psychology into their trading arsenal.
BTC 4h L/S Performance
local
█ Strategy, How It Works: Detailed Explanation
🔶 Data Collection and Ratio Calculation
Firstly, the strategy acquires data on leveraged long (**`priceLongs`**) and short positions (**`priceShorts`**) for Bitcoin. The primary metric of interest is the ratio of long positions relative to the total of both long and short positions:
BTC Ratio=priceLongs / (priceLongs+priceShorts)
This ratio reflects the prevailing market sentiment, where values closer to 1 indicate a bullish sentiment (dominance of long positions), and values closer to 0 suggest bearish sentiment (prevalence of short positions).
🔶 Z-Score Calculation
The Z-Score is then calculated to standardize the BTC Ratio, allowing for comparison across different time periods. The Z-Score formula is:
Z = (X - μ) / σ
Where:
- X is the current BTC Ratio.
- μ is the mean of the BTC Ratio over a specified period (**`zScoreCalculationPeriod`**).
- σ is the standard deviation of the BTC Ratio over the same period.
The Z-Score helps quantify how far the current sentiment deviates from the historical norm, with high positive values indicating extreme bullish sentiment and high negative values signaling extreme bearish sentiment.
🔶 Signal Generation: Trading signals are derived from the Z-Score as follows:
Long Entry Signal: Occurs when the BTC Ratio Z-Score crosses above the thresholdLongEntry, suggesting bullish sentiment.
- Condition for Long Entry = BTC Ratio Z-Score > thresholdLongEntry
Long Exit/Short Entry Signal: Triggered when the BTC Ratio Z-Score drops below thresholdLongExit for exiting longs or below thresholdShortEntry for entering shorts, indicating a shift to bearish sentiment.
- Condition for Long Exit/Short Entry = BTC Ratio Z-Score < thresholdLongExit or BTC Ratio Z-Score < thresholdShortEntry
Short Exit Signal: Happens when the BTC Ratio Z-Score exceeds the thresholdShortExit, hinting at reducing bearish sentiment and a potential switch to bullish conditions.
- Condition for Short Exit = BTC Ratio Z-Score > thresholdShortExit
🔶Implementation and Visualization: The strategy applies these conditions for trade management, aligning with the selected trade direction. It visualizes the BTC Ratio Z-Score with horizontal lines at entry and exit thresholds, illustrating the current sentiment against historical norms.
█ Trade Direction
The strategy offers flexibility in trade direction, allowing users to choose between long, short, or both, depending on their market outlook and risk tolerance. This adaptability ensures that traders can align the strategy with their individual trading style and market conditions.
█ Usage
To employ this strategy effectively:
1. Customization: Begin by setting the trade direction and adjusting the Z-Score calculation period and entry/exit thresholds to match your trading preferences.
2. Observation: Monitor the Z-Score and its moving average for potential trading signals. Look for crossover events relative to the predefined thresholds to identify entry and exit points.
3. Confirmation: Consider using additional analysis or indicators for signal confirmation, ensuring a comprehensive approach to decision-making.
█ Default Settings
- Trade Direction: Determines if the strategy engages in long, short, or both types of trades, impacting its adaptability to market conditions.
- Timeframe Input: Influences signal frequency and sensitivity, affecting the strategy's responsiveness to market dynamics.
- Z-Score Calculation Period: Affects the strategy’s sensitivity to market changes, with longer periods smoothing data and shorter periods increasing responsiveness.
- Entry and Exit Thresholds: Set the Z-Score levels for initiating or exiting trades, balancing between capturing opportunities and minimizing false signals.
- Impact of Default Settings: Provides a balanced approach to leverage sentiment trading, with adjustments needed to optimize performance across various market conditions.
Crypto Punk [Bot] (Zeiierman)█ Overview
The Crypto Punk (Zeiierman) is a trading strategy designed for the dynamic and volatile cryptocurrency market. It utilizes algorithms that incorporate price action analysis and principles inspired by Geometric Brownian Motion (GBM). The bot's core functionality revolves around analyzing differences in high and low prices over various timeframes, estimating drift (trend) and volatility, and applying this information to generate trading signals.
█ How to use the Crypto Punk Bot
Utilize the Crypto Punk Bot as a technical analysis tool to enhance your trading strategy. The signals generated by the bot can serve as a confirmation of your existing approach to entering and exiting the market. Additionally, the backtest report provided by the bot is a valuable resource for identifying the optimal settings for the specific market and timeframe you are trading in.
One method is to use the bot's signals to confirm entry points around key support and resistance levels.
█ Key Features
Let's explain how the core features work in the strategy.
⚪ Strategy Filter
The strategy filter plays a vital role in the entries and exits. By setting this filter, the bot can identify higher or lower price points at which to execute trades. Opting for higher values will make the bot target more long-term extreme points, resulting in fewer but potentially more significant signals. Conversely, lower values focus on short-term extreme points, offering more frequent signals focusing on immediate market movements.
How is it calculated?
This filter identifies significant price points within a specified dynamic range by applying linear regression to the absolute deviation of the range, smoothing out fluctuations, and determining the trend direction. The algorithm then normalizes the data and searches for extreme points.
⚪ External AI filter
The external AI filter allows traders to incorporate two external sources as signal filters. This feature is particularly useful for refining their signal accuracy with additional data inputs.
External sources can include any indicator applied to your TradingView chart that produces a plot as an output, such as a moving average, RSI, supertrend, MACD, etc. Traders can use these indicators of their choice to set filters for screening signals within the strategy.
This approach offers traders increased flexibility to select filters that align with their trading style. For instance, one trader might prefer to take trades when the price is above a moving average, while another might opt for trades when the MACD is below the MACD signal line. These external filters enable traders to choose options that best fit their trading strategies. See the example below. Note that the input sources for the External AI filter can be any indicator applied to the chart, and the input source per se does not make this strategy unique. The AI filter takes the selected input source and applies our function to it. So, if a trader selects RSI as an input filter, RSI is not unique, but how the source is computed within the AI functions is.
How is it calculated?
Once the external filters are selected and enabled within the settings panel, our AI function is applied to enhance the filter's ability to execute trades, even when the set conditions of the filter are not met. For instance, if a trader wants to take trades only when the price is above a moving average, the AI filter can actually execute trades even if the price is below the moving average.
The filter works by combining k-nearest Neighbors (KNN) with Geometric Brownian Motion (GBM) involves first using GBM to model the historical price trends of an asset, identifying patterns of drift and volatility. KNN is then applied to compare the current market conditions with historical instances, identifying the closest matches based on similar market behaviors. By examining the drift values of these nearest historical neighbors, KNN predicts the current trend's direction.
The AI adaptability value is a setting that determines how flexible the AI algorithm is when applying the external AI filter. Setting the adaptability to 10 indicates minimal adaptability, suggesting that the bot will strictly adhere to the set filter criteria. On the other hand, a higher adaptability value grants the algorithm more leeway to "think outside the box," allowing it to consider signals that may not strictly meet the filter criteria but are deemed viable trading opportunities by the AI.
█ Examples
In this example, the RSI is used to filter out signals when the RSI is below the smoothing line, indicating that prices are declining.
Note that the external filter is specifically designed to work with either 'LONG ONLY' or 'SHORT ONLY' modes; it does not apply when the bot is set to trade on 'BOTH' modes. For 'LONG ONLY' positions, the filter criteria are met when source 1 is greater than source 2 (source 1 >= source 2). Conversely, for 'SHORT ONLY' positions, the filter criteria require source 1 to be less than source 2 (source 1 <= source 2).
Examples of Filter Usage:
Long Signals: To receive long signals when the closing price is higher than a moving average, set Source 1 to the 'close' price and Source 2 to a moving average value. This setup ensures that signals are generated only when the closing price exceeds the moving average, indicating a potential upward trend.
█ Settings
⚪ Set Timeframe
Choosing the correct entry and exit timeframes is crucial for the bot's performance. The general guideline is to select a timeframe that is higher than the one currently displayed on the trading chart but still relatively close in duration. For instance, if trading on a 1-minute chart, setting the bot's Timeframe to 5 minutes is advisable.
⚪ Entry
Traders have the flexibility to configure the bot according to their trading strategy, allowing them to choose whether the bot should engage in long positions only, short positions only or both. This customization ensures that the bot aligns with the trader's market outlook and risk tolerance.
⚪ Pyramiding
Pyramiding functionality is available to enhance the bot's trading strategy. If the current position experiences a drawdown by a specified number of points, the bot is programmed to add new positions to the existing one, potentially capitalizing on lower prices to average down the entry cost. To utilize this feature, access the settings panel, navigate to 'Properties,' and look for 'Pyramiding' to specify the number of times the bot can re-enter the market (e.g., setting it to 2 allows for two additional entries).
⚪ Risk Management
The bot incorporates several risk management methods, including a regular stop loss, trailing stop, and risk-reward-based stop loss and exit strategies. These features assist traders in managing their risk.
Stop Loss
Trailing Stop
⚪ Trading on specific days
This feature allows trading on specific days by setting which days of the week the bot can execute trades on. It enables traders to tailor their strategies according to market behavior on particular days.
⚪ Alerts
Alerts can be set for entry, exit, and risk management. This feature allows traders to automate their trading strategy, ensuring timely actions are taken according to predefined criteria.
█ How is Crypto Punk calculated?
The Crypto Punk Bot is a trading bot that utilizes a combination of price action analysis and elements inspired by Geometric Brownian Motion (GBM) to generate buy and sell signals for cryptocurrencies. The bot focuses on analyzing the difference between high and low prices over various timeframes, alongside estimates of drift (trend) and volatility derived from GBM principles.
Timeframe Analysis for Price Action
The bot examines multiple timeframes (e.g., daily, weekly) to identify the range between the highest and lowest prices within each period. This range analysis helps in understanding market volatility and the potential for significant price movements. The algorithm calculates the trading range by applying maximum and minimum functions to the set of prices over your selected timeframe. It then subtracts these values to determine the range's width. This method offers a quantitative measure of the asset's price volatility for the specified period.
Estimating Drift (Trend)
The bot estimates the drift component, which reflects the underlying trend or expected return of the cryptocurrency. The algorithm does this by estimating the drift (trend) using Geometric Brownian Motion (GBM), which involves determining an asset's average rate of return over time, reflecting the asset's expected direction of movement.
Estimating Volatility
Volatility is estimated by calculating the standard deviation of the logarithmic returns of the cryptocurrency's price over the same timeframe used for the drift calculation. Geometric Brownian Motion (GBM) involves measuring the extent of variation or dispersion in the returns of an asset over time. In the context of GBM, volatility quantifies the degree to which the price of an asset is expected to fluctuate around its drift.
Combining Drift and Volatility for Signal Generation
The bot uses the calculated drift and volatility to understand the current market conditions. A higher drift coupled with manageable volatility may indicate a strong upward trend, suggesting a potential buy signal. Conversely, a low or negative drift with increasing volatility might suggest a weakening market, triggering a sell signal.
█ Strategy Properties
This script backtest is done on the 1 hour chart Bitcoin, using the following backtesting properties:
Balance (default): 10 000 (default base currency)
Order Size: 10% of the equity
Commission: 0.05 %
Slippage: 500 ticks
Stop Loss: Risk Reward set to 1
These parameters are set to provide an accurate representation of the backtesting environment. It's important to recognize that default settings may vary for several reasons outlined below:
Order Size: The standard is set at one contract to facilitate compatibility with a wide range of instruments, including futures.
Commission: This fee is subject to fluctuation based on the specific market and financial instrument, and as such, there isn't a standard rate that will consistently yield accurate outcomes.
We advise users to customize the Script Properties in the strategy settings to match their personal trading accounts and preferred platforms. This adjustment is crucial for obtaining practical insights from the deployed strategies.
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
BigBeluga - BacktestingThe Backtesting System (SMC) is a strategy builder designed around concepts of Smart Money.
What makes this indicator unique is that users can build a wide variety of strategies thanks to the external source conditions and the built-in one that are coded around concepts of smart money.
🔶 FEATURES
🔹 Step Algorithm
Crafting Your Strategy:
You can add multiple steps to your strategy, using both internal and external (custom) conditions.
Evaluating Your Conditions:
The system evaluates your conditions sequentially.
Only after the previous step becomes true will the next one be evaluated.
This ensures your strategy only triggers when all specified conditions are met.
Executing Your Strategy:
Once all steps in your strategy are true, the backtester automatically opens a market order.
You can also configure exit conditions within the strategy builder to manage your positions effectively.
🔹 External and Internal build-in conditions
Users can choose to use external or internal conditions or just one of the two categories.
Build-in conditions:
CHoCH or BOS
CHoCH or BOS Sweep
CHoCH
BOS
CHoCH Sweep
BOS Sweep
OB Mitigated
Price Inside OB
FVG Mitigated
Raid Found
Price Inside FVG
SFP Created
Liquidity Print
Sweep Area
Breakdown of each of the options:
CHoCH: Change of Character (not Charter) is a change from bullish to bearish market or vice versa.
BOS: Break of Structure is a continuation of the current trend.
CHoCH or BOS Sweep: Liquidity taken out from the market within the structure.
OB Mitigated: An order block mitigated.
FVG Mitigated: An imbalance mitigated.
Raid Found: Liquidity taken out from an imbalance.
SFP Created: A Swing Failure Pattern detected.
Liquidity Print: A huge chunk of liquidity taken out from the market.
Sweep Area: A level regained from the structure.
Price inside OB/FVG: Price inside an order block or an imbalance.
External inputs can be anything that is plotted on the chart that has valid entry points, such as an RSI or a simple Supertrend.
Equal
Greather Than
Less Than
Crossing Over
Crossing Under
Crossing
🔹 Direction
Users can change the direction of each condition to either Bullish or Bearish. This can be useful if users want to long the market on a bearish condition or vice versa.
🔹 Build-in Stop-Loss and Take-Profit features
Tailoring Your Exits:
Similar to entry creation, the backtesting system allows you to build multi-step exit strategies.
Each step can utilize internal and external (custom) conditions.
This flexibility allows you to personalize your exit strategy based on your risk tolerance and trading goals.
Stop-Loss and Take-Profit Options:
The backtesting system offers various options for setting stop-loss and take-profit levels.
You can choose from:
Dynamic levels: These levels automatically adjust based on market movements, helping you manage risk and secure profits.
Specific price levels: You can set fixed stop-loss and take-profit levels based on your comfort level and analysis.
Price - Set x point to a specific price
Currency - Set x point away from tot Currency points
Ticks - Set x point away from tot ticks
Percent - Set x point away from a fixed %
ATR - Set x point away using the Averge True Range (200 bars)
Trailing Stop (Only for stop-loss order)
🔶 USAGE
Users can create a variety of strategies using this script, limited only by their imagination.
Long entry : Bullish CHoCH after price is inside a bullish order block
Short entry : Bearish CHoCH after price is inside a bearish order block
Stop-Loss : Trailing Stop set away from price by 0.2%
Example below using external conditions
Long entry : Bullish Liquidity Prints after bullish CHoCH
Short entry : Bearish Liquidity Prints after Bearish CHoCH
Long Exit : RSI Crossing over 70 line
Short Exit : RSI Crossing over 30 line
Stop-Loss : Trailing Stop set away from price by 0.3%
🔶 PROPERTIES
Users will need to adjust the property tabs according to their individual balance to achieve realistic results.
An important aspect to note is that past performance does not guarantee future results. This principle should always be kept in mind.
🔶 HOW TO ACCESS
You can see the Author Instructions to get access.
arpit bollinger bandStrategy Overview:
This strategy utilizes Bollinger Bands based on a 20-period Exponential Moving Average (EMA) with a standard deviation multiplier of 1.5. It is designed to generate early trading signals based on the relationship between the price action and the Bollinger Bands.
Bollinger Bands Calculation:
The upper Bollinger Band is calculated as the 20-period EMA of the closing prices plus 1.5 times the standard deviation of the same period.
The lower Bollinger Band is calculated as the 20-period EMA of the closing prices minus 1.5 times the standard deviation.
Entry Criteria:
Buy Signal: A buy signal is generated when the current candle's high exceeds the high of the candle two periods ago, which had closed below the lower Bollinger Band. This condition implies an anticipation of a bullish reversal.
Sell Signal: A sell signal is generated when the current candle's low falls below the low of the candle two periods ago, which had closed above the upper Bollinger Band. This condition suggests an anticipated bearish reversal.
Stop Loss and Take Profit:
The stop loss for a buy order is set slightly below the low of the current candle, and for a sell order, it is set slightly above the high of the current candle.
The take profit level is determined based on a predefined risk-reward ratio of 1:3. This means the take profit target is set at a distance three times greater than the distance between the entry price and the stop loss.
Risk Management:
The strategy includes an input option to adjust the risk-reward ratio, allowing for flexibility in managing the trade's potential risk versus reward.
Trade Execution:
The strategy automatically plots the buy and sell signals on the chart and executes the trades according to the defined conditions. It also visually indicates the stop loss levels for each trade.
Usage Notes:
This strategy is designed for use in the TradingView platform using Pine Script version 5.
It is important to backtest and paper trade the strategy before using it in live trading to understand its performance characteristics and risk profile.
The strategy should be used as part of a comprehensive trading plan, considering market conditions, trader risk tolerance, and personal trading goals.
Turtle Trading Strategy@lihexieThe full implementation of the Turtle Trading Rules (as distinct from the various truncated versions circulating within the community) is now ready.
This trading strategy script distinguishes itself from all currently publicly available Turtle trading systems on Tradingview by comprehensively embodying the rules for entries, exits, position management, and profit and loss controls.
Market Selection:
Trade in highly liquid markets such as forex, commodity futures, and stock index futures.
Entry Strategies:
Model 1: Buy when the price breaks above the highest point of the last 20 trading days; Sell when the price drops below the lowest point of the last 20 trading days. When an entry opportunity arises, if the previous trade was profitable, skip the current breakout opportunity and refrain from entering.
Model 2: Buy when the price breaks above the highest point of the last 55 trading days; Sell when the price drops below the lowest point of the last 55 trading days.
Position Sizing:
Determine the size of each position based on the price volatility (ATR) to ensure that the risk of each trade does not exceed 2% of the account balance.
Exit Strategies:
1. Use a fixed stop-loss point to limit losses: Close long positions when the price falls below the lowest point of the last 10 trading days.
2. Trailing stop-loss: Once a position is profitable, adjust the stop-loss point to protect profits.
Pyramiding Rules:
Unit Doubling: Increase position size by one unit every time the price moves forward by n (default is 0.5) units of ATR, up to a maximum of 4 units, while also raising the stop-loss point to below the ATR value at the level of additional entries.
海龟交易法则的完整实现（区别于当前社区各种有阉割海龟交易系统代码）
本策略脚本区别于Tradingview目前公开的所有的海龟交易系统，完整的实现了海龟交易法则中入场、出场、仓位管理，止盈止损的规则。
市场选择：
选择流动性高的市场进行交易，如外汇、商品期货和股指期货等。
入市策略：
模式1：当价格突破过去20个交易日的高点时，买入；当价格跌破过去20个交易日的低点时，卖出。当出现入场机会时，如果上一笔交易是盈利的，那么跳过当前突破的机会，不进行入场。
模式2：当价格突破过去55个交易日的高点时，买入；当价格跌破过去55个交易日的低点时，卖出。
头寸规模：
根据价格波动性（ATR）来确定每个头寸的大小, 使每笔交易的风险不超过账户余额的2%。
退出策略：
1. 使用一个固定的止损点来限制损失：当多头头寸的价格跌破过去10个交易日的低点时，平仓止损。
2. 跟踪止损：一旦头寸盈利，移动止损点以保护利润。
加仓规则：
单位加倍：每当价格向前n（默认是0.5）个单位的ATR移动时，就增加一个单位的头寸大小（默认最大头寸数量是4个），同时将止损点提升至加仓点位的ATR值以下。
[strategy][1H] SPY slow stochastics
SPY slow stochastics
Overview
The "SPY Auto RSI Stochastics" strategy is designed to leverage a combination of Relative Strength Index (RSI) and Stochastic indicators to identify potential entry and exit points in trading the SPY $SP:SPX.
The technicals:
A simple yet effective strategy for identifying (reversal) trends on SPY (or any asset).
The logic is as follows:
1. Slow stochastics are effective at predicting momentum. They can also be used to effectively identify reversals.
2. A combination of slow and fast RSI (along with an SMA for the fast RSI) can be used to see potential changes in the directional trend of the underlying asset.
3. In order to reduce noise, a band in the middle of RSI values is ignored; think of this as the price converging and potential explosions (sometimes fake) on either side.
4. Outside this noise band, a crossover of fast RSI on slow RSI indicates an upward trend incoming.
5. A crossunder of fast RSI on slow RSI indicates a downward trend incoming.
Strategy Specific Notes -
1. Load this strategy on SPREADEX:SPX on an hourly chart for the best results.
2. This is a generic strategy, use it on anything - index, stocks, etc. You will need to adjust the parameters for the best results.
3. The RSI Upper defines the cutoff for two things -- threshold for entering a long AND exit signal for short. Likewise for RSI Lower.
4. To have alerts on the strategy, add this to your chart, be content with the backtesting results, select "strategy tester", the alert icon, replace the message body with "{{strategy.order.alert_message}}" without the ".
5. In my experience, the strategy won't be immediately profitable upon a signal but it does get there in the backtested results. Intuitively, this makes sense. Reversals take some time to kick in completely.
Inputs
- **slowRSILength**: Length parameter for the slow RSI calculation.
- **fastRSILength**: Length parameter for the fast RSI calculation.
- **smaRSILength**: Length parameter for the Simple Moving Average (SMA) of the fast RSI.
- **RSIUpperThreshold**: Upper threshold for the RSI, used in exit conditions.
- **RSILowerThreshold**: Lower threshold for the RSI, used in exit conditions.
- **RSIUpperDeadzone**: Upper deadzone threshold for the RSI.
- **RSILowerDeadzone**: Lower deadzone threshold for the RSI.
Strategy Logic
- **RSI Calculation**: The script calculates both slow and fast RSI values based on the provided lengths.
- **Entry Condition**: Entry conditions for long and short positions are based on the crossing of fast RSI over slow RSI and SMA RSI, respectively, along with avoidance of RSI deadzones and validation of trade time.
- **Exit Condition**: Exit conditions for both long and short positions are based on crossing RSI thresholds or opposite entry conditions.
Trade Management
- **Position Entry**: Long and short positions are entered based on predefined entry conditions.
- **Position Exit**: Positions are exited based on predefined exit conditions.
- **Alerts**: The script provides alert messages for entry and exit points.
Plotting
- **Slow RSI**: Plots the slow RSI on the chart.
- **SMA RSI**: Plots the Simple Moving Average of fast RSI on the chart.
Example Usage
The defaults work well for SPY on a 1H timeframe.
If you apply this to anything else DAX, EUSTX50, FTSE, CAC (these are what i have); tweak the input parameters.
Plotting
plot(slowRSI, "Slow RSI", color=color.green) //or fastRSI
plot(smaRSI, "SMA RSI", color=color.white)
Conclusion
The "SPY Auto RSI Stochastics" strategy combines RSI and Stochastic indicators to provide potential trade signals for the SPY ETF. Traders can use this strategy with proper risk management and analysis to enhance their trading decisions.
TTP Intelligent AccumulatorThe intelligent accumulator is a proof of concept strategy. A hybrid between a recurring buy and TA-based entries and exits.
Distribute the amount of equity and add to your position as long as the TA condition is valid.
Use the exit TA condition to define your exit strategy.
Decide between adding only into losing positions to average down or take a riskier approach by allowing to add into a winning position as well.
Take full profit or distribute your exit into multiple take profit exists of the same size.
You can also decide if you allow your exit conditions to close your position in a loss or require a minimum take profit %.
The strategy includes a default built-in TA conditions just for showcasing the idea but the final intent of this script is to delegate the TA entries and exists to external sources.
The internal conditions use RSI length 7 crossing below the BB with std 1 for entries and above for exits.
To control the number of orders use the properties from settings:
- adjust the pyramiding
- adjust the percentage of equity
- make sure that pyramiding * % equity equals 100 to prevent over use of equity (unless using leverage)
The script is designed as an alternative to daily or weekly recurring buys but depending on the accuracy of your TA conditions it might prove profitable also in lower timeframes.
The reason the script is named Intelligent is because recurring buy is most commonly used without any decision making: buy no matter what with certain frequency. This strategy seeks to still perform recurring buys but filtering out some of the potential bad entries that can delay unnecessarily seeing the position in profits. The second reason is also securing an exit strategy from the beginning which no recurring buy option offers out-of-the-box.
Long EMA Strategy with Advanced Exit OptionsThis strategy is designed for traders seeking a trend-following system with a focus on precision and adaptability.
**Core Strategy Concept**
The essence of this strategy lies in use of Exponential Moving Averages (EMAs) to identify potential long (buy) positions based on the relative positions of short-term, medium-term, and long-term EMAs. The use of EMAs is a classic yet powerful approach to trend detection, as these indicators smooth out price data over time, emphasizing the direction of recent price movements and potentially signaling the beginning of new trends.
**Customizable Parameters**
- **EMA Periods**: Users can define the periods for three EMAs - long-term, medium-term, and short-term - allowing for a tailored approach to capture trends based on individual trading styles and market conditions.
- **Volatility Filter**: An optional Average True Range (ATR)-based volatility filter can be toggled on or off. When activated, it ensures that trades are only entered when market volatility exceeds a user-defined threshold, aiming to filter out entries during low-volatility periods which are often characterized by indecisive market movements.
- **Trailing Stop Loss**: A trailing stop loss mechanism, expressed as a percentage of the highest price achieved since entry, provides a dynamic way to manage risk by allowing profits to run while cutting losses.
- **EMA Exit Condition**: This advanced exit option enables closing positions when the short-term EMA crosses below the medium-term EMA, serving as a signal that the immediate trend may be reversing.
- **Close Below EMA Exit**: An additional exit condition, which is disabled by default, allows positions to be closed if the price closes below a user-selected EMA. This provides an extra layer of flexibility and risk management, catering to traders who prefer to exit positions based on specific EMA thresholds.
**Operational Mechanics**
Upon activation, the strategy evaluates the current price in relation to the set EMAs. A long position is considered when the current price is above the long-term EMA, and the short-term EMA is above the medium-term EMA. This setup aims to identify moments where the price momentum is strong and likely to continue.
The strategy's versatility is further enhanced by its optional settings:
- The **Volatility Filter** adjusts the sensitivity of the strategy to market movements, potentially improving the quality of the entries during volatile market conditions.
The Average True Range (ATR) is a key component of this filter, providing a measure of market volatility by calculating the average range between the high and low prices over a specified number of periods. Here's how you can adjust the volatility filter settings for various market conditions, focusing on filtering out low-volatility markets:
Setting Examples for Volatility Filter
1. High Volatility Markets (e.g., Cryptocurrencies, Certain Forex Pairs):
ATR Periods: 14 (default)
ATR Multiplier: Setting the multiplier to a lower value, such as 1.0 or 1.2, can be beneficial in high-volatility markets. This sensitivity allows the strategy to react to volatility changes more quickly, ensuring that you're entering trades during periods of significant movement.
2. Medium Volatility Markets (e.g., Major Equity Indices, Medium-Volatility Forex Pairs):
ATR Periods: 14 (default)
ATR Multiplier: A multiplier of 1.5 (default) is often suitable for medium volatility markets. It provides a balanced approach, ensuring that the strategy filters out low-volatility conditions without being overly restrictive.
3. Low Volatility Markets (e.g., Some Commodities, Low-Volatility Forex Pairs):
ATR Periods: Increasing the ATR period to 20 or 25 can smooth out the volatility measure, making it less sensitive to short-term fluctuations. This adjustment helps in focusing on more significant trends in inherently stable markets.
ATR Multiplier: Raising the multiplier to 2.0 or even 2.5 increases the threshold for volatility, effectively filtering out low-volatility conditions. This setting ensures that the strategy only triggers trades during periods of relatively higher volatility, which are more likely to result in significant price movements.
How to Use the Volatility Filter for Low-Volatility Markets
For traders specifically interested in filtering out low-volatility markets, the key is to adjust the ATR Multiplier to a higher level. This adjustment increases the threshold required for the market to be considered sufficiently volatile for trade entries. Here's a step-by-step guide:
Adjust the ATR Multiplier: Increase the ATR Multiplier to create a higher volatility threshold. A multiplier of 2.0 to 2.5 is a good starting point for very low-volatility markets.
Fine-Tune the ATR Periods: Consider lengthening the ATR calculation period if you find that the strategy is still entering trades in undesirable low-volatility conditions. A longer period provides a more averaged-out measure of volatility, which might better suit your needs.
Monitor and Adjust: Volatility is not static, and market conditions can change. Regularly review the performance of your strategy in the context of current market volatility and adjust the settings as necessary.
Backtest in Different Conditions: Before applying the strategy live, backtest it across different market conditions with your adjusted settings. This process helps ensure that your approach to filtering low-volatility conditions aligns with your trading objectives and risk tolerance.
By fine-tuning the volatility filter settings according to the specific characteristics of the market you're trading in, you can enhance the performance of this strategy
- The **Trailing Stop Loss** and **EMA Exit Conditions** provide two layers of exit strategies, focusing on capital preservation and profit maximization.
**Visualizations**
For clarity and ease of use, the strategy plots the three EMAs and, if enabled, the ATR threshold on the chart. These visual cues not only aid in decision-making but also help in understanding the market's current trend and volatility state.
**How to Use**
Traders can customize the EMA periods to fit their trading horizon, be it short, medium, or long-term trading. The volatility filter and exit options allow for further customization, making the strategy adaptable to different market conditions and personal risk tolerance levels.
By offering a blend of trend-following principles with advanced risk management features, this strategy aims to cater to a wide range of trading styles, from cautious to aggressive. Its strength lies in its flexibility, allowing traders to fine-tune settings to their specific needs, making it a potentially valuable tool in the arsenal of any trader looking for a disciplined approach to navigating the markets.
Octopus Nest Strategy Hello Fellas,
Hereby, I come up with a popular strategy from YouTube called Octopus Nest Strategy. It is a no repaint, lower timeframe scalping strategy utilizing PSAR, EMA and TTM Squeeze.
The strategy considers these market factors:
PSAR -> Trend
EMA -> Trend
TTM Squeeze -> Momentum and Volatility by incorporating Bollinger Bands and Keltner Channels
Note: As you can see there is a potential improvement by incorporating volume.
What's Different Compared To The Original Strategy?
I added an option which allows users to use the Adaptive PSAR of @loxx, which will hopefully improve results sometimes.
Signals
Enter Long -> source above EMA 100, source crosses above PSAR and TTM Squeeze crosses above 0
Enter Short -> source below EMA 100, source crosses below PSAR and TTM Squeeze crosses below 0
Exit Long and Exit Short are triggered from the risk management. Thus, it will just exit on SL or TP.
Risk Management
"High Low Stop Loss" and "Automatic High Low Take Profit" are used here.
High Low Stop Loss: Utilizes the last high for short and the last low for long to calculate the stop loss level. The last high or low gets multiplied by the user-defined multiplicator and if no recent high or low was found it uses the backup multiplier.
Automatic High Low Take Profit: Utilizes the current stop loss level of "High Low Stop Loss" and gets calculated by the user-defined risk ratio.
Now, follows the bunch of knowledge for the more inexperienced readers.
PSAR: Parabolic Stop And Reverse; Developed by J. Welles Wilders and a classic trend reversal indicator.
The indicator works most effectively in trending markets where large price moves allow traders to capture significant gains. When a security’s price is range-bound, the indicator will constantly be reversing, resulting in multiple low-profit or losing trades.
TTM Squeeze: TTM Squeeze is a volatility and momentum indicator introduced by John Carter of Trade the Markets (now Simpler Trading), which capitalizes on the tendency for price to break out strongly after consolidating in a tight trading range.
The volatility component of the TTM Squeeze indicator measures price compression using Bollinger Bands and Keltner Channels. If the Bollinger Bands are completely enclosed within the Keltner Channels, that indicates a period of very low volatility. This state is known as the squeeze. When the Bollinger Bands expand and move back outside of the Keltner Channel, the squeeze is said to have “fired”: volatility increases and prices are likely to break out of that tight trading range in one direction or the other. The on/off state of the squeeze is shown with small dots on the zero line of the indicator: red dots indicate the squeeze is on, and green dots indicate the squeeze is off.
EMA: Exponential Moving Average; Like a simple moving average, but with exponential weighting of the input data.
Don't forget to check out the settings and keep it up.
Best regards,
simwai
---
Credits to:
@loxx
@Bjorgum
@Greeny
Triple MA HTF strategy - Dynamic SmoothingThe triple MA strategy is a simple but effective method to trade the trend. The advantage of this script over the existing triple MA strategies is that the user can open a lower time frame chart and select higher time frame inputs for different MA types mainting the visibility on the chart. The dynamic smoothing code makes sure the HTF trendlines are not jagged, but a fluid line visiable on the lower time frame chart. The script comes with a MA crossover and crossunder strategy explained below.
Moving Averages (MA) Crossover for Entry:
Long Entry: A long entry signal is triggered when the moving average line 1 crosses above the moving average line 2. This crossover indicates a potential shift in market sentiment towards the upside. However, to validate this signal, the strategy checks if the moving average 3 on a higher time frame (eg. 4 hour) is in an upward trend. This additional filter ensures that the trade aligns with the prevailing trend on a broader time scale, increasing the probability of success.
Short Entry: Conversely, a short entry signal occurs when the moving average line 1 crosses below the moving average line 2. This crossover suggests a possible downturn in market momentum. However, for a short trade to be confirmed, the strategy verifies that the moving average 3 on the higher time frame is in a downward trend. This confirmation ensures that the trade is in harmony with the overarching market direction.
Exit from Long Position: The strategy triggers an exit signal from a long position when the moving average line 1 crosses below the moving average line 2. This crossover indicates a potential reversal in the market trend, prompting the trader to close their long position and take profits or minimize losses.
Exit from Short Position: Similarly, an exit signal from a short position occurs when the moving average line 1 crosses above the moving average line 2. This crossover suggests a potential shift in market sentiment towards the upside, prompting the trader to exit their short position and manage their risk accordingly.
Features of the script
This Triple MA Strategy is basically the HTF Trend Filter displayed 3 times on the chart. For more infomation on how the MA with dynamic smoothing is calculated I recommend reading the following script:
For risk management I included a simple script to opt for % of eauity or # of contracts of in the instrument. For explanation on how the risk management settings work I refer to my ealier published script:
The strategy is a simplified example for setting up an entry and exit logic based on multiple moving avarages. Hence the script is meant for educational purposes only.
CULTURATRADING STRATEGYThe "CULTURATRADING STRATEGY" is designed to capitalize on market trends by incorporating a combination of technical indicators that signal potential entry and exit points for trades on various assets. This strategy is not just a mere collection of indicators but a well-thought-out approach that synergizes different market signals to optimize trade decisions.
The script uses the MACD (Moving Average Convergence Divergence) to gauge momentum and trend direction, with the slope of the MACD line serving as a trigger for market entries. A positive slope suggests an upward trend and potential long entry, while a negative slope indicates a downward trend and a possible short entry.
In tandem with the MACD, the ADX (Average Directional Index) is utilized to measure the strength of the trend. An ADX value above 25 signifies a strong trend, which, when aligned with MACD signals, can validate the trade entries.
The RSI (Relative Strength Index) is another critical component, identifying overbought and oversold conditions. This strategy looks for crossovers above and below key levels (60 for overbought, 40 for oversold) to determine high-probability turning points in the market. The inclusion of a 20-period SMA (Simple Moving Average) of the RSI adds a layer to filter the signals further, allowing for the refinement of entry and exit points.
The script employs a dynamic stop-loss system, set at the lowest low of the past 20 bars for long positions and the highest high for shorts, to manage risk effectively. The strategy is configured for a $10,000 account, risking a reasonable portion of capital per trade, with a pyramid effect to allow for diversified entries from various signals. The backtesting results are based on a 5% capital allocation per trade and include a 0.08% commission. To ensure accurate backtesting, the script includes an additional percentage to account for slippage within the commission.
To provide a comprehensive understanding, the script also outputs a "volatility histogram" based on the ADX, offering insights into market volatility and helping to time the trades better.
This strategy has been backtested across different timeframes and assets, showing resilience in various market conditions. It is essential to check the 'recalculate after order filled' option due to the dynamic nature of stop-loss orders.
This script is paired with the "CULTURATRADING INDICATOR" for enhanced signal clarity, providing a holistic view of the strategy's performance. Please note that this script is for educational purposes and should not be taken as financial advice.
The "CULTURATRADING INDICATOR" is an essential tool that works in conjunction with the "CULTURATRADING STRATEGY" to provide traders with a clear visualization of the market's conditions. It enhances the strategy by offering visual cues that help interpret complex market data more intuitively.
The indicator displays key RSI levels, such as 60 for overbought conditions and 40 for oversold conditions, with a mid-level at 55 to indicate when a trend may be weakening. The colors on the RSI line change to reflect these conditions, offering a quick reference for traders: a blue color signifies an RSI above 60, indicating overbought conditions; a red color shows an RSI below 40, pointing to oversold conditions; and white represents values in between, suggesting a neutral state.
Moreover, the volatility histogram, which is part of the "CULTURATRADING INDICATOR," provides a visual representation of market volatility. The histogram changes colors based on the ADX value and the slope of the MACD line. For instance, a green histogram suggests a positive MACD slope during a strong trend, indicating potential bullish momentum. Conversely, a red histogram implies a negative MACD slope during strong trends, hinting at bearish momentum. A grey color might be used to represent periods when the trend is weak or the market is less volatile.
Together, these visual elements of the "CULTURATRADING INDICATOR" complement the strategy's signals, providing traders with an at-a-glance summary of the current market scenario, which can be particularly useful when managing multiple trades or assessing opportunities quickly.
Please remember, this script and its associated indicator are designed to serve as educational tools to assist in understanding market dynamics and are not intended as financial advice. Always conduct your own research and consider consulting a financial advisor for personalized guidance.
MACD + MA HTF Strategy - Dynamic SmoothingMACD + MA HTF Strategy - Dynamic Smoothing
The MACD alone generally gives too many false signals and is therefore often used in combination with different indicators. The basic idea to combine the MACD with a moving average on a higher time frame is a commonly used technique to only enter Longs in a uptrend and only Shorts in a downtrend while trading on lower timeframe charts. However, the main issue in many strategy scripts is that the HTF indicator is not visible on lower timecharts. With this strategy example I used the Dynamic Smoothing code to visualise the HTF MA filter to display on you lower timechart. This way it is easier to optimize the strategy settings to the instrument chart.
Orginality and Usefulness - Dynamic Smoothing
Visualizing a higher time frame on a lower timechart often gives jagged lines on your chart. As the calculation is done on less bars, compared to the bars you have open on your timechart. The dynamic smoothing factor is derived by taking the ratio of minutes of the higher time frame to the current time frame. This ensures the moving average remains fluid and consistent across different time frames, eliminating 'jagged' lines on your chart. This new MA value is then used as HTF filter on top of the MACD entry settings. Always make sure the time chart is equal or lower than the timeframe settings in the configuration settings. The intention of the script is to visualise the higher time frame confirmations while trading on a lower timechart.
Code example how to achieve Dynamic Smoothing:
// Get minutes for current and higher timeframes
// Function to convert a timeframe string to its equivalent in minutes
timeframeToMinutes(tf) =>
multiplier = 1
if (str.endswith(tf, "D"))
multiplier := 1440
else if (str.endswith(tf, "W"))
multiplier := 10080
else if (str.endswith(tf, "M"))
multiplier := 43200
else if (str.endswith(tf, "H"))
multiplier := int(str.tonumber(str.replace(tf, "H", "")))
else
multiplier := int(str.tonumber(str.replace(tf, "m", "")))
multiplier
// Get minutes for current and higher timeframes
currentTFMinutes = timeframeToMinutes(timeframe.period)
higherTFMinutes = timeframeToMinutes(TimeFrame_Trend)
// Calculate the smoothing factor
dynamicSmoothing = math.round(higherTFMinutes / currentTFMinutes)
MA_Value_Smooth = ta.sma(MA_Value_HTF, dynamicSmoothing)
Complete Strategy
The MACD and HTF moving average is used to determine when to enter a new position. However a strategy should consider more factors than only the timing of entering a trade. To complete the strategy I included:
an option to choose from different MA types per indicator
a Risk Management Tool
a Take Profit Logic
a Trailing stop loss
a Hard Stoploss
a visual representation of TP and SL
This is merely an example how to structure a strategy and many different setups are possible.
The features in this script are explained below:
Different MA types
The script supports various MA types like EMA, SMA, DEMA, TEMA, WMA and HMA. You can select the MA type and different timeframe to your liking.
Risk Management Tool
Traders can choose to allocate their position size based on a percentage of equity or a fixed number of contracts. This feature ensures prudent risk management and helps traders align their position sizes with their risk tolerance. In the strategy -0.5 is equal to 50% of equity and 1.5 is 150% of equity used. Make sure to align the % of equity with your maxdrawn results with backtesting. Personally I don't want higher max drawdowns than 15%. For the strategy results the script considers 0.05 commission rate on each trade, to stay conservative. For a more detailed explanation I refer to my earlier published tradingviewblog about risk management:
Take Profit Logic
The take profit logic in this script is designed for optimization, offering three distinct exit levels. Traders can customize these levels based on their risk appetite. The script allows adjustment of both the percentage take profit level and the position size, catering to individual trading strategies and objectives. The default settings closes 33% of the position when TP target is hit. The TP levels are simply calculated by inputting a % of of the entryprice.
Trailing Stop and Hard Stoploss
To mitigate downside risks and protect profits, the script incorporates a well-thought-out trailing stop mechanism based on the Average True Range (ATR). This dynamic trailing stop adapts to market volatility, allowing traders to secure gains while letting profitable positions run. Additionally, to prevent significant losses, a fixed stop loss is implemented, providing an added layer of protection.
Visual Representation of Take Profit and Stoploss Levels
For enhanced visualization, take profit and stoploss levels are displayed on the chart. Take profit levels are depicted with green lines, providing a clear indication of potential exit points. Conversely, the trailing stop loss is presented by the red line, serving as visual cues for risk management. Visualizing indicators makes is easier to optimize settings to your liking.
Ideal Settings and Accessibility
This script is intended to be used on lower timeframe charts like 10 to 30 minutes. You can Align the MACD entry settings equal to your opened timechart or use a slightly higher timeframe. For the MA trend filters, higher timeframe settings such as 30 min, 1 hour, 4 hours, or 1 day are recommended for trading the trend.
Disclaimer
Trading involves significant risk and may not be suitable for all investors. The information provided in this script is for educational purposes only and should not be considered as financial advice. Past performance is not indicative of future results. By using this script, you acknowledge that you understand and accept these risks.
Crypto MVRV ZScore - Strategy [PresentTrading]█ Introduction and How it is Different
The "Crypto Valuation Extremes: MVRV ZScore - Strategy " represents a cutting-edge approach to cryptocurrency trading, leveraging the Market Value to Realized Value (MVRV) Z-Score. This metric is pivotal for identifying overvalued or undervalued conditions in the crypto market, particularly Bitcoin. It assesses the current market valuation against the realized capitalization, providing insights that are not apparent through conventional analysis.
BTCUSD 6h Long/Short Performance
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█ Strategy, How It Works: Detailed Explanation
The strategy leverages the Market Value to Realized Value (MVRV) Z-Score, specifically designed for cryptocurrencies, with a focus on Bitcoin. This metric is crucial for determining whether Bitcoin is currently undervalued or overvalued compared to its historical 'realized' price. Below is an in-depth explanation of the strategy's components and calculations.
🔶Conceptual Foundation
- Market Capitalization (MC): This represents the total dollar market value of Bitcoin's circulating supply. It is calculated as the current price of Bitcoin multiplied by the number of coins in circulation.
- Realized Capitalization (RC): Unlike MC, which values all coins at the current market price, RC is computed by valuing each coin at the price it was last moved or traded. Essentially, it is a summation of the value of all bitcoins, priced at the time they were last transacted.
- MVRV Ratio: This ratio is derived by dividing the Market Capitalization by the Realized Capitalization (The ratio of MC to RC (MVRV Ratio = MC / RC)). A ratio greater than 1 indicates that the current price is higher than the average price at which all bitcoins were purchased, suggesting potential overvaluation. Conversely, a ratio below 1 suggests undervaluation.
🔶 MVRV Z-Score Calculation
The Z-Score is a statistical measure that indicates the number of standard deviations an element is from the mean. For this strategy, the MVRV Z-Score is calculated as follows:
MVRV Z-Score = (MC - RC) / Standard Deviation of (MC - RC)
This formula quantifies Bitcoin's deviation from its 'normal' valuation range, offering insights into market sentiment and potential price reversals.
🔶 Spread Z-Score for Trading Signals
The strategy refines this approach by calculating a 'spread Z-Score', which adjusts the MVRV Z-Score over a specific period (default: 252 days). This is done to smooth out short-term market volatility and focus on longer-term valuation trends. The spread Z-Score is calculated as follows:
Spread Z-Score = (Market Z-Score - MVVR Ratio - SMA of Spread) / Standard Deviation of Spread
Where:
- SMA of Spread is the simple moving average of the spread over the specified period.
- Spread refers to the difference between the Market Z-Score and the MVRV Ratio.
🔶 Trading Signals
- Long Entry Condition: A long (buy) signal is generated when the spread Z-Score crosses above the long entry threshold, indicating that Bitcoin is potentially undervalued.
- Short Entry Condition: A short (sell) signal is triggered when the spread Z-Score falls below the short entry threshold, suggesting overvaluation.
These conditions are based on the premise that extreme deviations from the mean (as indicated by the Z-Score) are likely to revert to the mean over time, presenting opportunities for strategic entry and exit points.
█ Practical Application
Traders use these signals to make informed decisions about opening or closing positions in the Bitcoin market. By quantifying market valuation extremes, the strategy aims to capitalize on the cyclical nature of price movements, identifying high-probability entry and exit points based on historical valuation norms.
█ Trade Direction
A unique feature of this strategy is its configurable trade direction. Users can specify their preference for engaging in long positions, short positions, or both. This flexibility allows traders to tailor the strategy according to their risk tolerance, market outlook, or trading style, making it adaptable to various market conditions and trader objectives.
█ Usage
To implement this strategy, traders should first adjust the input parameters to align with their trading preferences and risk management practices. These parameters include the trade direction, Z-Score calculation period, and the thresholds for long and short entries. Once configured, the strategy automatically generates trading signals based on the calculated spread Z-Score, providing clear indications for potential entry and exit points.
It is advisable for traders to backtest the strategy under different market conditions to validate its effectiveness and adjust the settings as necessary. Continuous monitoring and adjustment are crucial, as market dynamics evolve over time.
█ Default Settings
- Trade Direction: Both (Allows for both long and short positions)
- Z-Score Calculation Period: 252 days (Approximately one trading year, capturing a comprehensive market cycle)
- Long Entry Threshold: 0.382 (Indicative of moderate undervaluation)
- Short Entry Threshold: -0.382 (Signifies moderate overvaluation)
These default settings are designed to balance sensitivity to market valuation extremes with a pragmatic approach to trade execution. They aim to filter out noise and focus on significant market movements, providing a solid foundation for both new and experienced traders looking to exploit the unique insights offered by the MVRV Z-Score in the cryptocurrency market.
Bollinger and Stochastic with Trailing Stop - D.M.P.This trading strategy combines Bollinger Bands and the Stochastic indicator to identify entry opportunities in oversold and overbought conditions in the market. The aim is to capitalize on price rebounds from the extremes defined by the Bollinger Bands, with the confirmation of the Stochastic to maximize the probability of success of the operations.
Indicators Used
- Bollinger Bands Used to measure volatility and define oversold and overbought levels. When the price touches or breaks through the lower band, it indicates a possible oversold condition. Similarly, when it touches or breaks through the upper band, it indicates a possible overbought condition.
- Stochastic: A momentum oscillator that compares the closing price of an asset with its price range over a certain period. Values below 20 indicate oversold, while values above 80 indicate overbought.
Strategy Logic
- Long Entry (Buy): A purchase operation is executed when the price closes below the lower Bollinger band (indicating oversold) and the Stochastic is also in the oversold zone.
- Short Entry (Sell): A sell operation is executed when the price closes above the upper Bollinger band (indicating overbought) and the Stochastic is in the overbought zone.
CryptoGraph Dynamic DCAA system to backtest and automate comprehensive trading strategies
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🟣 Supporting Your Trades
CryptoGraph Dynamic DCA serves as a comprehensive tool on TradingView, designed to refine your approach to cryptocurrency trading. It utilises dynamic dollar-cost averaging (DCA), based on external indicator sources, to provide structured market entry and exit strategies. Suitable for both short-term trading and long-term portfolio management, CryptoGraph Dynamic DCA can offer a methodical way to support your trading decisions.
The tool offers an intuitive interface with inputs for strategy customisation, visualised preferences, and bot alert configurations. It can assist traders seeking precision, adaptability, and control in their trading activities. In the example on the chart above, we use the CryptoGraph Entry Builder (part of CryptoGraph Dynamic DCA package) as an external source for our initial entry (base order) and our safety orders, as well as an external source for our second take profit, which can be configured to be signal based.
🟣 Features
External Entry/Exit sources: The strategy is designed to assist with accurate market entries and exits by utilising signals from external indicators. It offers the flexibility to tailor your trading approach, providing an opportunity to leverage the analytical capabilities of various indicators available on TradingView.
Strategic Direction Control: Configure your strategy to go long, short, or both, adapting to market trends and your trading style.
Leverage Customisation: Tailor your leverage settings for isolated or cross margin to align with your risk tolerance, a liquidation estimation level is plotted on the chart, based on your input settings.
Diverse Entry Points: Utilise base orders and safety orders to diversify your entry points, reducing risk and enhancing potential returns.
Tailored Order Size: Fine-tune your order sizes using margin percentages or fixed contract sizes to fit your strategy’s requirements.
Profit Taking & Loss Prevention: Set take profit levels and stop losses with percentage or ATR-based parameters to secure profits and minimise losses. Options for moving the stop loss to entry after Take Profit 1, with an adjustable buffer, give you control over your risk management.
Max Safety Orders Count: Determine the maximum number of safety orders to manage risk effectively.
Price Deviation for DCA Orders: Specify the minimum price deviation percentage to trigger DCA orders, ensuring strategic order placement.
DCA Size Method: Choose from scaling or fixed-size DCA orders to align with your capital allocation strategy.
Visualisation & Alerts: Analyse your strategy’s performance with a backtest results table and configure bot alerts for automated trading. Auto configuration methods are integrated for multiple automated trading platforms.
🟣 Features Impression
🟣 Usage Guide
1. Strategy Configuration:
Select the appropriate cryptocurrency pair and exchange that corresponds to your trading preferences.
Choose your desired chart timeframe to align with your trading strategy’s temporal scope.
Ensure that you’re utilising the regular candle type for consistent and reliable data interpretation.
Pick an external entry source to trigger your trades based on predefined indicators or conditions.
Determine your take profit and stop loss levels to manage risks and secure earnings effectively.
Configure your DCA (Dollar-Cost Averaging) settings, including safety orders and the scaling method, to enhance entry points and manage investment distribution.
Always consult the tooltips next to each strategy input, to better understand their functions.
2. Backtest and Analysis:
Run backtests with your configured parameters to assess the strategy’s potential performance.
Review the backtest results and statistics tables to understand the strategy’s effectiveness, risk profile, and profitability.
3. Automated Trading Platform Integration:
Connect the strategy to a compatible automated trading platform to enable real-time execution of trades.
Within the trading platform, ensure the proper API setup of the bot’s configuration to align with the signals from the tool.
4. Alert Configuration in TradingView:
Set up the alert conditions in the TradingView tool to match your strategy triggers for entry, exit, take profit, and stop loss.
Configure the connection parameters within the tool to communicate effectively with your chosen automated trading platform
Activate the alerts, ensuring they are set to trigger actions such as order placement, adjustments, or closures as per your strategy’s logic.
5. Capital Management:
Confirm that your initial capital and order size are logically set, keeping in mind that the sum of all deals, especially when using pyramiding with safety orders, should not exceed your initial capital to avoid overexposure.
🟣 Trade Example
A clear example of a trade. Base order entry, safety order 1 fills, take profit 1 hits at 1%, the remainder of the position runs until the exit signal fires.
🟣 Warning
This tool has been developed to support your trading analysis, yet it’s important to acknowledge the inherent risks associated with trading. It is advisable to perform thorough research, assess your risk tolerance, and utilise this tool as one element of an overall trading strategy. Ensure that you only trade with capital that you are prepared to risk. In addition, due to the complexity of the tool, bugs may be found. Please alert us whenever you think you have found a bug in the system.
Supertrend & CCI Strategy ScalpThis strategy is based on 2 Super Trend Indicators along with CCI .
The longer factor length gives you the current trend and the deviation in the short factor length gives us the opportunity to enter in the trade .
CCI indicator is used to determine the overbought and oversold levels.
Setup :
Long : When atrLength1 > close and atrLength2 < close and CCI < -100 we look for long trades as the longer factor length will be bullish .
Short : When atrLength1 < close and atrLength2 > close and CCI > 100 we look for short trades as the longer factor length will be bearish .
Please tune the settings according to your use .
Trade what you see not what you feel .
Please consult with your financial advisor before you deploy any real money for trading .
PresentTrend RMI Synergy - Strategy [presentTrading] █ Introduction and How it is Different
The "PresentTrend RMI Synergy Strategy" is the combined power of the Relative Momentum Index (RMI) and a custom presentTrend indicator. This strategy introduces a multifaceted approach, integrating momentum analysis with trend direction to offer traders a more nuanced and responsive trading mechanism.
BTCUSD 6h L/S Performance
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█ Strategy, How It Works: Detailed Explanation
The "PresentTrend RMI Synergy Strategy" intricately combines the Relative Momentum Index (RMI) and a custom SuperTrend indicator to create a powerful tool for traders.
🔶 Relative Momentum Index (RMI)
The RMI is a variation of the Relative Strength Index (RSI), but instead of using price closes against itself, it measures the momentum of up and down movements in price relative to previous prices over a given period. The RMI for a period length `N` is calculated as follows:
RMI = 100 - 100/ (1 + U/D)
where:
- `U` is the average upward price change over `N` periods,
- `D` is the average downward price change over `N` periods.
The RMI oscillates between 0 and 100, with higher values indicating stronger upward momentum and lower values suggesting stronger downward momentum.
RMI = 21
RMI = 42
For more information - RMI Trend Sync - Strategy :
🔶 presentTrend Indicator
The presentTrend indicator combines the Average True Range (ATR) with a moving average to determine trend direction and dynamic support or resistance levels. The presentTrend for a period length `M` and a multiplier `F` is defined as:
- Upper Band: MA + (ATR x F)
- Lower Band: MA - (ATR x F)
where:
- `MA` is the moving average of the close price over `M` periods,
- `ATR` is the Average True Range over the same period,
- `F` is the multiplier to adjust the sensitivity.
The trend direction switches when the price crosses the presentTrend bands, signaling potential entry or exit points.
presentTrend length = 3
presentTrend length = 10
For more information - PresentTrend - Strategy :
🔶 Strategy Logic
Entry Conditions:
- Long Entry: Triggered when the RMI exceeds a threshold, say 60, indicating a strong bullish momentum, and when the price is above the presentTrend, confirming an uptrend.
- Short Entry: Occurs when the RMI drops below a threshold, say 40, showing strong bearish momentum, and the price is below the present trend, indicating a downtrend.
Exit Conditions with Dynamic Trailing Stop:
- Long Exit: Initiated when the price crosses below the lower presentTrend band or when the RMI falls back towards a neutral level, suggesting a weakening of the bullish momentum.
- Short Exit: Executed when the price crosses above the upper presentTrend band or when the RMI rises towards a neutral level, indicating a reduction in bearish momentum.
Equations for Dynamic Trailing Stop:
- For Long Positions: The exit price is set at the lower SuperTrend band once the entry condition is met.
- For Short Positions: The exit price is determined by the upper SuperTrend band post-entry.
These dynamic trailing stops adjust as the market moves, providing a method to lock in profits while allowing room for the position to grow.
This strategy's strength lies in its dual analysis approach, leveraging RMI for momentum insights and presentTrend for trend direction and dynamic stops. This combination offers traders a robust framework to navigate various market conditions, aiming to capture trends early and exit positions strategically to maximize gains and minimize losses.
█ Trade Direction
The strategy provides flexibility in trade direction selection, offering "Long," "Short," or "Both" options to cater to different market conditions and trader preferences. This adaptability ensures that traders can align the strategy with their market outlook, risk tolerance, and trading goals.
█ Usage
To utilize the "PresentTrend RMI Synergy Strategy," traders should input their preferred settings in the Pine Script™ and apply the strategy to their charts. Monitoring RMI for momentum shifts and adjusting positions based on SuperTrend signals can optimize entry and exit points, enhancing potential returns while managing risk.
█ Default Settings
1. RMI Length: 21
The 21-period RMI length strikes a balance between capturing momentum and filtering out market noise, offering a medium-term outlook on market trends.
2. Super Trend Length: 7
A SuperTrend length of 7 periods is chosen for its responsiveness to price movements, providing a dynamic framework for trend identification without excessive sensitivity.
3. Super Trend Multiplier: 4.0
The multiplier of 4.0 for the SuperTrend indicator widens the trend bands, focusing on significant market moves and reducing the impact of minor fluctuations.
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The "PresentTrend RMI Synergy Strategy" represents a significant step forward in trading strategy development, blending momentum and trend analysis in a unique way. By providing a detailed framework for understanding market dynamics, this strategy empowers traders to make more informed decisions.
