Supertrend StrategyThe Supertrend Strategy was created based on the Supertrend and Relative Strength Index (RSI) indicators, widely respected tools in technical analysis. This strategy combines these two indicators to capture market trends with precision and reliability, looking for optimizing exit levels at oversold or overbought price levels.
The Supertrend indicator identifies trend direction based on price and volatility by using the Average True Range (ATR). The ATR measures market volatility by calculating the average range between an asset’s high and low prices over a set period. It provides insight into price fluctuations, with higher ATR values indicating increased volatility and lower values suggesting stability. The Supertrend Indicator plots a line above or below the price, signaling potential buy or sell opportunities: when the price closes above the Supertrend line, an uptrend is indicated, while a close below the line suggests a downtrend. This line shifts as price movements and volatility levels change, acting as both a trailing stop loss and trend confirmation.
To enhance the Supertrend strategy, the Relative Strength Index (RSI) has been added as an exit criterion. As a momentum oscillator, the RSI indicates overbought (usually above 70) or oversold (usually below 30) conditions. This integration allows trades to close when the asset is overbought or oversold, capturing gains before a possible reversal, even if the percentage take profit level has not been reached. This mechanism aims to prevent losses due to market reversals before the Supertrend signal changes.
### Key Features
1. **Entry criteria**:
- The strategy uses the Supertrend indicator calculated by adding or subtracting a multiple of the ATR from the closing price, depending on the trend direction.
- When the price crosses above the Supertrend line, the strategy signals a long (buy) entry. Conversely, when the price crosses below, it signals a short (sell) entry.
- The strategy performs a reversal if there is an open position and a change in the direction of the supertrend occurs
2. **Exit criteria**:
- Take profit of 30% (default) on the average position price.
- Oversold (≤ 5) or overbought (≥ 95) RSI
- Reversal when there is a change in direction of the Supertrend
3. **No Repainting**:
- This strategy is not subject to repainting, as long as the timeframe configured on your chart is the same as the supertrend timeframe .
4. **Position Sizing by Equity and risk management**:
- This strategy has a default configuration to operate with 35% of the equity. At the time of opening the position, the supertrend line is typically positioned at about 12 to 16% of the entry price. This way, the strategy is putting at risk about 16% of 35% of equity, that is, around 5.6% of equity for each trade. The percentage of equity can be adjusted by the user according to their risk management.
5. **Backtest results**:
- This strategy was subjected to deep backtesting and operations in replay mode, including transaction fees of 0.12%, and slippage of 5 ticks.
- The past results in deep backtest and replay mode were compatible and profitable (Variable results depending on the take profit used, supertrend and RSI parameters). However, it should be noted that few operations were evaluated, since the currency in question has been created for a short time and the frequency of operations is relatively small.
- Past results are no guarantee of future results. The strategy's backtest results may even be due to overfitting with past data.
Default Settings
Chart timeframe: 2h
Supertrend Factor: 3.42
ATR period: 14
Supertrend timeframe: 2 h
RSI timeframe: 15 min
RSI Lenght: 5 min
RSI Upper limit: 95
RSI Lower Limit: 5
Take Profit: 30%
BYBIT:1000000MOGUSDT.P
Pesquisar nos scripts por "stop loss"
MACD Trend Trading with Dynamic Position Sizing // AlgoFyreThe MACD Trend Trading with Dynamic Position Sizing strategy combines MACD and trend indicators for trend trading. It uses MACD crossovers to identify entry points and a trend source for directional bias. The strategy incorporates risk management through dynamic position sizing based on a fixed risk amount. It allows for both long and short positions with customizable stop-loss and take-profit levels. The script includes visualization options for entry, stop-loss, and take-profit levels, enhancing trade analysis.
TABLE OF CONTENTS
🔶 ORIGINALITY
🔸Dynamic Position Sizing
🔸Trend-MACD Combination
🔸Customizable Risk Management
🔶 FUNCTIONALITY
🔸Indicators
🞘 Trend Indicator
🞘 Moving Average Convergence Divergence (MACD)
🔸Conditions
🞘 Long Entry
🞘 Short Entry
🔶 INSTRUCTIONS
🔸Step-by-Step Guidelines
🞘 Setting Up the Strategy
🞘 Alerts
🔸Customize settings
🔶 CONCLUSION
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🔶 ORIGINALITY The MACD Trend Trading with Dynamic Position Sizing strategy uniquely combines MACD indicators with trend analysis to optimize entry and exit points. Unlike static trading strategies, it employs dynamic position sizing based on a fixed risk amount, ensuring consistent risk management. This approach allows traders to adapt to varying market conditions by adjusting position sizes according to predefined risk parameters, enhancing both flexibility and control in trading decisions. The strategy's integration of customizable stop-loss and take-profit levels further refines its risk management capabilities, making it a robust tool for both trending and volatile markets.
🔸Dynamic Position Sizing This strategy calculates position sizes dynamically, based on a fixed risk amount, allowing traders to maintain consistent risk exposure across trades.
🔸Trend-MACD Combination By combining trend direction with MACD crossovers, the strategy enhances the accuracy of entry signals, aligning trades with prevailing market trends.
🔸Customizable Risk Management Traders can set flexible risk-reward ratios and adjust stop-loss and take-profit levels, tailoring the strategy to their risk tolerance and market conditions.
🔶 FUNCTIONALITY The MACD Trend Trading with Dynamic Position Sizing strategy leverages a combination of trend indicators and the MACD to identify optimal trading opportunities. This strategy is designed to capitalize on short-term price movements by dynamically adjusting position sizes based on predefined risk parameters. It allows traders to manage risk effectively while taking advantage of both long and short positions.
🔸Indicators 🞘 Trend Indicator: Utilizes the trend source to determine market direction, ensuring trades align with prevailing trends.
Recommendation: We recommend using the Adaptive MAs (Hurst, CVaR, Fractal) indicator with the following settings for trend detection. However, you can use any trend indicator that suits your trading style.
🞘 Moving Average Convergence Divergence (MACD): Employs MACD crossovers to generate entry signals, enhancing the accuracy of trade execution. Use the "Moving Average Convergence Divergence" Indicator with the following settings:
🔸Conditions 🞘 Long Entry: Initiates a long position when the price is above the trend source, and a MACD crossover occurs with both MACD and signal lines below zero.
🞘 Short Entry: Initiates a short position when the price is below the trend source, and a MACD crossunder occurs with both MACD and signal lines above zero.
🔶 INSTRUCTIONS
The MACD Trend Trading with Dynamic Position Sizing strategy can be set up by adding it to your TradingView chart and configuring parameters such as the MACD source, trend source, and risk management settings. This strategy is designed to capitalize on short-term price movements by dynamically adjusting position sizes based on predefined risk parameters. Enhance the accuracy of signals by combining this strategy with additional indicators like trend-following or momentum-based tools. Adjust settings to better manage risk and optimize entry and exit points.
🔸Step-by-Step Guidelines
🞘 Setting Up the Strategy
Adding the Strategy to the Chart:
Go to your TradingView chart.
Click on the "Indicators" button at the top.
Search for "MACD Trend Trading with Dynamic Position Sizing" in the indicators list.
Click on the strategy to add it to your chart.
Configuring the Strategy:
Open the strategy settings by clicking on the gear icon next to its name on the chart.
MACD: Select the MACD from the MACD Indicator.
MACD Signal: Select the MACD Signal from the MACD Indicator.
Trend Source: Choose the trend source to determine market direction. If you use the Adaptive MAs (Hurst, CVaR, Fractal) with our settings shown above, choose the MA1 Smoothing Line.
Stop Loss Percentage: Set the stop loss distance from the trend source as a percentage.
Risk/Reward Ratio: Define the desired risk/reward ratio for trades.
Backtesting and Practice:
Backtest the strategy on historical data to understand how it performs in various market environments.
Practice using the strategy on a demo account before implementing it in live trading.
Market Awareness:
Keep an eye on market news and events that might cause extreme price movements. The strategy reacts to price data and might not account for news-driven events that can cause large deviations.
🔶 CONCLUSION
The MACD Trend Trading with Dynamic Position Sizing strategy provides a robust framework for capitalizing on short-term market trends by combining the MACD indicator with dynamic position sizing. This strategy leverages MACD crossovers to identify entry points and utilizes a trend source for directional bias, ensuring trades align with prevailing market conditions. By incorporating dynamic position sizing based on a fixed risk amount, traders can effectively manage risk and adapt to varying market conditions. The strategy's customizable stop-loss and take-profit levels further enhance its risk management capabilities, making it a versatile tool for both trending and volatile markets. With its strategic blend of technical indicators and risk management, the MACD Trend Trading strategy offers traders a comprehensive approach to optimizing trade execution and maximizing potential returns.
Trend Confirmation and ASO-based StrategyStrategy Name: Trend Confirmation with EMA, ASO, and ATR Bands Auto-Trading
Purpose:
This strategy aims to enhance trend confirmation and entry point precision by combining multiple technical indicators. Specifically, it uses the 200 EMA for trend confirmation, the Average Sentiment Oscillator (ASO) to capture market sentiment, and ATR bands for risk management. This provides a comprehensive approach to capturing trade opportunities. The strategy emphasizes trend-following trades, reducing noise while keeping risk management simple.
Uniqueness and Usefulness:
Uniqueness:
This strategy stands out because it integrates multiple elements that complement each other for increased effectiveness and originality. Instead of relying on a single indicator, it generates more accurate trading signals by allowing each indicator to work synergistically.
200 EMA: Used to confirm the long-term trend, providing clarity on the trend direction and ensuring trades align with the dominant market trend.
Average Sentiment Oscillator (ASO): Measures market sentiment based on the crossover between the bull and bear lines. Signals are generated only when ASO detects a trend shift, filtering out price fluctuations and noise.
ATR Bands: Evaluates market volatility and sets stop-loss levels upon entry. By using ATR bands, the strategy supports traders in maintaining a fixed stop-loss for risk management.
Each component analyzes the market from a different perspective, and together, they generate reliable signals for trend-following trades. These indicators are not simply combined but are clearly defined in their roles to improve signal quality.
Usefulness:
This strategy is suitable for medium to long-term traders who focus on trend-following. It emphasizes entry during the early stages of a trend and focuses on risk management by offering reliable signals with minimal noise. The combination of ASO and ATR bands allows traders to assess market volatility while setting take profit levels based on a risk-reward ratio. This helps avoid overreacting to short-term price fluctuations and supports sustainable trading practices.
Entry Conditions:
Long Entry:
Condition: Price is above the 200 EMA, and the ASO bull line crosses above the bear line while also exceeding the 50 level.
Signal: A buy signal is generated, indicating the start of an uptrend.
Short Entry:
Condition: Price is below the 200 EMA, and the ASO bear line crosses above the bull line while also exceeding the 50 level.
Signal: A sell signal is generated, indicating the start of a downtrend.
Exit Conditions:
Exit Strategy:
While this strategy automates both entries and exits, it is recommended that traders manually manage their positions for risk control when necessary. The stop-loss is set based on ATR bands at the time of entry, and a take-profit is set with a risk-reward ratio of 1:1.5.
Risk Management:
This strategy incorporates a fixed stop-loss mechanism, where the stop-loss is set at entry based on the ATR band value. Once set, the stop-loss remains fixed, ensuring that trades stay within a predetermined risk range. The take-profit is based on a risk-reward ratio of 1:1.5, increasing the potential reward relative to the risk.
Account Size: ¥100,000
Commissions and Slippage: Assumed commission of 94 pips per trade and slippage of 1 pip.
Risk per Trade: 10% of account equity (adjustable based on risk tolerance).
Configurable Options:
ASO Period: Period setting for the Average Sentiment Oscillator (default is 32).
ATR Multiplier: Multiplier for ATR band calculation (default is 2.0).
EMA Period: Settings for the 200 EMA.
Signal Display Control: Option to toggle entry signal visibility on or off.
Adequate Sample Size:
To verify the effectiveness of this strategy, it is recommended to conduct extensive backtesting over a long period, covering different market conditions, including both high and low volatility environments.
Credits:
Acknowledgments:
This strategy integrates technical approaches based on the Average Sentiment Oscillator, 200 EMA, and ATR bands, drawing insights from the broader trading community.
Clean Chart Description:
Chart Appearance:
This strategy maintains a clean chart display by offering a toggle to switch the visibility of the ASO, EMA, and entry signals on or off. This helps reduce visual clutter and enhances effective trend analysis.
Addressing the House Rule Violations:
Omissions and Unrealistic Claims:
This strategy makes no exaggerated claims or guarantees about performance. All signals are provided for educational purposes, and it is emphasized that past performance does not guarantee future results. Proper risk management is essential, and the importance of this is highlighted throughout the strategy.
[1H] Auto SignalMakerBINANCE:SANDUSDT
this strategy is Squeeze Momentum strategy is the on base.
And we added custom ma filter and risk management method. this is not repaint.
This strategy is a long-term strategy.
Use stop loss and profit.
All trading involves high risk; past performance is not necessarily indicative of future results. Hypothetical or simulated performance results have certain inherent limitations.
Unlike an actual performance record, simulated results do not represent actual trading.
Also, since the trades have not actually been executed, the results may have under- or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity.
Simulated trading programs in general are also subject to the fact that they are designed with the benefit of hindsight.
No representation is being made that any account will or is likely to achieve profits or losses similar to those shown.
HFT V.2 EnhancedTitle: HFT V.2 Enhanced - ATR Dynamic Stop-Loss & Take-Profit
Description:
The HFT V.2 Enhanced strategy is designed for high-frequency trading with dynamic trade management and robust entry/exit logic. This strategy uses simple moving averages (SMA) for trend identification and the relative strength index (RSI) for momentum confirmation. In this enhanced version, the strategy also incorporates dynamic stop-loss and take-profit levels based on the Average True Range (ATR), offering better adaptability to market volatility.
Features:
Moving Average Crossover: Uses a fast and slow SMA to capture trend reversals and generate trade entries.
RSI Confirmation: Ensures momentum is in the direction of the trade by incorporating the RSI threshold for both long and short entries.
Dynamic Stop-Loss and Take-Profit: Stop-loss and take-profit levels are calculated based on the ATR, allowing the strategy to adjust its exit points according to market volatility. This helps manage risk more effectively and capture larger trends.
Auto-Close Opposing Positions: Automatically closes any open long positions when a short entry is triggered, and vice versa.
Once-Per-Bar Execution: Ensures that a position is entered only once per bar, avoiding multiple trades within the same bar.
Parameters:
Fast MA Length: Defines the length of the fast-moving average.
Slow MA Length: Defines the length of the slow-moving average.
RSI Length: Sets the period for the RSI indicator.
RSI Threshold: Controls the RSI level for confirming momentum (50 by default).
ATR Length: Determines the period for the ATR calculation.
ATR Multiplier for Stop-Loss/Take-Profit: Adjusts the sensitivity of the stop-loss and take-profit levels based on ATR.
How it Works:
Long Entry: The strategy opens a long trade when the fast SMA crosses above the slow SMA, and the RSI is above the user-defined threshold. A dynamic stop-loss is placed below the entry price, and a take-profit target is set based on ATR.
Short Entry: The strategy opens a short trade when the fast SMA crosses below the slow SMA, and the RSI is below the inverse threshold. A stop-loss is placed above the entry price, and a take-profit target is set using ATR.
Risk Management: The strategy adapts to changing market conditions by dynamically adjusting its stop-loss and take-profit levels, ensuring it remains responsive to market volatility.
This script is ideal for traders looking for a high-frequency strategy with advanced trade management, including dynamic exits and volatility-based risk management.
Disclaimer: Always backtest and optimize the parameters to fit your trading style and risk tolerance before using the strategy in live trading.
ICT Indicator with Paper TradingThe strategy implemented in the provided Pine Script is based on **ICT (Inner Circle Trader)** concepts, particularly focusing on **order blocks** to identify key levels for potential reversals or continuations in the market. Below is a detailed description of the strategy:
### 1. **Order Block Concept**
- **Order blocks** are price levels where large institutional orders accumulate, often leading to a reversal or continuation of price movement.
- In this strategy, **order blocks** are identified when:
- The high of the current bar crosses above the high of the previous bar (for bullish order blocks).
- The low of the current bar crosses below the low of the previous bar (for bearish order blocks).
### 2. **Buy and Sell Signal Generation**
The core of the strategy revolves around identifying the **breakout** of order blocks, which is interpreted as a signal to either enter or exit trades:
- **Buy Signal**:
- Generated when the closing price crosses **above** the last identified bullish order block (i.e., the highest point during the last upward crossover of highs).
- This signals a potential upward trend, and the strategy enters a long position.
- **Sell Signal**:
- Generated when the closing price crosses **below** the last identified bearish order block (i.e., the lowest point during the last downward crossover of lows).
- This signals a potential downward trend, and the strategy exits any open long positions.
### 3. **Strategy Execution**
The strategy is executed using the `strategy.entry()` and `strategy.close()` functions:
- **Enter Long Positions**: When a buy signal is generated, the strategy opens a long position (buying).
- **Exit Positions**: When a sell signal is generated, the strategy closes the long position.
### 4. **Visual Indicators on the Chart**
To make the strategy easier to follow visually, buy and sell signals are marked directly on the chart:
- **Buy signals** are indicated with a green upward-facing triangle above the bar where the signal occurred.
- **Sell signals** are indicated with a red downward-facing triangle below the bar where the signal occurred.
### 5. **Key Elements of the Strategy**
- **Trend Continuation and Reversals**: This strategy is attempting to capture trends based on the breakout of important price levels (order blocks). When the price breaks above or below a significant order block, it is expected that the market will continue in that direction.
- **Order Block Strength**: Order blocks are considered strong areas where price action could reverse or accelerate, based on how institutional investors place large orders.
### 6. **Paper Trading**
This script uses **paper trading** to simulate trades without actual money being involved. This allows users to backtest the strategy, seeing how it would have performed in historical market conditions.
### 7. **Basic Strategy Flow**
1. **Order Block Identification**: The script constantly monitors price movements to detect bullish and bearish order blocks.
2. **Buy Signal**: If the closing price crosses above the last order block high, the strategy interprets it as a sign of bullish momentum and enters a long position.
3. **Sell Signal**: If the closing price crosses below the last order block low, it signals a bearish momentum, and the strategy closes the long position.
4. **Visual Representation**: Buy and sell signals are displayed on the chart for easy identification.
### **Advantages of the Strategy:**
- **Simple and Clear Rules**: The strategy is based on clearly defined rules for identifying order blocks and trade signals.
- **Effective for Trend Following**: By focusing on breakouts of order blocks, this strategy attempts to capture strong trends in the market.
- **Visual Aids**: The plot of buy/sell signals helps traders to quickly see where trades would have been placed.
### **Limitations:**
- **No Shorting**: This strategy only enters long positions (buying). It does not account for shorting opportunities.
- **No Risk Management**: There are no built-in stop losses, trailing stops, or profit targets, which could expose the strategy to large losses during adverse market conditions.
- **Whipsaws in Range Markets**: The strategy could produce false signals in sideways or choppy markets, where breakouts are short-lived and prices quickly reverse.
### **Overall Strategy Objective:**
The goal of the strategy is to enter into long positions when the price breaks above a significant order block, and exit when it breaks below. The strategy is designed for trend-following, with the assumption that price will continue in the direction of the breakout.
Let me know if you'd like to enhance or modify this strategy further!
Trading TP SL### Detailed Explanation of the "Trading TP SL" Indicator:
#### 1. **Main Purpose of the Indicator**:
This Pine Script strategy is designed to automate trading decisions by using predefined Take Profit (TP) and Stop Loss (SL) levels for both buy and sell orders. It allows for visual representation of these levels on the chart through lines and labels.
---
#### 2. **Key Variables**:
- **Candle_length**: Specifies the number of candles used for calculating the Simple Moving Average (SMA).
- **Quantity_of_deals**: Defines the number of consecutive price conditions needed to trigger a trade.
- **SLbuy and SLsell**: Inputs for setting the stop loss level for buy and sell trades.
- **TPbuy1 - TPbuy4 and TPsell1 - TPsell4**: Inputs for specifying up to four take profit levels for buy and sell trades.
- **show_SL_buy and show_TP1_buy (and others)**: These options control whether the lines and labels for the specified levels are shown on the chart.
---
#### 3. **Buy Logic**:
- The script calculates the Simple Moving Average (SMA) using the number of candles specified by **Candle_length**.
- A condition is checked to see if the current price is above the SMA (**bcond = price > ma**).
- If this condition holds true for a number of candles equal to **Quantity_of_deals**, a buy trade is triggered with the command: `strategy.entry("BUY", strategy.long)`.
- The stop loss and take profit levels are calculated based on user inputs (in ticks).
##### Example:
- If the price is above the 50-period SMA, and this happens for 30 consecutive candles, a buy order will be triggered, with the corresponding SL and TP levels plotted on the chart.
---
#### 4. **Sell Logic**:
- The opposite logic applies for sell trades. If the price is below the SMA (**scond = price < ma**) for a number of candles equal to **Quantity_of_deals**, a sell trade is triggered using: `strategy.entry("SELL", strategy.short)`.
- Stop loss and take profit levels are calculated and displayed in the same way as for buy trades.
---
#### 5. **Displaying Lines and Labels**:
- Lines and labels are drawn on the chart to represent the SL and TP levels using the `line.new` and `label.new` functions.
- The visibility of these lines and labels is controlled by options like **show_SL_buy**, **show_TP1_buy**, **show_SL_sell**, etc.
##### Example:
- If **show_SL_buy** is enabled, a red line and label for the buy stop loss will appear on the chart, labeled "SL".
- The same applies for the take profit levels (TP1, TP2, etc.) and the sell orders.
---
#### 6. **Color Customization**:
- The script allows for customization of colors for different components:
- **SL_1**: The color of the buy stop loss line (red).
- **TP_1**: The color of the first take profit line for buy orders (green).
- **short1**: The color of the sell order line.
---
### Advantages:
- Full control over profit and stop loss levels.
- Flexibility to define the number of conditions required to trigger a trade.
- Options to show or hide levels on the chart, providing visual clarity.
---
### Conclusion:
This strategy is built around using the Simple Moving Average (SMA) to identify entry signals for both buy and sell trades. The stop loss and take profit levels are user-defined, with significant flexibility to customize and visualize them on the chart.
### شرح تفصيلي لمؤشر "Trading TP SL" المكتوب بلغة Pine Script:
#### 1. **الهدف الأساسي للمؤشر**:
المؤشر مصمم كاستراتيجية تداول مبنية على أوامر الشراء والبيع مع إعدادات خاصة بأهداف الربح (TP) ومستويات إيقاف الخسارة (SL). يتم تحديد هذه المستويات بشكل يدوي عن طريق المدخلات، مع إمكانية إظهار الخطوط والملصقات على الرسم البياني لتوضيح تلك المستويات.
---
#### 2. **المتغيرات الأساسية**:
- **Candle_length**: عدد الشموع المستخدمة لحساب المتوسط المتحرك البسيط (SMA).
- **Quantity_of_deals**: عدد الصفقات المطلوبة قبل تفعيل إشارة الدخول.
- **SLbuy و SLsell**: مستوى إيقاف الخسارة للشراء والبيع.
- **TPbuy1 - TPbuy4 و TPsell1 - TPsell4**: مستويات الربح المستهدفة (TP) للشراء والبيع.
- **show_SL_buy و show_TP1_buy (وما إلى ذلك)**: هذه الخيارات تظهر أو تخفي الخطوط والملصقات على الرسم البياني لكل مستوى من المستويات المحددة.
---
#### 3. **المنطق وراء الشراء**:
- يتم حساب المتوسط المتحرك البسيط (SMA) باستخدام الشموع المحددة في المتغير **Candle_length**.
- يتم التأكد مما إذا كان السعر الحالي أعلى من هذا المتوسط المتحرك البسيط (**bcond = price > ma**).
- إذا تحقق هذا الشرط لعدد من الشموع يساوي **Quantity_of_deals**، يتم تفعيل صفقة شراء باستخدام أمر: `strategy.entry("BUY", strategy.long)`.
- يتم حساب مستويات إيقاف الخسارة وأهداف الربح بناءً على القيمة المدخلة من المستخدم (القيمة بالنقاط).
##### مثال:
- إذا كان السعر الحالي أكبر من المتوسط المتحرك لمدة 50 شمعة، وحدث ذلك على التوالي لـ 30 شمعة، سيتم تفعيل صفقة شراء مع مستويات إيقاف الخسارة وأهداف الربح المعروضة على الرسم البياني.
---
#### 4. **المنطق وراء البيع**:
- يحدث العكس في حالة البيع. إذا كان السعر أقل من المتوسط المتحرك البسيط (**scond = price < ma**) وتحقق هذا الشرط لعدد من الشموع يساوي **Quantity_of_deals**، يتم تفعيل صفقة بيع باستخدام أمر: `strategy.entry("SELL", strategy.short)`.
- يتم حساب مستويات إيقاف الخسارة وأهداف الربح وفقًا للقيم المدخلة من المستخدم، وتظهر هذه المستويات على الرسم البياني.
---
#### 5. **إظهار الخطوط والملصقات**:
- يتم رسم الخطوط والملصقات على الرسم البياني لإيضاح المستويات (SL و TP) باستخدام دوال `line.new` و `label.new`.
- يمكنك التحكم في إظهار أو إخفاء هذه الخطوط والملصقات عن طريق الخيارات **show_SL_buy**, **show_TP1_buy**, **show_SL_sell**, إلخ.
##### مثال:
- إذا تم تفعيل خيار **show_SL_buy**، سيظهر خط إيقاف الخسارة للشراء على الرسم البياني بلون أحمر مع ملصق يُظهر "SL".
- يتم تكرار نفس الشيء لأهداف الربح (TP1, TP2, إلخ) وخطوط البيع.
---
#### 6. **ألوان المكونات**:
- الألوان لكل مستوى يمكن تخصيصها. على سبيل المثال:
- **SL_1**: لون إيقاف الخسارة للشراء (أحمر).
- **TP_1**: لون هدف الربح الأول للشراء (أخضر).
- **short1**: لون صفقة البيع.
---
### المزايا:
- التحكم الكامل في مستويات الربح والخسارة.
- إمكانية تخصيص عدد الصفقات المطلوبة لتفعيل إشارة الدخول.
- إظهار أو إخفاء المستويات على الرسم البياني وفقًا لرغبة المستخدم.
---
### الخلاصة:
هذه الاستراتيجية تعتمد على المتوسط المتحرك البسيط (SMA) لعدد معين من الشموع كإشارة دخول، سواء للشراء أو البيع. يتم تعيين مستويات الربح والخسارة يدويًا، مع توفير مرونة عالية في إظهار الخطوط والملصقات على الرسم البياني.
Calculus Free Trend Strategy for Crypto & StocksObjective :
The Correlation Channel Trading Strategy is designed to identify potential entry points based on the relationship between price movements and a correlation channel. The strategy aims to capture trends within the channel while managing risk effectively.
Parameters :
Length: Determines the period for calculating moving averages and the true range, influencing the sensitivity of the strategy to price movements.
Multiplier: Adjusts the width of the correlation channel, providing flexibility to adapt to different market conditions.
Inputs :
Asset Symbol: Allows users to specify the financial instrument for analysis.
Timeframe: Defines the timeframe for data aggregation, enabling customization based on trading preferences.
Plot Correlation Channel: Optional input to visualize the correlation channel on the price chart.
Methodology :
Data Acquisition: The strategy fetches OHLC (Open, High, Low, Close) data for the specified asset and timeframe. In this case we use COINBASE:BTCUSD
Calculation of Correlation Channel: It computes the squared values for OHLC data, calculates the average value (x), and then calculates the square root of x to derive the source value. Additionally, it calculates the True Range as the difference between high and low prices.
Moving Averages: The strategy calculates moving averages (MA) for the source value and the True Range, which form the basis for defining the correlation channel.
Upper and Lower Bands: Using the MA and True Range, the strategy computes upper and lower bands of the correlation channel, with the width determined by the multiplier.
Entry Conditions: Long positions are initiated when the price crosses above the upper band, signaling potential overbought conditions. Short positions are initiated when the price crosses below the lower band, indicating potential oversold conditions.
Exit Conditions: Stop-loss mechanisms are incorporated directly into the entry conditions to manage risk. Long positions are exited if the price falls below a predefined stop-loss level, while short positions are exited if the price rises above the stop-loss level.
Strategy Approach: The strategy aims to capitalize on trends within the correlation channel, leveraging systematic entry signals while actively managing risk through stop-loss orders.
Backtest Details : For the purpose of this test I used the entire data available for BTCUSD Coinbase, with 10% of capital allocation and 0.1% comission for entry/exit(0.2% total). Can be also used with other both directly correlated with current settings of BTC or with new ones
Advantages :
Provides a systematic approach to trading based on quantifiable criteria.
Offers flexibility through customizable parameters to adapt to various market conditions.
Integrates risk management through predefined stop-loss mechanisms.
Limitations :
Relies on historical price data and technical indicators, which may not always accurately predict future price movements.
May generate false signals during periods of low volatility or erratic price behavior.
Requires continuous monitoring and adjustment of parameters to maintain effectiveness.
Conclusion :
The Correlation Channel Trading Strategy offers traders a structured framework for identifying potential entry points within a defined price channel. By leveraging moving averages and true range calculations, the strategy aims to capture trends while minimizing risk through stop-loss mechanisms. While no strategy can guarantee success in all market conditions, the Correlation Channel Trading Strategy provides a systematic approach to trading that can enhance decision-making and risk management for traders.
Footprint strategyThis strategy uses imbalance volume data obtained by footprint calculation technology.
There are two signals to enter a trade:
trend - the current buy volume on the bar is greater than the current sell volume and there is at least one imbalance line.
reversal - the current bar is falling, but the general market trend is positive (growing) and the imbalance buy volume exceeds the imbalance sell volume.
When any of the conditions is triggered, two orders are placed: Take Profit and Stop loss (according to the percentage value from the inputs).
A little advice on use:
The strategy performs best on a 15 minute timeframe.
It is necessary to choose acceptable values of Take Profit and Stop loss depending on the order of symbol prices.
Inputs related to the strategy:
Stop loss - percentage size of stop loss to exit the trade.
Enable stop loss - stop loss activation.
Take Profit - percentage size of Take Profit.
Calculation timeframe - this is the timeframe from which the volume will be collected for distribution to buy and sell (if you do not have access to the seconds chart, set here 1 minute, the accuracy will be less, but it will work).
Trend timeframe - this is the timeframe from which the trend will be calculated.
Enable trend - activation of trend calculation.
Inputs related to the calculation of footprints (collection of the volume of purchases and sales):
Count show bars - Number of bars from rt bar to history to calculate.
Display all available bars - Strategy calculation on all available bars (based on the available amount of data with reduced resolution (set in Calculation timeframe)).
Ticks Per Row - Sets the price step, calculated by multiplying the entered value by syminfo.mintick.
Auto - The automatic "Ticks Per Row" calculation is based on the first available bar and applied to subsequent bars.
Max row - sets the acceptable number of rows within a bar.
Imbalance Percent - A percentage coefficient to determine the Imbalance of price levels.
Stacked levels - And minimum number of consecutive Imbalance levels required to draw extended lines.
If you have suggestions for improving the strategy and adding new conditions for entering and exiting the trade, please write).
Big RunnerPresenting the "Big Runner" technique, dubbed "Sprinter," which is intended to help traders looking for momentum chances recognise important market swings. This approach maximises profit potential while controlling risk by using trend ribbons and moving averages to identify entry and exit locations.
Important characteristics:
Moving Averages: To determine the direction of the underlying trend, moving averages, both rapid and slow, are used. Depending on their preferred trading strategy, traders can alter the duration of these averages.
Trend Ribbon: Shows phases of bullish and bearish momentum by using a ribbon indicator to visualise the strength of the trend. Trend transitions are simple to spot for traders so they can make wise decisions.
Buy and Sell Signals: This tool generates buy and sell signals that indicate possible entry and exit opportunities based on the crossing and crossunder of moving averages.
Stop Loss/Take Profit Management: This feature enables traders to successfully apply risk management methods by giving them the ability to set stop loss and take profit levels as a percentage of the entry price.
Dynamic Position Sizing: Optimises capital allocation for every trade by dynamically calculating position size depending on leverage and portfolio proportion.
Implementation:
Long Entry: Started when a bullish trend is indicated by a price cross above the fast and slow moving averages. To control risk and lock in earnings, stop loss and take profit thresholds are established appropriately.
Short Entry: Indicates a bearish trend when the price crosses below both moving averages. The concepts of risk management are similar, with dynamic calculations used to determine take-profit and stop-loss levels.
Extra Personalisation:
Take Profit/Stop Loss Management: Provides the ability to select a take profit and stop loss
API Integration: This feature improves execution flexibility and efficiency by enabling traders to include custom parameters for automated trading.
Notice:
Trading entails risk, and performances in the past do not guarantee future outcomes. Before making any trades with this approach, careful analysis and risk management are necessary.
In summary:
By integrating risk management procedures with technical indicators, the "Big Runner" strategy provides a thorough method for identifying noteworthy market changes and achieving the best possible trading results. Traders can adjust parameters to suit their interests and style of trading, giving them the confidence to traverse volatile market situations.
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.
FluxFilter Trend Strategy [BITsPIP]Hello fellow traders, I'm excited to share with you the FluxFilter Trend Strategy, a trading approach I've developed for those interested in exploring trend-following strategies. My goal was to create something straightforward and accessible, so traders looking to refine their portfolios can easily integrate its features. By the end of this guide, I hope you'll have a solid grasp of how the FluxFilter Trend Strategy functions, appreciate its benefits, understand its potential drawbacks, and see how it might fit into various trading contexts.
I) Overview
The FluxFilter Trend Strategy is tailored to align with the market's long-term trend. It examines the price data from the previous year to gauge the market's overall trajectory by employing moving averages. Subsequently, within shorter timeframes, the strategy utilizes a combination of modified Supertrend, Hull Suite, and various trend-following and filtering techniques to generate buy or sell signals. Although its advanced take profit and stop loss mechanisms might initially present a learning curve, they are integral to the strategy's effectiveness. They are designed to secure gains by capturing prevailing trends and mitigating the impact of false reversal signals.
II) Deep Backtesting
Deep backtesting stands as a cornerstone in the development of trading strategies, offering a robust method for traders to assess the performance of their strategy against historical data. This process yields a retrospective view, illustrating how the strategy might have navigated through past market fluctuations, thereby shedding light on its potential robustness and areas for refinement. However, it's crucial to acknowledge that a strategy's performance can be influenced by a myriad of factors including market dynamics, the chosen timeframe, and the inherent attributes of the traded asset. Consequently, it's advisable to conduct thorough backtesting under various conditions to ascertain the strategy's reliability before applying it to actual trading scenarios.
III) Benefits
A primary advantage of the FluxFilter Trend Strategy is its proficiency in discerning genuine market trends from mere price fluctuations, thereby avoiding premature or uncertain trades. Unlike approaches that take high risks on speculative trades, this strategy prioritizes a high degree of confidence in the direction of the trade. It meticulously waits for a clear confirmation of the market trend. Once this certainty is established, the strategy promptly generates trade signals, ensuring that traders are positioned to capitalize on optimal market entry points without delay. This approach not only enhances the potential for profit but also aligns with a disciplined and methodical trading ethos.
IV) Applications
FluxFilter Trend Strategy can be applied across various timeframes, with a particular efficacy in those under 15 minutes. Its adaptable framework means it can be customized to cater to a variety of asset classes, encompassing stocks, commodities, forex, and cryptocurrencies. Initially, the strategy was specifically calibrated for low-volatile cryptocurrencies, as reflected in the default settings for stop loss and take profit values. It's important to recognize that the unique volatility and trend patterns of your selected market necessitate careful adjustments to these parameters. This fine-tuning of profit targets and stop loss thresholds is crucial for aligning the strategy with the specific dynamics of your chosen market, which I will discuss shortly.
V) Strategy's Logic
1. Trend Identification: My conviction lies in the power of trend trading to yield long-term gains. Central to the FluxFilter Trend Strategy is the Hull Suite indicator, a tool developed by InSilico, serving as one of the confirmation indicators. This indicator acts as a compass for trend direction; a price residing above the Hull Suite line signals an uptrend, potentially marking an entry point for a buy position or confirming it. In contrast, a price positioned below this line suggests a downtrend, potentially indicating a strategic moment to sell or confirming the sell.
2. Noise Reduction: The financial markets are known for their 'noise'—short-lived price movements that can obscure the true market direction. The FluxFilter Trend Strategy is designed to sift through this noise, thereby facilitating more lucid and informed trading decisions. It employs a set of straightforward yet innovative techniques to single out significant misleading fluctuations. This is achieved by analyzing recent bars to spot bars with unusually large bodies, which often represent misleading market noise.
3. Risk Management: A key facet of the strategy is its emphasis on pragmatic risk management. Traders are empowered to establish practical stop-loss and take-profit levels, tailoring these crucial parameters to the specific market they are engaging in. This customization is instrumental in optimizing long-term profitability, ensuring that the strategy adapts fluidly to the unique characteristics and volatility patterns of different trading environments.
VI) Strategy's Input Settings and Default Values
1. Modified Supertrend
i. Factor: Serving as a multiplier in the Average True Range (ATR) calculation, this parameter adjusts the distance of the Supertrend line relative to the price chart. Elevating the factor value widens the gap between the Supertrend line and price, offering a more conservative stance. On the flip side, diminishing the factor value pulls the Supertrend line closer to the price action, heightening its sensitivity. While the preset value is 1, you have the flexibility to modify this to suit your trading approach.
ii. ATR Length: This defines the count of bars that are incorporated into the ATR computation, directly influencing the Supertrend's adaptability to market changes. With a default setting of 30 bars, it strikes a balance, smoothing over short-term fluctuations while maintaining a meaningful sensitivity to market trends. Adjusting this parameter allows you to tailor the indicator's responsiveness to suit your trading strategy, considering the volatility and behavioral patterns of the asset you are trading.
2. Hull Suite
i. Hull Suite Length: Designed for capturing long-term trends, the Hull Suite Length is configured at 1000. Functioning comparably to moving averages, the Hull Suite features upper and lower bands, though these are not employed in our current strategy.
ii. Length Multiplier: It's advisable to maintain a minimal value for the Length Multiplier, prioritizing the optimization of the Hull Suite Length. Presently, it is set to 1.
3. Filtering Indicators
i. Fluctuation Filtering Percentage: It's advisable to set this parameter to ten times the size of the average bar in your specific market, as this helps effectively mitigate the impact of market fluctuations. While the initial default is 0.4(%), based on the BTCUSDT market, it's crucial to adjust this figure to align with the characteristics of different assets or markets you're trading in.
ii. Fluctuation Filtering Bars: This parameter designates the count of preceding bars to consider when assessing market fluctuations. It's fully customizable, allowing you to tailor it based on your market insights. The preset default is 3, a balance chosen to minimize susceptibility to potentially misleading signals.
iii. Trend Confirmation Percentage: This metric is pivotal for verifying the viability of a trend post-entry. If the trade doesn't achieve this percentage in profit, it indicates a deviation from the expected trend. Under such circumstances, it may be prudent to exit the trade prematurely rather than awaiting the stop-loss trigger. It's recommended to set this parameter at half the size of the average candle body for the market you're analyzing. The initial default is set at 0.2(%).
4. StopLoss and TakeProfit
i. StopLoss and TakeProfit Settings: Two distinct approaches are available. Semi-Automatic StopLoss/TakeProfit Setting and Manual StopLoss/TakeProfit Setting. The Semi-Automatic mode streamlines the process by allowing you to input values for a 5-minute timeframe, subsequently auto-adjusting these values across various timeframes, both lower and higher. Conversely, the Manual mode offers full control, enabling you to meticulously define TakeProfit values for each individual timeframe.
ii. TakeProfit Threshold # and TakeProfit Value #: Imagine this mechanism as an ascending staircase. Each step represents a range, with the lower boundary (TakeProfit Value) designed to close the trade upon being reached, and the upper boundary (TakeProfit Threshold) upon being hit, propelling the trade to the next level, and forming a new range. This stair-stepping approach enhances risk management and has the potential to increase profitability. The pre-set configurations are tailored for volatile markets, such as BTCUSDT. It's advisable to devote time to tailoring these settings to your specific market, aiming to achieve optimal results based on backtesting.
iii. StopLoss Value: In line with its name, this value marks the limit of loss you're prepared to accept should the market trend go against your expectations. It's crucial to note that once your asset reaches the first TakeProfit range, the initial StopLoss value becomes obsolete, supplanted by the first TakeProfit Value. The default StopLoss value is pegged at 1.8(%), a figure worth considering in your trading strategy.
VII) Entry Conditions
The principal element that triggers the signal is the Modified Supertrend. Additional indicators serve as confirmatory tools. Nonetheless, to refine your strategy effectively, it's crucial to fine-tune the parameters. This involves adjusting input variables such as take profit levels, threshold parameters, and the filtering values discussed previously.
VIII) Exit Conditions
The strategy stipulates exit conditions primarily governed by stop loss and take profit parameters. On infrequent occasions, if the trend lacks confirmation post-entry, the strategy mandates an exit upon the issuance of a reverse signal (whether confirmed or unconfirmed) by the strategy itself.
Good Luck!!
The Flash-Strategy with Minervini Stage Analysis QualifierThe Flash-Strategy (Momentum-RSI, EMA-crossover, ATR) with Minervini Stage Analysis Qualifier
Introduction
Welcome to a comprehensive guide on a cutting-edge trading strategy I've developed, designed for the modern trader seeking an edge in today's dynamic markets. This strategy, which I've honed through my years of experience in the trading arena, stands out for its unique blend of technical analysis and market intuition, tailored specifically for use on the TradingView platform.
As a trader with a deep passion for the financial markets, my journey began several years ago, driven by a relentless pursuit of a trading methodology that is both effective and adaptable. My background in trading spans various market conditions and asset classes, providing me with a rich tapestry of experiences from which to draw. This strategy is the culmination of that journey, embodying the lessons learned and insights gained along the way.
The cornerstone of this strategy lies in its ability to generate precise long signals in a Stage 2 uptrend and equally accurate short signals in a Stage 4 downtrend. This approach is rooted in the principles of trend following and momentum trading, harnessing the power of key indicators such as the Momentum-RSI, EMA Crossover, and Average True Range (ATR). What sets this strategy apart is its meticulous design, which allows it to adapt to the ever-changing market conditions, providing traders with a robust tool for navigating both bullish and bearish scenarios.
This strategy was born out of a desire to create a trading system that is not only highly effective in identifying potential trade setups but also straightforward enough to be implemented by traders of varying skill levels. It's a reflection of my belief that successful trading hinges on clarity, precision, and disciplined execution. Whether you are a seasoned trader or just beginning your journey, this guide aims to provide you with a comprehensive understanding of how to harness the full potential of this strategy in your trading endeavors.
In the following sections, we will delve deeper into the mechanics of the strategy, its implementation, and how to make the most out of its features. Join me as we explore the nuances of a strategy that is designed to elevate your trading to the next level.
Stage-Specific Signal Generation
A distinctive feature of this trading strategy is its focus on generating long signals exclusively during Stage 2 uptrends and short signals during Stage 4 downtrends. This approach is based on the widely recognized market cycle theory, which divides the market into four stages: Stage 1 (accumulation), Stage 2 (uptrend), Stage 3 (distribution), and Stage 4 (downtrend). By aligning the signal generation with these specific stages, the strategy aims to capitalize on the most dynamic and clear-cut market movements, thereby enhancing the potential for profitable trades.
1. Long Signals in Stage 2 Uptrends
• Characteristics of Stage 2: Stage 2 is characterized by a strong uptrend, where prices are consistently rising. This stage typically follows a period of accumulation (Stage 1) and is marked by increased investor interest and bullish sentiment in the market.
• Criteria for Long Signal Generation: Long signals are generated during this stage when the technical indicators align with the characteristics of a Stage 2 uptrend.
• Rationale for Stage-Specific Signals: By focusing on Stage 2 for long trades, the strategy seeks to enter positions during the phase of strong upward momentum, thus riding the wave of rising prices and investor optimism. This stage-specific approach minimizes exposure to less predictable market phases, like the consolidation in Stage 1 or the indecision in Stage 3.
2. Short Signals in Stage 4 Downtrends
• Characteristics of Stage 4: Stage 4 is identified by a pronounced downtrend, with declining prices indicating prevailing bearish sentiment. This stage typically follows the distribution phase (Stage 3) and is characterized by increasing selling pressure.
• Criteria for Short Signal Generation: Short signals are generated in this stage when the indicators reflect a strong bearish trend.
• Rationale for Stage-Specific Signals: Targeting Stage 4 for shorting capitalizes on the market's downward momentum. This tactic aligns with the natural market cycle, allowing traders to exploit the downward price movements effectively. By doing so, the strategy avoids the potential pitfalls of shorting during the early or late stages of the market cycle, where trends are less defined and more susceptible to reversals.
In conclusion, the strategy’s emphasis on stage-specific signal generation is a testament to its sophisticated understanding of market dynamics. By tailoring the long and short signals to Stages 2 and 4, respectively, it leverages the most compelling phases of the market cycle, offering traders a clear and structured approach to aligning their trades with dominant market trends.
Strategy Overview
At the heart of this trading strategy is a philosophy centered around capturing market momentum and trend efficiency. The core objective is to identify and capitalize on clear uptrends and downtrends, thereby allowing traders to position themselves in sync with the market's prevailing direction. This approach is grounded in the belief that aligning trades with these dominant market forces can lead to more consistent and profitable outcomes.
The strategy is built on three foundational components, each playing a critical role in the decision-making process:
1. Momentum-RSI (Relative Strength Index): The Momentum-RSI is a pivotal element of this strategy. It's an enhanced version of the traditional RSI, fine-tuned to better capture the strength and velocity of market trends. By measuring the speed and change of price movements, the Momentum-RSI provides invaluable insights into whether a market is potentially overbought or oversold, suggesting possible entry and exit points. This indicator is especially effective in filtering out noise and focusing on substantial market moves.
2. EMA (Exponential Moving Average) Crossover: The EMA Crossover is a crucial component for trend identification. This strategy employs two EMAs with different timeframes to determine the market trend. When the shorter-term EMA crosses above the longer-term EMA, it signals an emerging uptrend, suggesting a potential long entry. Conversely, a crossover below indicates a possible downtrend, hinting at a short entry opportunity. This simple yet powerful tool is key in confirming trend directions and timing market entries.
3. ATR (Average True Range): The ATR is instrumental in assessing market volatility. This indicator helps in understanding the average range of price movements over a given period, thus providing a sense of how much a market might move on a typical day. In this strategy, the ATR is used to adjust stop-loss levels and to gauge the potential risk and reward of trades. It allows for more informed decisions by aligning trade management techniques with the current volatility conditions.
The synergy of these three components – the Momentum-RSI, EMA Crossover, and ATR – creates a robust framework for this trading strategy. By combining momentum analysis, trend identification, and volatility assessment, the strategy offers a comprehensive approach to navigating the markets. Whether it's capturing a strong trend in its early stages or identifying a potential reversal, this strategy aims to provide traders with the tools and insights needed to make well-informed, strategically sound trading decisions.
Detailed Component Analysis
The efficacy of this trading strategy hinges on the synergistic functioning of its three key components: the Momentum-RSI, EMA Crossover, and Average True Range (ATR). Each component brings a unique perspective to the strategy, contributing to a well-rounded approach to market analysis.
1. Momentum-RSI (Relative Strength Index)
• Definition and Function: The Momentum-RSI is a modified version of the classic Relative Strength Index. While the traditional RSI measures the velocity and magnitude of directional price movements, the Momentum-RSI amplifies aspects that reflect trend strength and momentum.
• Significance in Identifying Trend Strength: This indicator excels in identifying the strength behind a market's move. A high Momentum-RSI value typically indicates strong bullish momentum, suggesting the potential continuation of an uptrend. Conversely, a low Momentum-RSI value signals strong bearish momentum, possibly indicative of an ongoing downtrend.
• Application in Strategy: In this strategy, the Momentum-RSI is used to gauge the underlying strength of market trends. It helps in filtering out minor fluctuations and focusing on significant movements, providing a clearer picture of the market's true momentum.
2. EMA (Exponential Moving Average) Crossover
• Definition and Function: The EMA Crossover component utilizes two exponential moving averages of different timeframes. Unlike simple moving averages, EMAs give more weight to recent prices, making them more responsive to new information.
• Contribution to Market Direction: The interaction between the short-term and long-term EMAs is key to determining market direction. A crossover of the shorter EMA above the longer EMA is an indicator of an emerging uptrend, while a crossover below signals a developing downtrend.
• Application in Strategy: The EMA Crossover serves as a trend confirmation tool. It provides a clear, visual representation of the market's direction, aiding in the decision-making process for entering long or short positions. This component ensures that trades are aligned with the prevailing market trend, a crucial factor for the success of the strategy.
3. ATR (Average True Range)
• Definition and Function: The ATR is an indicator that measures market volatility by calculating the average range between the high and low prices over a specified period.
• Role in Assessing Market Volatility: The ATR provides insights into the typical market movement within a given timeframe, offering a measure of the market's volatility. Higher ATR values indicate increased volatility, while lower values suggest a calmer market environment.
• Application in Strategy: Within this strategy, the ATR is instrumental in tailoring risk management techniques, particularly in setting stop-loss levels. By accounting for the market's volatility, the ATR ensures that stop-loss orders are placed at levels that are neither too tight (risking premature exits) nor too loose (exposing to excessive risk).
In summary, the combination of Momentum-RSI, EMA Crossover, and ATR in this trading strategy provides a comprehensive toolkit for market analysis. The Momentum-RSI identifies the strength of market trends, the EMA Crossover confirms the market direction, and the ATR guides in risk management by assessing volatility. Together, these components form the backbone of a strategy designed to navigate the complexities of the financial markets effectively.
1. Signal Generation Process
• Combining Indicators: The strategy operates by synthesizing signals from the Momentum-RSI, EMA Crossover, and ATR indicators. Each indicator serves a specific purpose: the Momentum-RSI gauges trend momentum, the EMA Crossover identifies the trend direction, and the ATR assesses the market’s volatility.
• Criteria for Signal Validation: For a signal to be considered valid, it must meet specific criteria set by each of the three indicators. This multi-layered approach ensures that signals are not only based on one aspect of market behavior but are a result of a comprehensive analysis.
2. Conditions for Long Positions
• Uptrend Confirmation: A long position signal is generated when the shorter-term EMA crosses above the longer-term EMA, indicating an uptrend.
• Momentum-RSI Alignment: Alongside the EMA crossover, the Momentum-RSI should indicate strong bullish momentum. This is typically represented by the Momentum-RSI being at a high level, confirming the strength of the uptrend.
• ATR Consideration: The ATR is used to fine-tune the entry point and set an appropriate stop-loss level. In a low volatility scenario, as indicated by the ATR, the stop-loss can be set tighter, closer to the entry point.
3. Conditions for Short Positions
• Downtrend Confirmation: Conversely, a short position signal is indicated when the shorter-term EMA crosses below the longer-term EMA, signaling a downtrend.
• Momentum-RSI Confirmation: The Momentum-RSI should reflect strong bearish momentum, usually seen when the Momentum-RSI is at a low level. This confirms the bearish strength of the market.
• ATR Application: The ATR again plays a role in determining the stop-loss level for the short position. Higher volatility, as indicated by a higher ATR, would warrant a wider stop-loss to accommodate larger market swings.
By adhering to these mechanics, the strategy aims to ensure that each trade is entered with a high probability of success, aligning with the market’s current momentum and trend. The integration of these indicators allows for a holistic market analysis, providing traders with clear and actionable signals for both entering and exiting trades.
Customizable Parameters in the Strategy
Flexibility and adaptability are key features of this trading strategy, achieved through a range of customizable parameters. These parameters allow traders to tailor the strategy to their individual trading style, risk tolerance, and specific market conditions. By adjusting these parameters, users can fine-tune the strategy to optimize its performance and align it with their unique trading objectives. Below are the primary parameters that can be customized within the strategy:
1. Momentum-RSI Settings
• Period: The lookback period for the Momentum-RSI can be adjusted. A shorter period makes the indicator more sensitive to recent price changes, while a longer period smoothens the RSI line, offering a broader view of the momentum.
• Overbought/Oversold Thresholds: Users can set their own overbought and oversold levels, which can help in identifying extreme market conditions more precisely according to their trading approach.
2. EMA Crossover Settings
• Timeframes for EMAs: The strategy uses two EMAs with different timeframes. Traders can modify these timeframes, choosing shorter periods for a more responsive approach or longer periods for a more conservative one.
• Source Data: The choice of price data (close, open, high, low) used in calculating the EMAs can be varied depending on the trader’s preference.
3. ATR Settings
• Lookback Period: Adjusting the lookback period for the ATR impacts how the indicator measures volatility. A longer period may provide a more stable but less responsive measure, while a shorter period offers quicker but potentially more erratic readings.
• Multiplier for Stop-Loss Calculation: This parameter allows traders to set how aggressively or conservatively they want their stop-loss to be in relation to the ATR value.
Here are the standard settings:
YinYang RSI Volume Trend StrategyThere are many strategies that use RSI or Volume but very few that take advantage of how useful and important the two of them combined are. This strategy uses the Highs and Lows with Volume and RSI weighted calculations on top of them. You may be wondering how much of an impact Volume and RSI can have on the prices; the answer is a lot and we will discuss those with plenty of examples below, but first…
How does this strategy work?
It’s simple really, when the purchase source crosses above the inner low band (red) it creates a Buy or Long. This long has a Trailing Stop Loss band (the outer low band that's also red) that can be adjusted in the Settings. The Stop Loss is based on a % of the inner low band’s price and by default it is 0.1% lower than the inner band’s price. This Stop Loss is not only a stop loss but it can also act as a Purchase Available location.
You can get back into a trade after a stop loss / take profit has been hit when your Reset Purchase Availability After condition has been met. This can either be at Stop Loss, Entry or None.
It is advised to allow it to reset in case the stop loss was a fake out but the call was right. Sometimes it may trigger stop loss multiple times in a row, but you don’t lose much on stop loss and you gain lots when the call is right.
The Take Profit location is the basis line (white). Take Profit occurs when the Exit Source (close, open, high, low or other) crosses the basis line and then on a different bar the Exit Source crosses back over the basis line. For example, if it was a Long and the bar’s Exit Source closed above the basis line, and then 2 bars later its Exit Source closed below the basis line, Take Profit would occur. You can disable Take Profit in Settings, but it is very useful as many times the price will cross the Basis and then correct back rather than making it all the way to the opposing zone.
Longs:
If for instance your Long doesn’t need to Take Profit and instead reaches the top zone, it will close the position when it crosses above the inner top line (green).
Please note you can change the Exit Source too which is what source (close, open, high, low) it uses to end the trades.
The Shorts work the same way as the Long but just opposite, they start when the purchase source crosses under the inner upper band (green).
Shorts:
Shorts take profit when it crosses under the basis line and then crosses back.
Shorts will Stop loss when their outer upper band (green) is crossed with the Exit Source.
Short trades are completed and closed when its Exit Source crosses under the inner low red band.
So, now that you understand how the strategy works, let’s discuss why this strategy works and how it is profitable.
First we will discuss Volume as we deem it plays a much bigger role overall and in our strategy:
As I’m sure many of you know, Volume plays a huge factor in how much something moves, but it also plays a role in the strength of the movement. For instance, let’s look at two scenarios:
Bitcoin’s price goes up $1000 in 1 Day but the Volume was only 10 million
Bitcoin’s price goes up $200 in 1 Day but the Volume was 40 million
If you were to only look at the price, you’d say #1 was more important because the price moved x5 the amount as #2, but once you factor in the volume, you know this is not true. The reason why Volume plays such a huge role in Price movement is because it shows there is a large Limit Order battle going on. It means that both Bears and Bulls believe that price is a good time to Buy and Sell. This creates a strong Support and Resistance price point in this location. If we look at scenario #2, when there is high volume, especially if it is drastically larger than the average volume Bitcoin was displaying recently, what can we decipher from this? Well, the biggest take away is that the Bull’s won the battle, and that likely when that happens we will see bullish movement continuing to happen as most of the Bears Limit Orders have been fulfilled. Whereas with #2, when large price movement happens and Bitcoin goes up $1000 with low volume what can we deduce? The main takeaway is that Bull’s pressured the price up with Market Orders where they purchased the best available price, also what this means is there were very few people who were wanting to sell. This generally dictates that Whale Limit orders for Sells/Shorts are much higher up and theres room for movement, but it also means there is likely a whale that is ready to dump and crash it back down.
You may be wondering, what did this example have to do with YinYang RSI Volume Trend Strategy? Well the reason we’ve discussed this is because we use Volume multiple times to apply multiplications in our calculations to add large weight to the price when there is lots of volume (this is applied both positively and negatively). For instance, if the price drops a little and there is high volume, our strategy will move its bounds MUCH lower than the price actually dropped, and if there was low volume but the price dropped A LOT, our strategy will only move its bounds a little. We believe this reflects higher levels of price accuracy than just price alone based on the examples described above.
Don’t believe us?
Here is with Volume NOT factored in (VWMA = SMA and we remove our Volume Filter calculation):
Which produced -$2880 Profit
Here is with our Volume factored in:
Which produced $553,000 (55.3%)
As you can see, we wen’t from $-2800 profit with volume not factored to $553,000 with volume factored. That's quite a big difference! (Please note previous success does not predict future success we are simply displaying the $ amounts as example).
Now how about RSI and why does it matter in this strategy?
As I’m sure most of you are aware, RSI is one of the leading indicators used in trading. For this reason we figured it would only make sense to incorporate it into our calculations. We fiddled with RSI for quite awhile and sometimes what logically seems to be the right way to use it isn’t. Now, because of this, our RSI calculation is a little odd, but basically what we’re doing is we calculate the RSI, then turn it into a percentage (between 0-1) that can easily be multiplied to the price point we need. The price point we use is the difference between our high purchase zone and our low purchase zone. This allows us to see how much price movement there is between zones. We multiply our zone size with our RSI multiplication and we get the amount we will add +/- to our basis line (white line). This officially creates the NEW high and low purchase zones that we are actually using and displaying in our trades.
If you found that confusing, here are some examples to why it is an important calculation for this strategy:
Before RSI factored in:
Which produced 27.8% Profit
After RSI factored in:
Which produced 553% Profit
As you can see, the RSI makes not only the purchase zones more accurate, but it also greatly increases the profit the strategy is able to make. It also helps ensure an relatively linear profit slope so you know it is reliable with its trades.
This strategy can work on pretty much anything, but you should tweak the values a bit for each pair you are trading it with for best results.
We hope you can find some use out of this simple but effective strategy, if you have any questions, comments or concerns please let us know.
HAPPY TRADING!
[tradinghook] - Renko Trend Reversal Strategy V2Title: Renko Trend Reversal Strategy
Short Title: - Renko TRS
> Special thanks to for manually calculating `renkoClose` and `renkoOpen` values in order to remove the infamous repaint issue
Description:
The Renko Trend Reversal Strategy ( - Renko TRS) is a powerful and original trading approach designed to identify trend reversals in financial markets using Renko charts. Renko charts differ from traditional time-based charts, as they focus solely on price movements and ignore time, resulting in a clearer representation of market trends. This strategy leverages Renko charts in conjunction with the Average True Range (ATR) to capture trend reversals with high precision and effectiveness.
Key Concepts:
Renko Charts: Renko charts are unique chart types that only plot price movements beyond a predefined brick size, ignoring time and noise. By doing so, they provide a more straightforward depiction of market trends, eliminating insignificant price fluctuations and making it easier to spot trend reversals.
Average True Range (ATR): The strategy utilizes the ATR indicator, which measures market volatility and provides valuable insights into potential price movements. By setting the brick size of the Renko chart based on the ATR, the strategy adapts to changing market conditions, ensuring optimal performance across various instruments and timeframes.
How it Works:
The Renko Trend Reversal Strategy is designed to identify trend reversal points and generate buy or sell signals based on the following principles:
Renko Brick Generation: The strategy calculates the ATR over a user-defined period (ATR Length) and utilizes this value to determine the size of Renko bricks. Larger ATR values result in bigger bricks, capturing higher market volatility, while smaller ATR values create smaller bricks for calmer market conditions.
Buy and Sell Signals: The strategy generates buy signals when the Renko chart's open price crosses below the close price, indicating a potential bullish trend reversal. Conversely, sell signals are generated when the open price crosses above the close price, suggesting a bearish trend reversal. These signals help traders identify potential entry points to capitalize on market movements.
Stop Loss and Take Profit Management: To manage risk and protect profits, the strategy incorporates dynamic stop-loss and take-profit levels. The stop-loss level is calculated as a percentage of the Renko open price, ensuring a fixed risk amount for each trade. Similarly, the take-profit level is set as a percentage of the Renko open price to secure potential gains.
How to Use:
Inputs: Before using the strategy, traders can customize several parameters to suit their trading preferences. These inputs include the ATR Length, Stop Loss Percentage, Take Profit Percentage, Start Date, and End Date. Adjusting these settings allows users to optimize the strategy for different market conditions and risk tolerances.
Chart Setup: Apply the - Renko TRS script to your desired financial instrument and timeframe on TradingView. The Renko chart will dynamically adjust its brick size based on the ATR Length parameter.
Buy and Sell Signals: The strategy will generate green "Buy" labels below bullish reversal points and red "Sell" labels above bearish reversal points on the Renko chart. These labels indicate potential entry points for long and short trades, respectively.
Risk Management: The strategy automatically calculates stop-loss and take-profit levels based on the user-defined percentages. Traders can ensure proper risk management by using these levels to protect their capital and secure profits.
Backtesting and Optimization: Before implementing the strategy live, traders are encouraged to backtest it on historical data to assess its performance across various market conditions. Adjust the input parameters through optimization to find the most suitable settings for specific instruments and timeframes.
Conclusion:
The - Renko Trend Reversal Strategy is a unique and versatile tool for traders looking to identify trend reversals with greater accuracy. By combining Renko charts and the Average True Range (ATR) indicator, this strategy adapts to market dynamics and provides clear entry and exit signals. Traders can harness the power of Renko charts while effectively managing risk through stop-loss and take-profit levels. Before using the strategy in live trading, backtesting and optimization will help traders fine-tune the parameters for optimal performance. Start exploring trend reversals with the - Renko TRS and take your trading to the next level.
(Note: This description is for illustrative purposes only and does not constitute financial advice. Traders are advised to thoroughly test the strategy and exercise sound risk management practices when trading in real markets.)
Previous Day High Low Strategy only for LongWelcome to the "Previous Day High Low Strategy only for Long"!.
This strategy aims to identify potential long trading opportunities based on the previous day's high and low prices, along with certain market strength conditions.
Key Features:
Entry Conditions: The strategy triggers a long position when the current day's closing price crosses above the previous day's high or low.
Market Strength Filter: The strategy incorporates a market strength filter using the Average Directional Index (ADX). It only takes long positions when the ADX value is above a specific threshold and when there is a predominance of upward movement.
Trade Timing: The strategy operates within a specified trade window, starting at 09:30 and ending at 15:10. Positions are closed at 15:15 if still active.
Risk Management: The strategy employs dynamic stop-loss and profit-taking levels based on a user-defined Max Profit value. It has three profit targets (T1, T2, T3) and a stop-loss level to manage risk effectively.
Rules:
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Respect the moderators' work and address complaints privately.
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Do not attempt to manipulate the reputation system or engage in like-for-like schemes.
Explanation of how the strategy works
1. Previous Day's High and Low (HH, LL):
In this strategy, we start by obtaining the high and low prices of the previous day (not the current day) using the request.security function. This function allows us to access historical data for a specific time frame. The high and low prices are stored in the variables HH and LL, respectively.
2. Entry Conditions:
The strategy uses two conditions to trigger a long position:
Condition 1 (Long Condition 1): If the closing price of the current day crosses above the previous day's high (HH), it generates a long signal. This is achieved using the ta.crossover function, which detects when a crossover occurs.
Condition 2 (Long Condition 2): Similarly, if the closing price of the current day crosses above the previous day's low (LL), it also generates a long signal.
Combined Condition: To take long positions, the strategy combines both long conditions using the logical OR operator (or). This means that if either of the two conditions is met, a long position will be initiated.
3. Market Strength Filter:
The strategy also includes a filter based on the Average Directional Index (ADX) to gauge the market's strength before taking long positions. The ADX measures the strength of a trend in the market. The higher the ADX value, the stronger the trend.
Calculation of ADX: The ADX is calculated using the adx function, which takes two parameters: LWdilength (DMI Length) and LWadxlength (ADX period).
Strength Condition (strength_up): The strategy requires that the ADX value should be above a threshold (11 in this case) and that there is a predominance of upward movement (up > down) before initiating a long position. The LWADX value is multiplied by 2.5 and compared to the highest value of LWADX from the last 4 periods using ta.highest(LWADX , 4). If these conditions are met, the variable strength_up is set to true.
Combined Condition: The strength_up condition is then combined with the long conditions using the logical AND operator (and). This means that the strategy will only take a long position if both the long conditions and the market strength condition are met.
4. Trade Timing:
The strategy sets a specific trade window between 09:30 and 15:10. It will only execute trades within this time frame (TradeTime).
5. Risk Management:
The strategy implements dynamic stop-loss (SL) and profit-taking levels (T1, T2, T3) based on a user-defined Max Profit value. The stop-loss is set as a percentage of the Max Profit value. As the position moves in favor of the trader, the profit targets are adjusted accordingly.
6. Position Management:
The strategy uses the strategy.entry function to enter long positions based on the combined entry conditions. Once a position is open, the script uses strategy.exit to define the exit condition when either the profit target or stop-loss level is hit. The strategy.close function is used to close any open position at the end of the trade window (15:15).
7. Plotting:
The strategy uses the plot function to visualize the previous day's high and low prices, as well as the stop-loss (SL) and profit-taking (T1, T2, T3) levels on the chart.
Overall, the "Previous Day High Low Strategy only for Long" aims to identify potential long trading opportunities based on the previous day's price action and market strength conditions. However, as with any trading strategy, it's essential to thoroughly test it and consider risk management before applying it to real-world trading scenarios.
Disclaimer:
The information presented by this strategy is for educational purposes only and should not be considered as investment advice. The strategy is not designed for qualified investors. Always conduct your own research and consult with a financial advisor before making any trading decisions.
Remember, the success of any trading strategy depends on various factors, including market conditions, risk management, and individual trading skills. Past performance is not indicative of future results.
[tradinghook] - Renko Trend Reversal Strategy - Renko Trend Reversal Strategy
Short Title: - Renko TRS
Description:
The Renko Trend Reversal Strategy ( - Renko TRS) is a powerful and original trading approach designed to identify trend reversals in financial markets using Renko charts. Renko charts differ from traditional time-based charts, as they focus solely on price movements and ignore time, resulting in a clearer representation of market trends. This strategy leverages Renko charts in conjunction with the Average True Range (ATR) to capture trend reversals with high precision and effectiveness.
Key Concepts:
Renko Charts: Renko charts are unique chart types that only plot price movements beyond a predefined brick size, ignoring time and noise. By doing so, they provide a more straightforward depiction of market trends, eliminating insignificant price fluctuations and making it easier to spot trend reversals.
Average True Range (ATR): The strategy utilizes the ATR indicator, which measures market volatility and provides valuable insights into potential price movements. By setting the brick size of the Renko chart based on the ATR, the strategy adapts to changing market conditions, ensuring optimal performance across various instruments and timeframes.
How it Works:
The Renko Trend Reversal Strategy is designed to identify trend reversal points and generate buy or sell signals based on the following principles:
Renko Brick Generation: The strategy calculates the ATR over a user-defined period (ATR Length) and utilizes this value to determine the size of Renko bricks. Larger ATR values result in bigger bricks, capturing higher market volatility, while smaller ATR values create smaller bricks for calmer market conditions.
Buy and Sell Signals: The strategy generates buy signals when the Renko chart's open price crosses below the close price, indicating a potential bullish trend reversal. Conversely, sell signals are generated when the open price crosses above the close price, suggesting a bearish trend reversal. These signals help traders identify potential entry points to capitalize on market movements.
Stop Loss and Take Profit Management: To manage risk and protect profits, the strategy incorporates dynamic stop-loss and take-profit levels. The stop-loss level is calculated as a percentage of the Renko open price, ensuring a fixed risk amount for each trade. Similarly, the take-profit level is set as a percentage of the Renko open price to secure potential gains.
How to Use:
Inputs: Before using the strategy, traders can customize several parameters to suit their trading preferences. These inputs include the ATR Length, Stop Loss Percentage, Take Profit Percentage, Start Date, and End Date. Adjusting these settings allows users to optimize the strategy for different market conditions and risk tolerances.
Chart Setup: Apply the - Renko TRS script to your desired financial instrument and timeframe on TradingView. The Renko chart will dynamically adjust its brick size based on the ATR Length parameter.
Buy and Sell Signals: The strategy will generate green "Buy" labels below bullish reversal points and red "Sell" labels above bearish reversal points on the Renko chart. These labels indicate potential entry points for long and short trades, respectively.
Risk Management: The strategy automatically calculates stop-loss and take-profit levels based on the user-defined percentages. Traders can ensure proper risk management by using these levels to protect their capital and secure profits.
Backtesting and Optimization: Before implementing the strategy live, traders are encouraged to backtest it on historical data to assess its performance across various market conditions. Adjust the input parameters through optimization to find the most suitable settings for specific instruments and timeframes.
Conclusion:
The - Renko Trend Reversal Strategy is a unique and versatile tool for traders looking to identify trend reversals with greater accuracy. By combining Renko charts and the Average True Range (ATR) indicator, this strategy adapts to market dynamics and provides clear entry and exit signals. Traders can harness the power of Renko charts while effectively managing risk through stop-loss and take-profit levels. Before using the strategy in live trading, backtesting and optimization will help traders fine-tune the parameters for optimal performance. Start exploring trend reversals with the - Renko TRS and take your trading to the next level.
(Note: This description is for illustrative purposes only and does not constitute financial advice. Traders are advised to thoroughly test the strategy and exercise sound risk management practices when trading in real markets.)
METRIC-TREND-TRADERThis script is a Fully Automated trading script meant to be used with "Oanda" broker and the plug-ins for algorithmic trading automation.( FOREX ONLY)
This script is meant to capture "TREND FOLLOWING " for intraday charts (1hour) preferably and will hold for days / weeks .trading on forex markets.
(The combination of indicators includes a short high and low price channel and a longer term high and low price channel)
This script is original in description as being automated to try and capture dynamic trending markets with both long and short fractal price channels. although trend trading is not an original concept. trend trading with this dynamic indicator allows the user visualize both short term and longer term price action at the same time, helping to make better trading decisions. the channels are designed to buy breakouts in the direction of the longer term trend while trailing stop a built-in stop loss that allows normal market movement while attempting to lock in flexible profits.
The concept of this indicator is be able to quickly visualize trends by high lighting the large green areas beneath price "when trending long" which is the difference between the (user defined) short term lows and the (user defined) Long period price lows.
For "down trending" markets a large red area above price will be displayed and this is the difference between the (user defined) short term highs and the (user defined) long term highs.
This strategy uses a lower than reward profile to jump in direction of market moves for continuation,
(1 risk to 4 reward)
in the likelihood the instrument will continue (example) 200 pips before it reverts 50 pips in the counter direction.
This strategy should only be used in markets that you believe are "TRENDING" at the time of trading otherwise you risk trend trading a range market.
This script uses a (user defined period) of short term high and low price ( green/red color) and (user defined period) Long Term high and low price (green/red) chosen in the indicator settings menu.
The default parameters are 10 with a (minimum of 1 and maximum of 10000) for the short term channel and 50 with a (minimum of 1 and maximum of 10000) for the long term price channel , the default parameters = roughly 2 days "long term" and 10 hours "short term" of price action on the (1 hour) chart.
Strategy entries and exits , for Long trades the trade will be entered if the short term high crosses above the Long Term high and the Short term low is not equal to the Long term low . the trade will exit if profit or stop loss are hit or if the Short term low crosses under the long term low.
For Short trades the trade will enter short if , the short term low crosses under the long term low and the short term high is not equal to the long term high. the trade will exit if profit or stop loss are hit or the short term high crosses over the long term high
"The default parameters should be kept unless you fully understand the complete strategy"
There are two very important inputs to be selected at the user setting menu "Long Only " and "Short Only" if you are looking to place long trades only select "Long Only" or for short trades select " Short Only" it is not recommended to keep both selected as it will trade both sides!
When the trade is entered a red , a blue and green horizontal dotted line will appear on the chart.
the blue line is the strategy entry price , the red line is the stop loss price , and the green line is the take profit price . the colors will invert if the trade is long or short.
(Setting alerts should be done in the indicator settings menu, and the parameters you chose will determine the stop loss/target and the amount of "units = (position size)" you wish to trade for the (forex only) markets. using "alert() function calls only" is the only alert that should be used with this strategy.
(note : when "alert() function calls only" is set two messages will be sent, one closing any open position in the opposite direction and one placing the new order regardless if you are currently in a trade or not)
Trade targets , stoploss and trade position size are a user defined variables entered in the indicator settings menu. (target pips minimum 0 and a maximum of 1000)(stop pips minimum of 0 and maximum of 1000)
Back test date range is included in the script for back testing different data periods.
the back ground will be colored a transparent navy blue if the period you are looking trading is with in the date range( note: to place live trades the end date will need to be in the future)
this is also adjustable in the settings menu
The avoid spread filter is a user defined time in which the spread is typically higher than average, applying this filter avoids trades in the specified time. When this filter is applied there will be a transparent red back ground color in the specified time.
Back test default setting are equivocal to OANDA:USDJPY
at the time of this publication placing trades with the "Oanda" broker are as follows , USD units = 2000 equal 2000 USD position size . "Oanda" current leverage is 20 to 1 for this particular pair and commission is paid in spread (1.4) pips = 0.19 USD per trade , Margin required for the trade is 100.0 USD , Position sizing = 10% of a 1000 USD account.
OANDA:USDJPY
DZ Strategy ICTThe script presented is a trading strategy called "Breaker Block Strategy with Price Channel". This strategy uses multiple time frames (1 minute, 5 minutes, 15 minutes, 1 hour, and 4 hours) to detect support and resistance areas on the chart.
The strategy uses parameters such as length, deviations, multiplier, Fibonacci level, move lag and volume threshold for each time frame. These parameters are adjustable by the user.
The script then calculates support and resistance levels using the simple moving average (SMA) and standard deviation (STDEV) of closing prices for each time frame.
It also detects "Breaker Blocks" based on price movement from support and resistance levels, as well as trade volume. A Breaker Block occurs when there is a significant breakout of a support or resistance level with high volume.
Buy and sell signals are generated based on the presence of a Breaker Block and price movement from support and resistance levels. When a buy signal is generated, a buy order is placed, and when a sell signal is generated, a sell order is placed.
The script also plots price channels for each time frame, representing resistance and support levels.
Profit limit levels are set for each time range, indicating that the price levels assigned to positions should be closed with a profit. Stop-loss levels are also set to limit losses in the event of canceled price movements.
In summary, this trading strategy uses a combination of Breaker Block detection, support and resistance levels, price channels and profit limit levels to generate buy and sell signals and manage positions on different time ranges.
Premium MTF Layered RSI - Bitcoin Bot [wbburgin]This the premium version of my MTF Layered RSI strategy, which improves significantly on the original strategy (publicly available on my profile). Improvements are below. This strategy will also appear as an overlay on your chart. It is completely non-repainting.
The MTF Layered RSI strategy uses the current timeframe and two configurable higher timeframes to enter a long position when Bitcoin is oversold on all three timeframes, and exit the long position when Bitcoin is overbought on the current timeframe. This hedges against situations where the RSI on higher timeframes never reaches the overbought level and we are left "holding the bag" so to speak with the classic "enter long at oversold and enter short at overbought" strategy.
IMPORTANT: This strategy does not work on ranges. It will work on all timeframes and assets, but does not work on ranges (Renko blocks and some other advanced types of charts).
********** My Background
I am an investor, trader, and entrepreneur with 10 years of cryptocurrency and equity trading experience and founder of two fintech startups. I am a graduate of a prestigious university in the United States and carry broad and inclusive interests in mathematical finance, computer science, machine learning / artificial intelligence, as well as other fields.
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Improvements over the original MTF RSI strategy include:
Filters for Uptrends and Downtrends → The Premium RSI strategy will adjust its buy and sell thresholds depending on whether the instrument is trending. This means that, in uptrends, the Premium strategy will buy more frequently, bringing in potentially greater profit, and in downtrends, the strategy will stop buying altogether. These filters and dynamic buy/sell thresholds have made this strategy more profitable in my backtesting across random timeframes, but I cannot guarantee that the strategy will be profitable for you on the default settings. To that end, I have enabled a number of different configurations that you can change in the settings of the strategy.
Stop Loss / Take Profit Calculation Per Tick → Stop loss and take profit are now both enabled in the script and each has their own alerts. You can specify what type of stop loss or take profit you want: percentage or ATR. If you have alerts configured, you will be alerted mid-bar, instead of at close. This helps prevent loss from abrupt falls in price between closing price and next bar open.
Customizable Alert Messages In-Strategy → In the settings, there will be text boxes where you can create your own alerts. All you will need to do is create an alert in the alert panel on Tradingview and leave the message box blank - if you fill out the alert boxes in the settings, these will automatically populate into your alerts. There are in total eight different customizable alerts messages: Entry, Exit, Stop loss, and Take profit alerts for both Long and Short sides. If you disable stop loss and/or take profit, these alerts will also be disabled. Similarly, if you disable shorts, all short alerts will be disabled.
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Display
Configuring Stop Loss or Take Profit will make their corresponding displays appear.
Separately from the trading boxes, background colors (green, red) signify extended uptrends and downtrends, respectively.
Configuring Alerts
In TradingView desktop, go to the ‘Alerts’ tab on the right panel. Click the “+” button to create a new alert. Select this strategy for the condition and one of the two options that includes alert() function calls. Name the alert what you wish and clear the default message, because your text in the settings will replace this message.
Now that the alert is configured, you can go to the settings of the strategy and fill in your chosen text for the specific alert condition. You will need to check “Long and Short” in the “Trade Direction” setting in order for any Short Alerts to become active. Similarly, you will need to check “Enable Stop Loss” for stop loss alerts to become active and “Enable Take Profit” for take profit alerts to become active.
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Disclaimer
Copyright by wbburgin.
The information contained in my Scripts/Indicators/Algorithms 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.
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Notes on the Strategy Performance below: This is 3% of equity per trade, with a pyramiding number of 3. I did not include fees because Binance US on Bitcoin/USD does not charge fees on the instrument; however, I heavily encourage you to include fees in your backtesting if you use a different brokerage. To mitigate fees, this strategy is designed with a high average %/trade. If your current fees are greater than the strategy's average %/trade, I encourage you to choose a higher RSI period, such as 14 or 28, which will result in less trades but potentially a higher %/trade.
FVG Strategy - Fair Value GapThe Fair Value Gap Strategy (FVG) is a trading approach that relies on price action analysis and involves identifying market inefficiencies or imbalances.
The strategy offers a variety of customizable settings to match your preferences and includes an entry and exit strategy to guide you through trades.
The script operates in the following manner:
It begins by searching for fair-value-gaps and subsequently identifies a break in structure.
The next step involves waiting for the price to retrace within the previously established fair value gap.
Within this gap, there is a Fibonacci retracement that must be reached before placing a stop-order.
Example: GER40, 1min Chart
STOP LOSS & RISK MANAGEMENT
FVG : The stop loss will be set at the end of the fair value gap
Last Swing : The stop loss will be at the last swing high/low
ATR (Average True Range) : The stop loss will be placed one 'Average True Range' away from the entry
TAKE PROFIT
Pips/Points : The stop loss will be set at the chosen amount of pips/points.
RiskReward TP : This is a fixed take profit where you can set a specific risk-to-reward ratio for the trade. For example, you can set a 1:3 risk-to-reward ratio.
Trailing Stop : This is a flexible stop that moves with the market price, allowing you to capture more profit as the trade moves in your favor.
Both : This option combines both the RiskReward TP and Trailing Stop. If the price target is set at a 1:3 risk-to-reward ratio, the trailing stop will move with the price until either the stop or take profit is reached, and the position will be closed completely.
THE FVG SECTION
In the FVG section, you will have the ability to customize your settings based on your specific requirements.
Firstly, you will have the choice of two possible entry options:
Candle Close : This option triggers the order once the candle has completely closed and all the set requirements are met.
Stop Orders : This option triggers the order once all the set requirements are met, even if the candle is still active and has not yet closed.
On top, you can activate the "Pinbar-Trading", that will allow you to take a trade on a pinbar, even when the candle just dipped into the FVG and snapped back.
FAIR VALUE GAP TYPE
On volatile market, it may happen that a massive FVG is created. Thats why we have separated the FVG into 2 different variables.
FVG Type: Normal : This is all regular FVG that meet the requirement of you minimum size range. As example FVG must be minimum 5$ big.
FVG Type: Big : This are all big FVG that meet the minimum set size range. The difference to the "normal" type, the stop loss will be set at 50% of the Big-FVG.
FIBONACCI RETRACEMENT & MARKET STRUCTURE
To refine the FVG strategy, you have three options:
Fibonacci Retracement Value (%) : The FVG strategy employs a Fibonacci retracement, which allows you to trade in the direction of the market movement. To initiate the order, the price must reach a predetermined Fibonacci level and then rebound.
Formation-to-Retracement Countdown: : This option provides you with a specified number of candles to meet the necessary conditions. For example, if the order is not triggered within 20 candles, delete the FVG-Zone and skip the trade to avoid getting caught in a sideways ranging trend.
Structure Lookback : This feature filters out older FVG Zones. You can specify the number of candles that should mark the FVG Zones. Keep in mind that newer and fresher zones will automatically conceal older ones.
Lorentzian Classification Strategy Based in the model of Machine learning: Lorentzian Classification by @jdehorty, you will be able to get into trending moves and get interesting entries in the market with this strategy. I also put some new features for better backtesting results!
Backtesting context: 2022-07-19 to 2023-04-14 of US500 1H by PEPPERSTONE. Commissions: 0.03% for each entry, 0.03% for each exit. Risk per trade: 2.5% of the total account
For this strategy, 3 indicators are used:
Machine learning: Lorentzian Classification by @jdehorty
One Ema of 200 periods for identifying the trend
Supertrend indicator as a filter for some exits
Atr stop loss from Gatherio
Trade conditions:
For longs:
Close price is above 200 Ema
Lorentzian Classification indicates a buying signal
This gives us our long signal. Stop loss will be determined by atr stop loss (white point), break even(blue point) by a risk/reward ratio of 1:1 and take profit of 3:1 where half position will be closed. This will be showed as buy.
The other half will be closed when the model indicates a selling signal or Supertrend indicator gives a bearish signal. This will be showed as cl buy.
For shorts:
Close price is under 200 Ema
Lorentzian Classification indicates a selling signal
This gives us our short signal. Stop loss will be determined by atr stop loss (white point), break even(blue point) by a risk/reward ratio of 1:1 and take profit of 3:1 where half position will be closed. This will be showed as sell.
The other half will be closed when the model indicates a buying signal or Supertrend indicator gives a bullish signal. This will be showed as cl sell.
Risk management
To calculate the amount of the position you will use just a small percent of your initial capital for the strategy and you will use the atr stop loss or last swing for this.
Example: You have 1000 usd and you just want to risk 2,5% of your account, there is a buy signal at price of 4,000 usd. The stop loss price from atr stop loss or last swing is 3,900. You calculate the distance in percent between 4,000 and 3,900. In this case, that distance would be of 2.50%. Then, you calculate your position by this way: (initial or current capital * risk per trade of your account) / (stop loss distance).
Using these values on the formula: (1000*2,5%)/(2,5%) = 1000usd. It means, you have to use 1000 usd for risking 2.5% of your account.
We will use this risk management for applying compound interest.
> In settings, with position amount calculator, you can enter the amount in usd of your account and the amount in percentage for risking per trade of the account. You will see this value in green color in the upper left corner that shows the amount in usd to use for risking the specific percentage of your account.
> You can also choose a fixed amount, so you will have to activate fixed amount in risk management for trades and set the fixed amount for backtesting.
Script functions
Inside of settings, you will find some utilities for display atr stop loss, break evens, positions, signals, indicators, a table of some stats from backtesting, etc.
You will find the settings for risk management at the end of the script if you want to change something or trying new values for other assets for backtesting.
If you want to change the initial capital for backtest the strategy, go to properties, and also enter the commisions of your exchange and slippage for more realistic results.
In risk managment you can find an option called "Use leverage ?", activate this if you want to backtest using leverage, which means that in case of not having enough money for risking the % determined by you of your account using your initial capital, you will use leverage for using the enough amount for risking that % of your acount in a buy position. Otherwise, the amount will be limited by your initial/current capital
I also added a function for backtesting if you had added or withdrawn money frequently:
Adding money: You can choose how often you want to add money (Monthly, yearly, daily or weekly). Then a fixed amount of money and activate or deactivate this function
Withdraw money: You can choose if you want to withdraw a fixed amount or a percentage of earnings. Then you can choose a fixed amount of money, the period of time and activate or deactivate this function. Also, the percentage of earnings if you choosed this option.
Some other assets where strategy has worked
BTCUSD 4H, 1D
ETHUSD 4H, 1D
BNBUSD 4H
SPX 1D
BANKNIFTY 4H, 15 min
Some things to consider
USE UNDER YOUR OWN RISK. PAST RESULTS DO NOT REPRESENT THE FUTURE.
DEPENDING OF % ACCOUNT RISK PER TRADE, YOU COULD REQUIRE LEVERAGE FOR OPEN SOME POSITIONS, SO PLEASE, BE CAREFULL AND USE CORRECTLY THE RISK MANAGEMENT
Do not forget to change commissions and other parameters related with back testing results!. If you have problems loading the script reduce max bars back number in general settings
Strategies for trending markets use to have more looses than wins and it takes a long time to get profits, so do not forget to be patient and consistent !
Please, visit the post from @jdehorty called Machine Learning: Lorentzian Classification for a better understanding of his script!
Any support and boosts will be well received. If you have any question, do not doubt to ask!
Cloud X MesoHello there fellow Traders!
Thanks for stopping by, so today I will be covering everything you need to to know about this TradingView strategy.
Below I will discuss everything you need to know about this strategy so you can get a full grasp of what the strategy is, the features, what it does, how it works, the benefits of how this strategy can help you, and the results.
What is Cloud X Meso?
-Cloud X Meso is a strategy that consists of 7 indicators to all line up for total confluence to take a buy or sell once all 6 indicators conditions are met. This strategy does not repaint and doesn't require any technical analysis to be used. The strategy can be used on any timeframe, and any instrument.
-I have optimized many different variations for different types of trading instruments of this strategy ready to be used. The difference of this strategy is that these variations do not need any reoptimization to keep up with recent market conditions since there are hardly any inputs used, which prevents common overfitting problems. The main goal was for this strategy to be automated, as well as plug and play or you can officially consider this as set and forever forget.
What does this strategy do?
-The main goal for this strategy is to catch long or short term trends by waiting for all 7 indicators to line up as well as using customized trading times to trade certain sessions where there is high amounts of volume in the market. This strategy doesn't always need to have a clear trending market, since it can also catch short term trends in choppy markets as well. Overall, the strategy tell you when it buys, sells, and exits after all conditions are met.
How does the strategy work?
-The way that this strategy works is when all of the indicators confluences are met. Next, a buy or sell label will print and the candles colors will color blue or red to show that the trade is in the buy or sell position followed along with a magenta colored line which is the trailing stop to follow the trade until the trade exits from the trailing stop being hit or if the strategies exit condition is met.
-The strategy does have a set Take Profit target since it relies on the trailing stop to end the trade. This is beneficial so you can catch any size of a trend move when the strategy is in high volume market sessions. You catch these trends by customizing the settings to toggle on or off certain indicators, functions, configuring a customized trading time, and toggling on or off certain trading days to make a specific approach for fine tuning a pair to trade in a certain time window with high amounts of volume to catch trending moves whether it be a long or short term trend.
Below I will explain each functionality of the strategy for you to better understand the different ways you can adjust the settings of this strategy.
Backtest Settings:
-You can use these settings to determine a start / end date of what results you would like to see in the strategy tester.
-You can determine the $ amount you would like to see on strategy testers results to be in terms of net profit and max drawdown.
-You can choose whether you want the strategy to take buys only, sells only, or buys and sells.
Automation:
-Compatible with Pine Connectors to fully automate this strategy for MT4/5
-It uses a % based risk when placing trades so you won't have to calculate a proper lot size or dollar amount.
-You can also put the symbol of what that strategy will be trading on so you know what pair its trading.
Custom Trading Times:
-When you customize a trading time for the strategy to trade in, the background will turn blue for that specific time window, and you can use the "Session Exit" function to have trades close once the time window ends when toggled on, or you can have the existing trades close on their own when "Session Exit" is toggled off.
Dynamic Trailing:
-The algorithm uses a volatility based indicator to determine proper stop loss placement depending on how volatile the market is. This will prevent you from guesstimating if your stop loss is too big or too small.
-When Dynamic trailing is off, then the strategy will use a Risk Reward based stop loss to trail everytime the trades hits a new Risk Reward target.
-You can also toggle on or off for the stop loss to go to break even once the trade hits a 1:1 Risk Reward.
Directional Bias Settings:
-This indicator is the main directional bias that uses a multi timeframe function to determine the directional bias, you can also use the Exponential Moving Average as a form of directional bias instead, or you can use both of them to work together to find the directional bias. You can also toggle each one on or off
Entry / Exit Settings:
-This indicator also uses a multi timeframe function but it determines the entry and exit for a trade when all confluences are met. You can also toggle the entry and exit functions on or off.
1 Candle Rule:
-This feature is inspired by No Nonsense Forex (NNFX) the main function of this is if your entry doesn't meet all the entry conditions, then the strategy will wait 1 more candle to meet all the entry conditions to take a trade.
No Trade Zone:
-This feature will uses a Volume based indicator to filter out low volume markets. The candles will turn grey to indicate the algorithm not to take trades, and you can also customize the sensitivity of how strong this indicator will filter out the low volume in the markets.
Indicator functions
Each indicator plays a certain role and also meets certain conditions when a buy or sell trade is placed. I will reveal 3 out of 7 of the indicators used to preserve the uniqueness of this strategy but overall, the logic of this strategies main goal is to ride long or short terms trends while getting dynamic Risk Reward trades.
-The first indicator that the strategy uses an Exponential Moving Average that is customizable, and is used as a form of a filter for either a long or short term directional bias to filter out false signals to help the algorithm trade with the trend.
-The second indicator that the strategy uses is an Oscillator which is the Wavetrend and this indicators functionality for the algorithm is used for the its buy and sell signals to line up with all the other indicators for confluence. This indicator can also be toggled on or off for you own preference
-The third indicator used is the Volume indicator, and this is used to give the other indicators the green light to enter a trade if there are high amounts of volume in the market.
What are the benefits of using this algorithm?
Stress Free Trading:
-Once automated, you will no longer need to stare at the charts all day, as well as trying to execute the trades on time or worried that you missed a setup. Or you can choose to take trades manually when a buy or sell signal comes up
Stress Free Risk Management:
-All you have to do is provide a risk % and the algorithm will do the rest of the work calculating the stop loss, exiting trades, etc. No more needing to find the right lot size, or dollar amount, all in all the strategy will manage the trades for you.
Psychology:
-when you choose to have a systematic trading approach, it eliminates a lot bad habits from human nature
What are the results like?
-I have multiple different variations of results of this strategy, but I will share one of the results.
Here is a screenshot below of what this strategy can do from just one of the variations.
The backtest below was done with another variation on simulating a 100k account risking 0.50% per trade.
Thank you for taking the time to read through this whole guide, and I hope this helped you better understand the strategy.
Strategy for UT Bot Alerts indicator Using the UT Bot alerts indicator by @QuantNomad, this strategy was designed for showing an example of how this indicator could be used, also, it has the goal to help some people from a group that use to use this indicator for their trading. Under any circumstance I recommend to use it without testing it before in real time.
Backtesting context: 2020-02-05 to 2023-02-25 of BTCUSD 4H by Tvc. Commissions: 0.03% for each entry, 0.03% for each exit. Risk per trade: 2.5% of the total account
For this strategy, 3 indicators are used:
UT Bot Alerts indicator by Quantnomad
One Ema of 200 periods for indicate the trend
Atr stop loss from Gatherio
Trade conditions:
For longs:
Close price is higher than Atr from UT Bot
Ema from UT Bot cross over Atr from UT Bot.
This gives us our long signal. Stop loss will be determined by atr stop loss (white point), break even(blue point) by a risk/reward ratio of 0.75:1 and take profit of 3:1 where half position will be closed. This will be showed as buy (open long position)
The other half will be closed when close price is lower than Atr and Ema from UT Bot cross under Atr. This will be showed as cl buy (close long position)
For shorts:
Close price is lower than Atr from UT Bot
Ema from UT Bot cross over Atr from UT Bot.
This gives us our short signal. Stop loss will be determined by atr stop loss (white point), break even(blue point) by a risk/reward ratio of 0.75:1 and take profit of 3:1 where half position will be closed. This will be showed as sell (open short position)
The other half will be closed when close price is higher than Atr and Ema from UT Bot cross over Atr. This will be showed as cl sell (close short position)
Risk management
For calculate the amount of the position you will use just a small percent of your initial capital for the strategy and you will use the atr stop loss for this.
Example: You have 1000 usd and you just want to risk 2,5% of your account, there is a long signal at price of 20,000 usd. The stop loss price from atr stop loss is 19,000. You calculate the distance in percent between 20,000 and 19,000. In this case, that distance would be of 5,0%. Then, you calculate your position by this way: (initial or current capital * risk per trade of your account) / (stop loss distance).
Using these values on the formula: (1000*2,5%)/(5,0%) = 500usd. It means, you have to use 500 usd for risking 2.5% of your account.
We will use this risk management for apply compound interest.
In settings, with position amount calculator, you can enter the amount in usd of your account and the amount in percentage for risking per trade of the account. You will see this value in green color in the upper left corner that shows the amount in usd to use for risking the specific percentage of your account.
Script functions
Inside of settings, you will find some utilities for display atr stop loss, break evens, positions, signals, indicators, etc.
You will find the settings for risk management at the end of the script if you want to change something. But rebember, do not change values from indicators, the idea is to not over optimize the strategy.
If you want to change the initial capital for backtest the strategy, go to properties, and also enter the commisions of your exchange and slippage for more realistic results.
In risk managment you can find an option called "Use leverage ?", activate this if you want to backtest using leverage, which means that in case of not having enough money for risking the % determined by you of your account using your initial capital, you will use leverage for using the enough amount for risking that % of your acount in a buy position. Otherwise, the amount will be limited by your initial/current capital
---> Do not forget to deactivate Trades on chart option in style settings for a cleaner look of the chart <---
Some things to consider
USE UNDER YOUR OWN RISK. PAST RESULTS DO NOT REPRESENT THE FUTURE.
DEPENDING OF % ACCOUNT RISK PER TRADE, YOU COULD REQUIRE LEVERAGE FOR OPEN SOME POSITIONS, SO PLEASE, BE CAREFULL AND USE CORRECTLY THE RISK MANAGEMENT
Do not forget to change commissions and other parameters related with back testing results!
Strategies for trending markets use to have more looses than wins and it takes a long time to get profits, so do not forget to be patient and consistent !
---> The strategy can still be improved, you can change some parameters depending of the asset and timeframe like risk/reward for taking profits, for break even, also the main parameters of the UT Bot Alerts <----