BTCUSD with adjustable sl,tpThis strategy is designed for swing traders who want to enter long positions on pullbacks after a short-term trend shift, while also allowing immediate short entries when conditions favor downside movement. It combines SMA crossovers, a fixed-percentage retracement entry, and adjustable risk management parameters for optimal trade execution.
Key Features:
✅ Trend Confirmation with SMA Crossover
The 10-period SMA crossing above the 25-period SMA signals a bullish trend shift.
The 10-period SMA crossing below the 25-period SMA signals a bearish trend shift.
Short trades are only taken if the price is below the 150 EMA, ensuring alignment with the broader trend.
📉 Long Pullback Entry Using Fixed Percentage Retracement
Instead of entering immediately on the SMA crossover, the strategy waits for a retracement before going long.
The pullback entry is defined as a percentage retracement from the recent high, allowing for an optimized entry price.
The retracement percentage is fully adjustable in the settings (default: 1%).
A dynamic support level is plotted on the chart to visualize the pullback entry zone.
📊 Short Entry Rules
If the SMA(10) crosses below the SMA(25) and price is below the 150 EMA, a short trade is immediately entered.
Risk Management & Exit Strategy:
🚀 Take Profit (TP) – Fully customizable profit target in points. (Default: 1000 points)
🛑 Stop Loss (SL) – Adjustable stop loss level in points. (Default: 250 points)
🔄 Break-Even (BE) – When price moves in favor by a set number of points, the stop loss is moved to break-even.
📌 Extra Exit Condition for Longs:
If the SMA(10) crosses below SMA(25) while the price is still below the EMA150, the strategy force-exits the long position to avoid reversals.
How to Use This Strategy:
Enable the strategy on your TradingView chart (recommended for stocks, forex, or indices).
Customize the settings – Adjust TP, SL, BE, and pullback percentage for your risk tolerance.
Observe the plotted retracement levels – When the price touches and bounces off the level, a long trade is triggered.
Let the strategy manage the trade – Break-even protection and take-profit logic will automatically execute.
Ideal Market Conditions:
✅ Trending Markets – The strategy works best when price follows strong trends.
✅ Stocks, Indices, or Forex – Can be applied across multiple asset classes.
✅ Medium-Term Holding Period – Suitable for swing trades lasting days to weeks.
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Risk MeterRisk Meter Indicator for TradingView
The Risk Meter is a powerful market risk assessment tool designed to help traders evaluate the current risk environment using a simple, data-driven score. By analyzing four critical market factors—VIX (volatility index), market breadth, trailing volatility, and credit spreads—the indicator generates a risk score between 0 and 4. This score empowers traders to make informed decisions about hedging, exiting positions, or re-entering the market, with clear visual cues and alerts for intraday monitoring.
What It Does
Calculates a Risk Score: Assigns a score from 0 to 4, where each point reflects an active risk condition based on four market indicators.
Identifies Risk Levels:
A score of 3 or higher indicates a high-risk environment, suggesting traders consider hedging or reducing exposure.
A score of 2 or lower for at least two consecutive days signals a potential opportunity to re-enter the market.
Provides Visual Feedback: Uses color-coded Columns, threshold markers, and a component table for quick interpretation.
Supports Decision-Making: Offers a structured approach to managing risk and timing trades.
How It Works
The Risk Meter aggregates four key risk conditions, each contributing 1 point to the total score when triggered:
Elevated and Rising VIX (Risk 1)
Condition: The VIX is above 18 and higher than it was 20 days ago.
Purpose: Detects increasing market fear or uncertainty.
Market Breadth Dropping (Risk 2)
Condition: Either:
Fewer than 50% of S&P 500 stocks are above their 200-day moving average and fewer than 70% are above their 50-day moving average, or
The 3-day EMA of the 200-day breadth falls below 80% of its 20-day SMA.
Purpose: Identifies weakening participation across the market.
Trailing Volatility (Risk 3)
Condition: The 30-day annualized volatility of the equal-weight S&P 500 (RSP) exceeds 35%.
Purpose: Highlights periods of heightened price instability.
Credit Spreads (Risk 4)
Condition: The price ratio of high-yield bonds (HYG) to Treasuries (TLT or IEF) is lower than it was 20 days ago, indicating widening credit spreads.
Purpose: Signals potential stress in credit markets.
The total risk score is the sum of these conditions (0 to 4). Additionally, the indicator tracks consecutive days with a score of 2 or lower to generate re-entry signals.
How to Read It Intraday
The Risk Meter is built on daily data but can be monitored intraday for real-time insights. Here’s how traders can interpret it:
Risk Score Plot:
Displayed as a step line ranging from 0 to 4.
Colors:
Red: High risk (score ≥ 3) – caution advised.
Green: Re-entry signal – score ≤ 2 for at least two consecutive days (triggered when the count increments from 1 to 2).
Blue: Neutral or low risk (score < 3 without a re-entry signal).
Threshold Lines:
Dashed Gray Line at 3: Marks the high-risk threshold.
Dotted Gray Line at 2: Indicates the low-risk threshold for re-entry signals.
Risk Component Table:
Located in the top-right corner, it lists:
VIX, Breadth, Volatility, and Credit Spreads.
Status: Shows "" (warning, red) if the risk condition is met, or "✓" (safe, blue) if not.
Helps traders pinpoint which factors are driving the score.
Alerts:
High Risk Alert: Triggers when the score moves from < 3 to ≥ 3.
Re-entry Signal Alert: Triggers when the score ≤ 2 for two consecutive days.
Intraday Usage Tips
Check the indicator throughout the day for early signs of risk shifts, especially if the score is near a threshold (e.g., 2 or 3).
Combine with other intraday tools (e.g., price action, volume) since the Risk Meter updates daily but reflects broader market conditions.
How Traders Can Use It
High-Risk Signal (Score ≥ 3):
Consider hedging positions (e.g., with options) or reducing equity exposure to protect against potential downturns.
Re-entry Signal (Score ≤ 2 for 2+ Days):
Look to re-enter the market or increase exposure, as it suggests stabilizing conditions.
Daily Risk Management:
Use the score and table to assess overall market health and adjust strategies accordingly.
Alert-Driven Trading:
Set up alerts to stay notified of critical risk changes without constant monitoring.
Why Use the Risk Meter?
This indicator offers a systematic, multi-factor approach to risk assessment, blending volatility, breadth, and credit market data into an easy-to-read score. Whether you’re an intraday trader or a longer-term investor, the Risk Meter helps you stay proactive, avoid surprises, and time your trades with greater confidence.
Financial Risk Disclaimer for the Risk Meter Tool
Important Notice: The Risk Meter is a market risk assessment tool designed to provide insights into current market conditions based on historical data and predefined indicators. It is intended for informational and educational purposes only and should not be considered financial advice, a recommendation to buy or sell any securities, or a guarantee of future market performance.
Key Considerations
No Guarantee of Accuracy: While the Risk Meter utilizes reliable data sources and established financial metrics, the creators do not guarantee the accuracy, completeness, or timeliness of the information provided. Financial markets are complex and subject to rapid, unpredictable changes, and the tool’s output may not fully reflect all market dynamics.
Market Risks: Trading and investing in financial markets carry significant risks, including the potential loss of principal. Market volatility, economic shifts, and other factors can lead to unexpected outcomes. Past performance is not a reliable indicator of future results, and the Risk Meter’s assessments are based on historical data, not future predictions.
Not a Substitute for Professional Advice: The Risk Meter is not intended to replace personalized financial guidance. Users are strongly encouraged to consult a qualified financial advisor, perform their own research, and evaluate their personal financial situation, risk tolerance, and investment objectives before making any trading or investment decisions.
Limitation of Liability: The creators of the Risk Meter, including any affiliates, developers, or contributors, are not liable for any direct, indirect, incidental, or consequential losses or damages arising from the use of this tool. This includes, but is not limited to, financial losses, missed opportunities, or decisions based on the tool’s output.
User Responsibility: By using the Risk Meter, you accept full responsibility for your trading and investment decisions. You acknowledge that you use the tool at your own risk and that the creators bear no responsibility for any outcomes resulting from its use.
Final Note
The Risk Meter is a supplementary tool designed to enhance your understanding of market risk. It is not a comprehensive solution for investment management. Approach trading and investing with caution, ensuring your decisions align with your personal financial strategy.
Multi-Timeframe MACD Strategy ver 1.0Multi-Timeframe MACD Strategy: Enhanced Trend Trading with Customizable Entry and Trailing Stop
This strategy utilizes the Moving Average Convergence Divergence (MACD) indicator across multiple timeframes to identify strong trends, generate precise entry and exit signals, and manage risk with an optional trailing stop loss. By combining the insights of both the current chart's timeframe and a user-defined higher timeframe, this strategy aims to improve trade accuracy, reduce exposure to false signals, and capture larger market moves.
Key Features:
Dual Timeframe Analysis: Calculates and analyzes the MACD on both the current chart's timeframe and a user-selected higher timeframe (e.g., Daily MACD on a 1-hour chart). This provides a broader market context, helping to confirm trends and filter out short-term noise.
Configurable MACD: Fine-tune the MACD calculation with adjustable Fast Length, Slow Length, and Signal Length parameters. Optimize the indicator's sensitivity to match your trading style and the volatility of the asset.
Flexible Entry Options: Choose between three distinct entry types:
Crossover: Enters trades when the MACD line crosses above (long) or below (short) the Signal line.
Zero Cross: Enters trades when the MACD line crosses above (long) or below (short) the zero line.
Both: Combines both Crossover and Zero Cross signals, providing more potential entry opportunities.
Independent Timeframe Control: Display and trade based on the current timeframe MACD, the higher timeframe MACD, or both. This allows you to focus on the information most relevant to your analysis.
Optional Trailing Stop Loss: Implements a configurable trailing stop loss to protect profits and limit potential losses. The trailing stop is adjusted dynamically as the price moves in your favor, based on a user-defined percentage.
No Repainting: Employs lookahead=barmerge.lookahead_off in the request.security() function to prevent data leakage and ensure accurate backtesting and real-time signals.
Clear Visual Signals (Optional): Includes optional plotting of the MACD and Signal lines for both timeframes, with distinct colors for easy visual identification. These plots are for visual confirmation and are not required for the strategy's logic.
Suitable for Various Trading Styles: Adaptable to swing trading, day trading, and trend-following strategies across diverse markets (stocks, forex, cryptocurrencies, etc.).
Fully Customizable: All parameters are adjustable, including timeframes, MACD Settings, Entry signal type and trailing stop settings.
How it Works:
MACD Calculation: The strategy calculates the MACD (using the standard formula) for both the current chart's timeframe and the specified higher timeframe.
Trend Identification: The relationship between the MACD line, Signal line, and zero line is used to determine the current trend for each timeframe.
Entry Signals: Buy/sell signals are generated based on the selected "Entry Type":
Crossover: A long signal is generated when the MACD line crosses above the Signal line, and both timeframes are in agreement (if both are enabled). A short signal is generated when the MACD line crosses below the Signal line, and both timeframes are in agreement.
Zero Cross: A long signal is generated when the MACD line crosses above the zero line, and both timeframes agree. A short signal is generated when the MACD line crosses below the zero line and both timeframes agree.
Both: Combines Crossover and Zero Cross signals.
Trailing Stop Loss (Optional): If enabled, a trailing stop loss is set at a specified percentage below (for long positions) or above (for short positions) the entry price. The stop-loss is automatically adjusted as the price moves favorably.
Exit Signals:
Without Trailing Stop: Positions are closed when the MACD signals reverse according to the selected "Entry Type" (e.g., a long position is closed when the MACD line crosses below the Signal line if using "Crossover" entries).
With Trailing Stop: Positions are closed if the price hits the trailing stop loss.
Backtesting and Optimization: The strategy automatically backtests on the chart's historical data, allowing you to assess its performance and optimize parameters for different assets and timeframes.
Example Use Cases:
Confirming Trend Strength: A trader on a 1-hour chart sees a bullish MACD crossover on the current timeframe. They check the MTF MACD strategy and see that the Daily MACD is also bullish, confirming the strength of the uptrend.
Filtering Noise: A trader using a 15-minute chart wants to avoid false signals from short-term volatility. They use the strategy with a 4-hour higher timeframe to filter out noise and only trade in the direction of the dominant trend.
Dynamic Risk Management: A trader enters a long position and enables the trailing stop loss. As the price rises, the trailing stop is automatically adjusted upwards, protecting profits. The trade is exited either when the MACD reverses or when the price hits the trailing stop.
Disclaimer:
The MACD is a lagging indicator and can produce false signals, especially in ranging markets. This strategy is for educational and informational purposes only and should not be considered financial advice. Backtest and optimize the strategy thoroughly, combine it with other technical analysis tools, and always implement sound risk management practices before using it with real capital. Past performance is not indicative of future results. Conduct your own due diligence and consider your risk tolerance before making any trading decisions.
Multi-Timeframe Parabolic SAR Strategy ver 1.0Multi-Timeframe Parabolic SAR Strategy (MTF PSAR) - Enhanced Trend Trading
This strategy leverages the power of the Parabolic SAR (Stop and Reverse) indicator across multiple timeframes to provide robust trend identification, precise entry/exit signals, and dynamic trailing stop management. By combining the insights of both the current chart's timeframe and a user-defined higher timeframe, this strategy aims to improve trading accuracy, reduce risk, and capture more significant market moves.
Key Features:
Dual Timeframe Analysis: Simultaneously analyzes the Parabolic SAR on the current chart and a higher timeframe (e.g., Daily PSAR on a 1-hour chart). This allows you to align your trades with the dominant trend and filter out noise from lower timeframes.
Configurable PSAR: Fine-tune the PSAR calculation with adjustable Start, Increment, and Maximum values to optimize sensitivity for your trading style and the asset's volatility.
Independent Timeframe Control: Choose to display and trade based on either or both the current timeframe PSAR and the higher timeframe PSAR. Focus on the most relevant information for your analysis.
Clear Visual Signals: Distinct colors for the current and higher timeframe PSAR dots provide a clear visual representation of potential entry and exit points.
Multiple Entry Strategies: The strategy offers flexible entry conditions, allowing you to trade based on:
Confirmation: Both current and higher timeframe PSAR signals agree and the current timeframe PSAR has just flipped direction. (Most conservative)
Current Timeframe Only: Trades based solely on the current timeframe PSAR, ideal for when the higher timeframe is less relevant or disabled.
Higher Timeframe Only: Trades based solely on the higher timeframe PSAR.
Dynamic Trailing Stop (PSAR-Based): Implements a trailing stop-loss based on the current timeframe's Parabolic SAR. This helps protect profits by automatically adjusting the stop-loss as the price moves in your favor. Exits are triggered when either the current or HTF PSAR flips.
No Repainting: Uses lookahead=barmerge.lookahead_off in the security() function to ensure that the higher timeframe data is accessed without any data leakage, preventing repainting issues.
Fully Configurable: All parameters (PSAR settings, higher timeframe, visibility, colors) are adjustable through the strategy's settings panel, allowing for extensive customization and optimization.
Suitable for Various Trading Styles: Applicable to swing trading, day trading, and trend-following strategies across various markets (stocks, forex, cryptocurrencies, etc.).
How it Works:
PSAR Calculation: The strategy calculates the standard Parabolic SAR for both the current chart's timeframe and the selected higher timeframe.
Trend Identification: The direction of the PSAR (dots below price = uptrend, dots above price = downtrend) determines the current trend for each timeframe.
Entry Signals: The strategy generates buy/sell signals based on the chosen entry strategy (Confirmation, Current Timeframe Only, or Higher Timeframe Only). The Confirmation strategy offers the highest probability signals by requiring agreement between both timeframes.
Trailing Stop Exit: Once a position is entered, the strategy uses the current timeframe PSAR as a dynamic trailing stop. The stop-loss is automatically adjusted as the PSAR dots move, helping to lock in profits and limit losses. The strategy exits when either the Current or HTF PSAR changes direction.
Backtesting and Optimization: The strategy automatically backtests on the chart's historical data, allowing you to evaluate its performance and optimize the settings for different assets and timeframes.
Example Use Cases:
Trend Confirmation: A trader on a 1-hour chart observes a bullish PSAR flip on the current timeframe. They check the MTF PSAR strategy and see that the Daily PSAR is also bullish, confirming the strength of the uptrend and providing a high-probability long entry signal.
Filtering Noise: A trader on a 5-minute chart wants to avoid whipsaws caused by short-term price fluctuations. They use the strategy with a 1-hour higher timeframe to filter out noise and only trade in the direction of the dominant trend.
Dynamic Risk Management: A trader enters a long position and uses the current timeframe PSAR as a trailing stop. As the price rises, the PSAR dots move upwards, automatically raising the stop-loss and protecting profits. The trade is exited when the current (or HTF) PSAR flips to bearish.
Disclaimer:
The Parabolic SAR is a lagging indicator and can produce false signals, particularly in ranging or choppy markets. This strategy is intended for educational and informational purposes only and should not be considered financial advice. It is essential to backtest and optimize the strategy thoroughly, use it in conjunction with other technical analysis tools, and implement sound risk management practices before using it with real capital. Past performance is not indicative of future results. Always conduct your own due diligence and consider your risk tolerance before making any trading decisions.
Time-Weighted Price Action IndicatorThe Time-Weighted Price Action Indicator is a simple yet effective tool designed to detect consolidation zones based on time duration and highlight potential reversal points using a contrarian breakout logic. Instead of following traditional breakout strategies, this indicator aims to capitalize on false breakouts and reversal entries.
How It Works
• The indicator identifies a price range (zone) using a configurable lookback period.
• If the price remains within this range for a specified number of bars (threshold), a consolidation zone is confirmed.
• Once a breakout or breakdown from this zone occurs, the indicator triggers a reversed signal — suggesting a potential reversal instead of a trend-following entry.
• Support and resistance levels are marked visually, and BUY/SELL labels are plotted when price re-enters the zone, indicating potential exhaustion or traps.
Key Features
• ✅ Time-based consolidation detection
• ✅ Contrarian signal logic (Buy at breakdowns, Sell at breakouts)
• ✅ Dynamic zone plotting with support/resistance visualization
• ✅ Auto-reset after each breakout for fresh zone detection
• ✅ Visual labels and alerts for BUY/SELL signals
How to Use
• Ideal for range-bound markets or identifying trap zones around support/resistance.
• Use in conjunction with volume, momentum, or trend filters to refine entries.
• Can complement mean reversion strategies or be used as a signal confirmation tool.
Why This Combination?
This approach blends time-based consolidation logic with a contrarian price action perspective, offering traders a different lens to analyze markets. Instead of blindly following breakouts, it highlights areas where price rejections and false breakouts often occur — common in algorithm-driven markets.
Why It’s Worth Using
This indicator helps you stay ahead of trap zones, identify reversal spots, and understand price behavior in consolidation zones — a critical edge, especially in sideways or choppy markets. It adds context to price movement, helping traders avoid common breakout failures.
Note:
• No performance guarantees or exaggerated claims.
• No solicitation or promotional language used.
• This is a free, open-source educational tool meant to aid price action understanding.
Supertrend TP SL (PRO)2. Main Components:
Supertrend Indicator:
Theoretical basis: The Supertrend indicator is based on two main concepts: Average True Range (ATR) and Factor. ATR measures the extent of price fluctuations in a given period of time, while Factor determines the sensitivity of the indicator to price changes.
Mechanism of operation: The indicator calculates two possible lines: one line representing the potential support level and another line representing the potential resistance level. The selection of the appropriate line depends on the current price direction. When the price is above the line, the indicator is considered to be in an uptrend, and vice versa.
Customizable inputs:
atrPeriod: Allows the trader to specify the time period for calculating the ATR. Shorter periods make the indicator more sensitive to price changes, while longer periods reduce its sensitivity.
factor: Allows the adjustment of the factor. Higher values make the indicator less likely to give false signals, but they may also delay entry signals.
Risk Management:
Take Profit and Stop Loss Orders:
TPPoints: Specifies the distance between the entry price and the take profit level. This distance is expressed in points, and is converted to an actual price value using syminfo.mintick (the smallest possible price movement of the traded asset).
SLPoints: Specifies the distance between the entry price and the stop loss level.
Importance: These orders allow the trader to specify the maximum loss he is willing to take and the profit target he is aiming to achieve, which helps in effective risk management.
Activate/Disable Trades:
isLongEnabled: Allows buy trades to be enabled or disabled, which allows the trader to trade in one direction only (for example, only trade in the uptrend during a bull market).
isShortEnabled: Allows sell trades to be enabled or disabled.
isTakeProfitEnabled: Allows take profit orders to be enabled or disabled. The trader may wish to disable them if he prefers to manage his trades manually.
isStopLossEnabled: Allows you to enable or disable stop loss orders. Although disabling them may seem tempting in some cases, it is a very risky move.
Visual Customization:
Line Style and Width:
lineStyle: Allows the trader to choose the style of lines used to draw TP and SL levels (Solid, Dashed, Dotted).
lineWidth: Sets the thickness of the lines.
Label Size:
labelSize: Allows you to set the size of the labels that display TP and SL levels (Small, Normal, Large).
Colors:
bullColor, bearColor, tpColor, slColor: Allows the trader to customize the colors of the different elements on the chart, making visual analysis easier.
3. Strategy Logic:
Determining Entry Signals: The strategy relies on the Supertrend indicator to determine entry signals. When the Supertrend trend changes from bearish to bullish, a buy trade is triggered (if isLongEnabled is enabled). When the trend changes from bullish to bearish, a sell trade is triggered (if isShortEnabled is enabled).
Order Execution: Once the entry signal is triggered, the strategy automatically places buy or sell orders.
Trade Management: After opening a trade, the strategy monitors the price and automatically triggers Take Profit and Stop Loss orders if the price reaches the specified levels.
Visualization: The strategy displays useful information on the chart, such as TP and SL lines, entry and exit signals, which helps the trader understand the strategy’s behavior and evaluate its performance.
4. Advanced Tips:
Optimizing Settings: The strategy’s performance can be improved by adjusting different input values. For example, the trader can experiment with different values for atrPeriod and factor to improve the accuracy of Supertrend signals.
Combining Indicators: This strategy can be combined with other indicators to improve the accuracy of entry signals. For example, the Relative Strength Index (RSI) can be used to confirm Supertrend signals.
Time Analysis: The strategy’s performance can be analyzed over different time periods to evaluate its effectiveness in various market conditions.
Strategy Testing: Before using the strategy in real trading, it should be tested on historical data (Backtesting) to evaluate its performance and determine the optimal settings.
5. Associated Risks:
False Signals: The Supertrend indicator may sometimes give false signals, especially in volatile markets.
Losses: Even with the use of stop loss orders, the trader may be exposed to significant losses.
Over-optimization: Over-optimization of settings on historical data may lead to misleading results. The trader should be careful about generalizing the results to future data.
Over-reliance on automation: The automated strategy should not be relied upon completely. The trader should monitor the trades and make appropriate decisions when necessary.
6. Disclaimer:
I am not a licensed financial advisor. This strategy is provided for educational and illustrative purposes only and should not be considered as investment advice. Trading in financial markets involves significant risks and you may lose your invested capital. Before making any investment decisions, consult a qualified financial advisor and conduct your own research. You alone are responsible for your trading decisions and their results. By using this strategy, you acknowledge and agree that I am not responsible for any losses or damages you may incur.
2. المكونات الرئيسية:
مؤشر Supertrend:
الأساس النظري: يعتمد مؤشر Supertrend على مفهومين رئيسيين هما: متوسط المدى الحقيقي (Average True Range - ATR) ومعامل الضرب (Factor). ATR يقيس مدى تقلبات الأسعار في فترة زمنية محددة، بينما Factor يحدد مدى حساسية المؤشر لتغيرات الأسعار.
آلية العمل: يقوم المؤشر بحساب خطين محتملين: خط يمثل مستوى الدعم المحتمل وخط آخر يمثل مستوى المقاومة المحتمل. يعتمد اختيار الخط المناسب على اتجاه السعر الحالي. عندما يكون السعر أعلى من الخط، يعتبر المؤشر في اتجاه صاعد، والعكس صحيح.
المدخلات القابلة للتخصيص:
atrPeriod: يتيح للمتداول تحديد الفترة الزمنية لحساب ATR. الفترات الأقصر تجعل المؤشر أكثر حساسية لتغيرات الأسعار، بينما الفترات الأطول تقلل من حساسيته.
factor: يسمح بتعديل معامل الضرب. القيم الأعلى تجعل المؤشر أقل عرضة لإعطاء إشارات خاطئة، ولكنها قد تؤخر أيضًا إشارات الدخول.
إدارة المخاطر:
أوامر جني الأرباح وإيقاف الخسارة:
TPPoints: يحدد المسافة بين سعر الدخول ومستوى جني الأرباح. يتم التعبير عن هذه المسافة بالنقاط (Points)، ويتم تحويلها إلى قيمة سعرية فعلية باستخدام syminfo.mintick (أصغر حركة سعرية ممكنة للأصل المتداول).
SLPoints: يحدد المسافة بين سعر الدخول ومستوى إيقاف الخسارة.
الأهمية: تتيح هذه الأوامر للمتداول تحديد الحد الأقصى للخسارة التي يرغب في تحملها والهدف الربحي الذي يسعى لتحقيقه، مما يساعد على إدارة المخاطر بشكل فعال.
تفعيل/تعطيل الصفقات:
isLongEnabled: يسمح بتفعيل أو تعطيل صفقات الشراء، مما يمكن المتداول من التداول في اتجاه واحد فقط (على سبيل المثال، التداول فقط في الاتجاه الصاعد خلال سوق صاعدة).
isShortEnabled: يسمح بتفعيل أو تعطيل صفقات البيع.
isTakeProfitEnabled: يسمح بتفعيل أو تعطيل أوامر جني الأرباح. قد يرغب المتداول في تعطيلها إذا كان يفضل إدارة صفقاته يدويًا.
isStopLossEnabled: يسمح بتفعيل أو تعطيل أوامر إيقاف الخسارة. على الرغم من أن تعطيلها قد يبدو مغريًا في بعض الحالات، إلا أنه يعتبر خطوة محفوفة بالمخاطر للغاية.
التخصيص المرئي:
نمط وعرض الخطوط:
lineStyle: يتيح للمتداول اختيار نمط الخطوط المستخدمة لرسم مستويات TP و SL (Solid, Dashed, Dotted).
lineWidth: يحدد سمك الخطوط.
حجم الملصقات:
labelSize: يسمح بتحديد حجم الملصقات التي تعرض مستويات TP و SL (Small, Normal, Large).
الألوان:
bullColor, bearColor, tpColor, slColor: تتيح للمتداول تخصيص ألوان العناصر المختلفة على الرسم البياني، مما يسهل عملية التحليل البصري.
3. منطق عمل الاستراتيجية:
تحديد إشارات الدخول: تعتمد الاستراتيجية على مؤشر Supertrend لتحديد إشارات الدخول. عندما يتغير اتجاه Supertrend من هابط إلى صاعد، يتم تفعيل صفقة شراء (إذا كانت isLongEnabled مفعلة). وعندما يتغير الاتجاه من صاعد إلى هابط، يتم تفعيل صفقة بيع (إذا كانت isShortEnabled مفعلة).
تنفيذ الأوامر: بمجرد تفعيل إشارة الدخول، تقوم الاستراتيجية بوضع أوامر الشراء أو البيع تلقائيًا.
إدارة الصفقات: بعد فتح الصفقة، تقوم الاستراتيجية بمراقبة السعر وتفعيل أوامر جني الأرباح وإيقاف الخسارة تلقائيًا في حالة وصول السعر إلى المستويات المحددة.
التمثيل المرئي: تعرض الاستراتيجية معلومات مفيدة على الرسم البياني، مثل خطوط TP و SL وإشارات الدخول والخروج، مما يساعد المتداول على فهم سلوك الاستراتيجية وتقييم أدائها.
4. نصائح متقدمة:
تحسين الإعدادات: يمكن تحسين أداء الاستراتيجية من خلال تعديل قيم المدخلات المختلفة. على سبيل المثال، يمكن للمتداول تجربة قيم مختلفة لـ atrPeriod و factor لتحسين دقة إشارات Supertrend.
الجمع بين المؤشرات: يمكن دمج هذه الاستراتيجية مع مؤشرات أخرى لتحسين دقة إشارات الدخول. على سبيل المثال، يمكن استخدام مؤشر القوة النسبية (RSI) لتأكيد إشارات Supertrend.
التحليل الزمني: يمكن تحليل أداء الاستراتيجية على مدى فترات زمنية مختلفة لتقييم مدى فعاليتها في ظروف السوق المتنوعة.
اختبار الاستراتيجية: قبل استخدام الاستراتيجية في التداول الحقيقي، يجب اختبارها على بيانات تاريخية (Backtesting) لتقييم أدائها وتحديد الإعدادات المثلى.
5. المخاطر المرتبطة:
الإشارات الخاطئة: قد يعطي مؤشر Supertrend إشارات خاطئة في بعض الأحيان، خاصة في الأسواق المتقلبة.
الخسائر: حتى مع استخدام أوامر إيقاف الخسارة، قد يتعرض المتداول لخسائر كبيرة.
التحسين المفرط: قد يؤدي التحسين المفرط للإعدادات على بيانات تاريخية إلى نتائج مضللة. يجب أن يكون المتداول حذرًا بشأن تعميم النتائج على البيانات المستقبلية.
الاعتماد الزائد على الأتمتة: يجب عدم الاعتماد بشكل كامل على الاستراتيجية الآلية. يجب على المتداول مراقبة الصفقات واتخاذ القرارات المناسبة عند الضرورة.
6. إخلاء المسؤولية:
أنا لست مستشارًا ماليًا مرخصًا. هذه الاستراتيجية مقدمة لأغراض تعليمية وتوضيحية فقط، ولا ينبغي اعتبارها نصيحة استثمارية. التداول في الأسواق المالية ينطوي على مخاطر كبيرة، وقد تخسر رأس المال المستثمر. قبل اتخاذ أي قرارات استثمارية، استشر مستشارًا ماليًا مؤهلاً وقم بإجراء بحثك الخاص. أنت وحدك المسؤول عن قراراتك التجارية ونتائجها. باستخدام هذه الاستراتيجية، فإنك تقر وتوافق على أنني لست مسؤولاً عن أي خسائر أو أضرار قد تتكبدها.
TEMA OBOS Strategy PakunTEMA OBOS Strategy
Overview
This strategy combines a trend-following approach using the Triple Exponential Moving Average (TEMA) with Overbought/Oversold (OBOS) indicator filtering.
By utilizing TEMA crossovers to determine trend direction and OBOS as a filter, it aims to improve entry precision.
This strategy can be applied to markets such as Forex, Stocks, and Crypto, and is particularly designed for mid-term timeframes (5-minute to 1-hour charts).
Strategy Objectives
Identify trend direction using TEMA
Use OBOS to filter out overbought/oversold conditions
Implement ATR-based dynamic risk management
Key Features
1. Trend Analysis Using TEMA
Uses crossover of short-term EMA (ema3) and long-term EMA (ema4) to determine entries.
ema4 acts as the primary trend filter.
2. Overbought/Oversold (OBOS) Filtering
Long Entry Condition: up > down (bullish trend confirmed)
Short Entry Condition: up < down (bearish trend confirmed)
Reduces unnecessary trades by filtering extreme market conditions.
3. ATR-Based Take Profit (TP) & Stop Loss (SL)
Adjustable ATR multiplier for TP/SL
Default settings:
TP = ATR × 5
SL = ATR × 2
Fully customizable risk parameters.
4. Customizable Parameters
TEMA Length (for trend calculation)
OBOS Length (for overbought/oversold detection)
Take Profit Multiplier
Stop Loss Multiplier
EMA Display (Enable/Disable TEMA lines)
Bar Color Change (Enable/Disable candle coloring)
Trading Rules
Long Entry (Buy Entry)
ema3 crosses above ema4 (Golden Cross)
OBOS indicator confirms up > down (bullish trend)
Execute a buy position
Short Entry (Sell Entry)
ema3 crosses below ema4 (Death Cross)
OBOS indicator confirms up < down (bearish trend)
Execute a sell position
Take Profit (TP)
Entry Price + (ATR × TP Multiplier) (Default: 5)
Stop Loss (SL)
Entry Price - (ATR × SL Multiplier) (Default: 2)
TP/SL settings are fully customizable to fine-tune risk management.
Risk Management Parameters
This strategy emphasizes proper position sizing and risk control to balance risk and return.
Trading Parameters & Considerations
Initial Account Balance: $7,000 (adjustable)
Base Currency: USD
Order Size: 10,000 USD
Pyramiding: 1
Trading Fees: $0.94 per trade
Long Position Margin: 50%
Short Position Margin: 50%
Total Trades (M5 Timeframe): 128
Deep Test Results (2024/11/01 - 2025/02/24)BTCUSD-5M
Total P&L：+1638.20USD
Max equity drawdown：694.78USD
Total trades：128
Profitable trades:44.53
Profit factor:1.45
These settings aim to protect capital while maintaining a balanced risk-reward approach.
Visual Support
TEMA Lines (Three EMAs)
Trend direction is indicated by color changes (Blue/Orange)
ema3 (short-term) and ema4 (long-term) crossover signals potential entries
OBOS Histogram
Green → Strong buying pressure
Red → Strong selling pressure
Blue → Possible trend reversal
Entry & Exit Markers
Blue Arrow → Long Entry Signal
Red Arrow → Short Entry Signal
Take Profit / Stop Loss levels displayed
Strategy Improvements & Uniqueness
This strategy is based on indicators developed by "l_lonthoff" and "jdmonto0", but has been significantly optimized for better entry accuracy, visual clarity, and risk management.
Enhanced Trend Identification with TEMA
Detects early trend reversals using ema3 & ema4 crossover
Reduces market noise for a smoother trend-following approach
Improved OBOS Filtering
Prevents excessive trading
Reduces unnecessary risk exposure
Dynamic Risk Management with ATR-Based TP/SL
Not a fixed value → TP/SL adjusts to market volatility
Fully customizable ATR multiplier settings
(Default: TP = ATR × 5, SL = ATR × 2)
Summary
The TEMA + OBOS Strategy is a simple yet powerful trading method that integrates trend analysis and oscillators.
TEMA for trend identification
OBOS for noise reduction & overbought/oversold filtering
ATR-based TP/SL settings for dynamic risk management
Before using this strategy, ensure thorough backtesting and demo trading to fine-tune parameters according to your trading style.
Enhanced KLSE Banker Flow Oscillator# Enhanced KLSE Banker Flow Oscillator
## Description
The Enhanced KLSE Banker Flow Oscillator is a sophisticated technical analysis tool designed specifically for the Malaysian stock market (KLSE). This indicator analyzes price and volume relationships to identify potential smart money movements, providing early signals for market reversals and continuation patterns.
The oscillator measures the buying and selling pressure in the market with a focus on detecting institutional activity. By combining money flow calculations with volume filters and price action analysis, it helps traders identify high-probability trading opportunities with reduced noise.
## Key Features
- Dual-Timeframe Analysis: Combines long-term money flow trends with short-term momentum shifts for more accurate signals
- Adaptive Volume Filtering: Automatically adjusts volume thresholds based on recent market conditions
- Advanced Divergence Detection: Identifies potential trend reversals through price-flow divergences
- Early Signal Detection: Provides anticipatory signals before major price movements occur
- Multiple Signal Types: Offers both early alerts and strong confirmation signals with clear visual markers
- Volatility Adjustment: Adapts sensitivity based on current market volatility for more reliable signals
- Comprehensive Visual Feedback: Color-coded oscillator, signal markers, and optional text labels
- Customizable Display Options: Toggle momentum histogram, early signals, and zone fills
- Organized Settings Interface: Logically grouped parameters for easier configuration
## Indicator Components
1. Main Oscillator Line: The primary banker flow line that fluctuates above and below zero
2. Early Signal Line: Secondary indicator showing potential emerging signals
3. Momentum Histogram: Visual representation of flow momentum changes
4. Zone Fills: Color-coded background highlighting positive and negative zones
5. Signal Markers: Visual indicators for entry and exit points
6. Reference Lines: Key levels for strong and early signals
7. Signal Labels: Optional text annotations for significant signals
## Signal Types
1. Strong Buy Signal (Green Arrow): Major bullish signal with high probability of success
2. Strong Sell Signal (Red Arrow): Major bearish signal with high probability of success
3. Early Buy Signal (Blue Circle): First indication of potential bullish trend
4. Early Sell Signal (Red Circle): First indication of potential bearish trend
5. Bullish Divergence (Yellow Triangle Up): Price making lower lows while flow makes higher lows
6. Bearish Divergence (Yellow Triangle Down): Price making higher highs while flow makes lower highs
## Parameters Explained
### Core Settings
- MFI Base Length (14): Primary calculation period for money flow index
- Short-term Flow Length (5): Calculation period for early signals
- KLSE Sensitivity (1.8): Multiplier for flow calculations, higher = more sensitive
- Smoothing Length (5): Smoothing period for the main oscillator line
### Volume Filter Settings
- Volume Filter % (65): Minimum volume threshold as percentage of average
- Use Adaptive Volume Filter (true): Dynamically adjusts volume thresholds
### Signal Levels
- Strong Signal Level (15): Threshold for strong buy/sell signals
- Early Signal Level (10): Threshold for early buy/sell signals
- Early Signal Threshold (0.75): Sensitivity factor for early signals
### Advanced Settings
- Divergence Lookback (34): Period for checking price-flow divergences
- Show Signal Labels (true): Toggle text labels for signals
### Visual Settings
- Show Momentum Histogram (true): Toggle the momentum histogram display
- Show Early Signal (true): Toggle the early signal line display
- Show Zone Fills (true): Toggle background color fills
## How to Use This Indicator
### Installation
1. Add the indicator to your TradingView chart
2. Default settings are optimized for KLSE stocks
3. Customize parameters if needed for specific stocks
### Basic Interpretation
- Oscillator Above Zero: Bullish bias, buying pressure dominates
- Oscillator Below Zero: Bearish bias, selling pressure dominates
- Crossing Zero Line: Potential shift in market sentiment
- Extreme Readings: Possible overbought/oversold conditions
### Advanced Interpretation
- Divergences: Early warning of trend exhaustion
- Signal Confluences: Multiple signal types appearing together increase reliability
- Volume Confirmation: Signals with higher volume are more significant
- Momentum Alignment: Histogram should confirm direction of main oscillator
### Trading Strategies
#### Trend Following Strategy
1. Identify market trend direction
2. Wait for pullbacks shown by oscillator moving against trend
3. Enter when oscillator reverses back in trend direction with a Strong signal
4. Place stop loss below/above recent swing low/high
5. Take profit at previous resistance/support levels
#### Counter-Trend Strategy
1. Look for oscillator reaching extreme levels
2. Identify divergence between price and oscillator
3. Wait for oscillator to cross Early signal threshold
4. Enter position against prevailing trend
5. Use tight stop loss (1 ATR from entry)
6. Take profit at first resistance/support level
#### Breakout Confirmation Strategy
1. Identify stock consolidating in a range
2. Wait for price to break out of range
3. Confirm breakout with oscillator crossing zero line in breakout direction
4. Enter position in breakout direction
5. Place stop loss below/above the breakout level
6. Trail stop as price advances
### Signal Hierarchy and Reliability
From highest to lowest reliability:
1. Strong Buy/Sell signals with divergence and high volume
2. Strong Buy/Sell signals with high volume
3. Divergence signals followed by Early signals
4. Strong Buy/Sell signals with normal volume
5. Early Buy/Sell signals with high volume
6. Early Buy/Sell signals with normal volume
## Complete Trading Plan Example
### KLSE Market Trading System
#### Pre-Trading Preparation
1. Review overall market sentiment (bullish, bearish, or neutral)
2. Scan for stocks showing significant banker flow signals
3. Note key support/resistance levels for watchlist stocks
4. Prioritize trade candidates based on signal strength and volume
#### Entry Rules for Long Positions
1. Banker Flow Oscillator above zero line (positive flow environment)
2. One or more of the following signals present:
- Strong Buy signal (green arrow)
- Bullish Divergence signal (yellow triangle up)
- Early Buy signal (blue circle) with confirming price action
3. Entry confirmation requirements:
- Volume above 65% of 20-day average
- Price above short-term moving average (e.g., 20 EMA)
- No immediate resistance within 3% of entry price
4. Entry on the next candle open after signal confirmation
#### Entry Rules for Short Positions
1. Banker Flow Oscillator below zero line (negative flow environment)
2. One or more of the following signals present:
- Strong Sell signal (red arrow)
- Bearish Divergence signal (yellow triangle down)
- Early Sell signal (red circle) with confirming price action
3. Entry confirmation requirements:
- Volume above 65% of 20-day average
- Price below short-term moving average (e.g., 20 EMA)
- No immediate support within 3% of entry price
4. Entry on the next candle open after signal confirmation
#### Position Sizing Rules
1. Base risk per trade: 1% of trading capital
2. Position size calculation: Capital × Risk% ÷ Stop Loss Distance
3. Position size adjustments:
- Increase by 20% for Strong signals with above-average volume
- Decrease by 20% for Early signals without confirming price action
- Standard size for all other valid signals
#### Stop Loss Placement
1. For Long Positions:
- Place stop below the most recent swing low
- Minimum distance: 1.5 × ATR(14)
- Maximum risk: 1% of trading capital
2. For Short Positions:
- Place stop above the most recent swing high
- Minimum distance: 1.5 × ATR(14)
- Maximum risk: 1% of trading capital
#### Take Profit Strategy
1. First Target (33% of position):
- 1.5:1 reward-to-risk ratio
- Move stop to breakeven after reaching first target
2. Second Target (33% of position):
- 2.5:1 reward-to-risk ratio
- Trail stop at previous day's low/high
3. Final Target (34% of position):
- 4:1 reward-to-risk ratio or
- Exit when opposing signal appears (e.g., Strong Sell for long positions)
#### Trade Management Rules
1. After reaching first target:
- Move stop to breakeven
- Consider adding to position if new confirming signal appears
2. After reaching second target:
- Trail stop using banker flow signals
- Exit remaining position when:
- Oscillator crosses zero line in opposite direction
- Opposing signal appears
- Price closes below/above trailing stop level
3. Maximum holding period:
- 20 trading days for trend-following trades
- 10 trading days for counter-trend trades
- Re-evaluate if targets not reached within timeframe
#### Risk Management Safeguards
1. Maximum open positions: 5 trades
2. Maximum sector exposure: 40% of trading capital
3. Maximum daily drawdown limit: 3% of trading capital
4. Mandatory stop trading rules:
- After three consecutive losing trades
- After reaching 5% account drawdown
- Resume after two-day cooling period and strategy review
#### Performance Tracking
1. Track for each trade:
- Signal type that triggered entry
- Oscillator reading at entry and exit
- Volume relative to average
- Price action confirmation patterns
- Holding period
- Reward-to-risk achieved
2. Review performance metrics weekly:
- Win rate by signal type
- Average reward-to-risk ratio
- Profit factor
- Maximum drawdown
3. Adjust strategy parameters based on performance:
- Increase position size for highest performing signals
- Decrease or eliminate trades based on underperforming signals
## Advanced Usage Tips
1. Combine with Support/Resistance:
- Signals are more reliable when they occur at key support/resistance levels
- Look for banker flow divergence at major price levels
2. Multiple Timeframe Analysis:
- Use the oscillator on both daily and weekly timeframes
- Stronger signals when both timeframes align
- Enter on shorter timeframe when confirmed by longer timeframe
3. Sector Rotation Strategy:
- Compare banker flow across different sectors
- Rotate capital to sectors showing strongest positive flow
- Avoid sectors with persistent negative flow
4. Volatility Adjustments:
- During high volatility periods, wait for Strong signals only
- During low volatility periods, Early signals can be more actionable
5. Optimizing Parameters:
- For more volatile stocks: Increase Smoothing Length (6-8)
- For less volatile stocks: Decrease KLSE Sensitivity (1.2-1.5)
- For intraday trading: Reduce all length parameters by 30-50%
## Fine-Tuning for Different Markets
While optimized for KLSE, the indicator can be adapted for other markets:
1. For US Stocks:
- Reduce KLSE Sensitivity to 1.5
- Increase Volume Filter to 75%
- Adjust Strong Signal Level to 18
2. For Forex:
- Increase Smoothing Length to 8
- Reduce Early Signal Threshold to 0.6
- Focus more on divergence signals than crossovers
3. For Cryptocurrencies:
- Increase KLSE Sensitivity to 2.2
- Reduce Signal Levels (Strong: 12, Early: 8)
- Use higher Volume Filter (80%)
By thoroughly understanding and properly implementing the Enhanced KLSE Banker Flow Oscillator, traders can gain a significant edge in identifying institutional money flow and making more informed trading decisions, particularly in the Malaysian stock market.
SuperTrend AI Oscillator StrategySuperTrend AI Oscillator Strategy
Overview
This strategy is a trend-following approach that combines the SuperTrend indicator with oscillator-based filtering.
By identifying market trends while utilizing oscillator-based momentum analysis, it aims to improve entry precision.
Additionally, it incorporates a trailing stop to strengthen risk management while maximizing profits.
This strategy can be applied to various markets, including Forex, Crypto, and Stocks, as well as different timeframes. However, its effectiveness varies depending on market conditions, so thorough testing is required.
Features
1️⃣ Trend Identification Using SuperTrend
The SuperTrend indicator (a volatility-adjusted trend indicator based on ATR) is used to determine trend direction.
A long entry is considered when SuperTrend turns bullish.
A short entry is considered when SuperTrend turns bearish.
The goal is to capture clear trend reversals and avoid unnecessary trades in ranging markets.
2️⃣ Entry Filtering with an Oscillator
The Super Oscillator is used to filter entry signals.
If the oscillator exceeds 50, it strengthens long entries (indicating strong bullish momentum).
If the oscillator drops below 50, it strengthens short entries (indicating strong bearish momentum).
This filter helps reduce trades in uncertain market conditions and improves entry accuracy.
3️⃣ Risk Management with a Trailing Stop
Instead of a fixed stop loss, a SuperTrend-based trailing stop is implemented.
The stop level adjusts automatically based on market volatility.
This allows profits to run while managing downside risk effectively.
4️⃣ Adjustable Risk-Reward Ratio
The default risk-reward ratio is set at 1:2.
Example: A 1% stop loss corresponds to a 2% take profit target.
The ratio can be customized according to the trader’s risk tolerance.
5️⃣ Clear Trade Signals & Visual Support
Green "BUY" labels indicate long entry signals.
Red "SELL" labels indicate short entry signals.
The Super Oscillator is plotted in a separate subwindow to visually assess trend strength.
A real-time trailing stop is displayed to support exit strategies.
These visual aids make it easier to identify entry and exit points.
Trading Parameters & Considerations
Initial Account Balance: Default is $7,000 (adjustable).
Base Currency: USD
Order Size: 10,000 USD
Pyramiding: 1
Trading Fees: $0.94 per trade
Long Position Margin: 50%
Short Position Margin: 50%
Total Trades (M5 Timeframe): 1,032
Visual Aids for Clarity
This strategy includes clear visual trade signals to enhance decision-making:
Green "BUY" labels for long entries
Red "SELL" labels for short entries
Super Oscillator plotted in a subwindow with a 50 midline
Dynamic trailing stop displayed for real-time trend tracking
These visual aids allow traders to quickly identify trade setups and manage positions with greater confidence.
Summary
The SuperTrend AI Oscillator Strategy is developed based on indicators from Black Cat and LuxAlgo.
By integrating high-precision trend analysis with AI-based oscillator filtering, it provides a strong risk-managed trading approach.
Important Notes
This strategy does not guarantee profits—performance varies based on market conditions.
Past performance does not guarantee future results. Markets are constantly changing.
Always test extensively with backtesting and demo trading before using it in live markets.
Risk management, position sizing, and market conditions should always be considered when trading.
Conclusion
This strategy combines trend analysis with momentum filtering, enhancing risk management in trading.
By following market trends carefully, making precise entries, and using trailing stops, it seeks to reduce risk while maximizing potential profits.
Before using this strategy, be sure to test it thoroughly via backtesting and demo trading, and adjust the settings to match your trading style.
Aggressive Strategy for High IV Market### Strategic background
In a volatile high IV market, prices are volatile and market expectations of future uncertainty are high. This environment provides opportunities for aggressive trading strategies, but also comes with a high level of risk. In pursuit of a high Sharpe ratio (i.e., risk-adjusted return), we need to design a strategy that captures the benefits of market volatility while effectively controlling risk. Based on daily line cycles, I choose a combination of trend tracking and volatility filtering for highly volatile assets such as stocks, futures or cryptocurrencies.
---
### Strategy framework
#### Data
- Use daily data, including opening, closing, high and low prices.
- Suitable for highly volatile markets such as technology stocks, cryptocurrencies or volatile index futures.
#### Core indicators
1. ** Trend Indicators ** :
Fast Exponential Moving Average (EMA_fast) : 10-day EMA, used to capture short-term trends.
- Slow Exponential Moving Average (EMA_slow) : 30-day EMA, used to determine the long-term trend.
2. ** Volatility Indicators ** :
Average true Volatility (ATR) : 14-day ATR, used to measure market volatility.
- ATR mean (ATR_mean) : A simple moving average of the 20-day ATR that serves as a volatility benchmark.
- ATR standard deviation (ATR_std) : The standard deviation of the 20-day ATR, which is used to judge extreme changes in volatility.
#### Trading logic
The strategy is based on a trend following approach of double moving averages and filters volatility through ATR indicators, ensuring that trading only in a high-volatility environment is in line with aggressive and high sharpe ratio goals.
---
### Entry and exit conditions
#### Admission conditions
- ** Multiple entry ** :
- EMA_fast Crosses EMA_slow (gold cross), indicating that the short-term trend is turning upward.
-ATR > ATR_mean + 1 * ATR_std indicates that the current volatility is above average and the market is in a state of high volatility.
- ** Short Entry ** :
- EMA_fast Crosses EMA_slow (dead cross) downward, indicating that the short-term trend turns downward.
-ATR > ATR_mean + 1 * ATR_std, confirming high volatility.
#### Appearance conditions
- ** Long show ** :
- EMA_fast Enters the EMA_slow (dead cross) downward, and the trend reverses.
- or ATR < ATR_mean-1 * ATR_std, volatility decreases significantly and the market calms down.
- ** Bear out ** :
- EMA_fast Crosses the EMA_slow (gold cross) on the top, and the trend reverses.
- or ATR < ATR_mean-1 * ATR_std, the volatility is reduced.
---
### Risk management
To control the high risk associated with aggressive strategies, set up the following mechanisms:
1. ** Stop loss ** :
- Long: Entry price - 2 * ATR.
- Short: Entry price + 2 * ATR.
- Dynamic stop loss based on ATR can adapt to market volatility changes.
2. ** Stop profit ** :
- Fixed profit target can be selected (e.g. entry price ± 4 * ATR).
- Or use trailing stop losses to lock in profits following price movements.
3. ** Location Management ** :
- Reduce positions appropriately in times of high volatility, such as dynamically adjusting position size according to ATR, ensuring that the risk of a single trade does not exceed 1%-2% of the account capital.
---
### Strategy features
- ** Aggressiveness ** : By trading only in a high ATR environment, the strategy takes full advantage of market volatility and pursues greater returns.
- ** High Sharpe ratio potential ** : Trend tracking combined with volatility filtering to avoid ineffective trades during periods of low volatility and improve the ratio of return to risk.
- ** Daily line Cycle ** : Based on daily line data, suitable for traders who operate frequently but are not too complex.
---
### Implementation steps
1. ** Data Preparation ** :
- Get the daily data of the target asset.
- Calculate EMA_fast (10 days), EMA_slow (30 days), ATR (14 days), ATR_mean (20 days), and ATR_std (20 days).
2. ** Signal generation ** :
- Check EMA cross signals and ATR conditions daily to generate long/short signals.
3. ** Execute trades ** :
- Enter according to the signal, set stop loss and profit.
- Monitor exit conditions and close positions in time.
4. ** Backtest and Optimization ** :
- Use historical data to backtest strategies to evaluate Sharpe ratios, maximum retracements, and win rates.
- Optimize parameters such as EMA period and ATR threshold to improve policy performance.
---
### Precautions
- ** Trading costs ** : Highly volatile markets may result in frequent trading, and the impact of fees and slippage on earnings needs to be considered.
- ** Risk Control ** : Aggressive strategies may face large retracements and need to strictly implement stop losses.
- ** Scalability ** : Additional metrics (such as volume or VIX) can be added to enhance strategy robustness, or combined with machine learning to predict trends and volatility.
---
### Summary
This is a trend following strategy based on dual moving averages and ATR, designed for volatile high IV markets. By entering into high volatility and exiting into low volatility, the strategy combines aggressive and risk-adjusted returns for traders seeking a high sharpe ratio. It is recommended to fully backtest before implementation and adjust the parameters according to the specific market.
ADX for BTC [PineIndicators]The ADX Strategy for BTC is a trend-following system that uses the Average Directional Index (ADX) to determine market strength and momentum shifts. Designed for Bitcoin trading, this strategy applies a customizable ADX threshold to confirm trend signals and optionally filters entries using a Simple Moving Average (SMA). The system features automated entry and exit conditions, dynamic trade visualization, and built-in trade tracking for historical performance analysis.
⚙️ Core Strategy Components
1️⃣ Average Directional Index (ADX) Calculation
The ADX indicator measures trend strength without indicating direction. It is derived from the Positive Directional Movement (+DI) and Negative Directional Movement (-DI):
+DI (Positive Directional Index): Measures upward price movement.
-DI (Negative Directional Index): Measures downward price movement.
ADX Value: Higher values indicate stronger trends, regardless of direction.
This strategy uses a default ADX length of 14 to smooth out short-term fluctuations while detecting sustainable trends.
2️⃣ SMA Filter (Optional Trend Confirmation)
The strategy includes a 200-period SMA filter to validate trend direction before entering trades. If enabled:
✅ Long Entry is only allowed when price is above a long-term SMA multiplier (5x the standard SMA length).
✅ If disabled, the strategy only considers the ADX crossover threshold for trade entries.
This filter helps reduce entries in sideways or weak-trend conditions, improving signal reliability.
📌 Trade Logic & Conditions
🔹 Long Entry Conditions
A buy signal is triggered when:
✅ ADX crosses above the threshold (default = 14), indicating a strengthening trend.
✅ (If SMA filter is enabled) Price is above the long-term SMA multiplier.
🔻 Exit Conditions
A position is closed when:
✅ ADX crosses below the stop threshold (default = 45), signaling trend weakening.
By adjusting the entry and exit ADX levels, traders can fine-tune sensitivity to trend changes.
📏 Trade Visualization & Tracking
Trade Markers
"Buy" label (▲) appears when a long position is opened.
"Close" label (▼) appears when a position is exited.
Trade History Boxes
Green if a trade is profitable.
Red if a trade closes at a loss.
Trend Tracking Lines
Horizontal lines mark entry and exit prices.
A filled trade box visually represents trade duration and profitability.
These elements provide clear visual insights into trade execution and performance.
⚡ How to Use This Strategy
1️⃣ Apply the script to a BTC chart in TradingView.
2️⃣ Adjust ADX entry/exit levels based on trend sensitivity.
3️⃣ Enable or disable the SMA filter for trend confirmation.
4️⃣ Backtest performance to analyze historical trade execution.
5️⃣ Monitor trade markers and history boxes for real-time trend insights.
This strategy is designed for trend traders looking to capture high-momentum market conditions while filtering out weak trends.
Bot for Spot Market - Custom GridThis script is designed to create a trading bot for the spot market, specifically for buying and selling bitcoins profitably. Recommended for timeframes above two hours. Here are the main functions and features of the script:
Strategy Setup: The bot is set up with a custom grid strategy, defining parameters like pyramiding (allowed number of simultaneous trades), margin requirements, commission, and initial capital.
Order Requirements: It calculates the order price and amount based on the minimum requirements set by the exchange and rounds them appropriately.
Entry Conditions: The bot makes new entries if the closing price falls a certain percentage below the last entry price. It continues to make entries until the closing price rises a certain percentage above the average entry price.
Targets and Plots:
It calculates and plots the target profit level.
It plots the average entry price and the last entry price.
It plots the next entry price based on the defined conditions.
It plots the maximum number of orders allowed based on equity and the number of open orders.
Timerange: The bot can start trading from a specific date and time defined by the user.
Entries: It places orders if the timerange conditions are met. It also places new orders if the closing price is below the last entry price by a defined percentage.
Profit Calculation: The script calculates open profit or loss for the open positions.
Exit Conditions: It closes all positions if the open profit is positive and the closing price is above the target profit level.
Performance Table: The bot maintains and displays statistics like the number of open and closed trades, net profit, and equity in a table format.
The script is customizable, allowing users to adjust parameters like initial capital, commission, order values, and profit targets to fit their specific trading needs and exchange requirements.
Supertrend Strategy with Money Ocean TradeStrategy Overview
The Supertrend Strategy with Trend Change Confirmation leverages the Supertrend indicator to identify potential buy and sell signals based on changes in trend direction and subsequent price action. The strategy is designed to work with any financial instrument (symbol) and aims to provide clear entry and exit signals.
Key Components
Supertrend Indicator: The core of this strategy is the Supertrend indicator, calculated using a length of 3 and a factor of 1. The Supertrend line is plotted on the chart to visually represent trend direction.
Direction 1: Indicates an uptrend (bullish).
Direction -1: Indicates a downtrend (bearish).
Trend Change Detection: The strategy monitors changes in the trend direction. When a trend change is detected, it checks if the next candle confirms the trend change by breaking above or below the Supertrend line.
Entry Conditions:
Long Entry (Buy): When the Supertrend direction changes to 1 (uptrend) and the next candle closes above the Supertrend line.
Short Entry (Sell): When the Supertrend direction changes to -1 (downtrend) and the next candle closes below the Supertrend line.
Exit Conditions: The strategy closes the position based on the opposite signal.
Long Exit: When the Supertrend direction changes to -1 (downtrend) and the next candle closes below the Supertrend line.
Short Exit: When the Supertrend direction changes to 1 (uptrend) and the next candle closes above the Supertrend line.
Visual Signals: The strategy plots buy and sell signals on the chart using plotshape:
BUY: A green label below the bar when a long entry is triggered.
SELL: A red label above the bar when a short entry is triggered.
Alerts: Alerts are set up to notify when a buy or sell signal is triggered.
Script Summary
This strategy helps traders identify potential trading opportunities based on trend changes and confirms the trend by checking the next candle's price action. The visual signals and dashboard enhance the user's ability to monitor and manage trades effectively.
Feel free to test and adjust the parameters to suit your trading preferences! If you need further customizations or explanations, let me know.
[3Commas] HA & MAHA & MA
🔷What it does: This tool is designed to test a trend-following strategy using Heikin Ashi candles and moving averages. It enters trades after pullbacks, aiming to let profits run once the risk-to-reward ratio reaches 1:1 while securing the position.
🔷Who is it for: It is ideal for traders looking to compare final results using fixed versus dynamic take profits by adjusting parameters and trade direction—a concept applicable to most trading strategies.
🔷How does it work: We use moving averages to define the market trend, then wait for opposite Heikin Ashi candles to form against it. Once these candles reverse in favor of the trend, we enter the trade, using the last swing created by the pullback as the stop loss. By applying the breakeven ratio, we protect the trade and let it run, using the slower moving average as a trailing stop.
A buy signal is generated when:
The previous candle is bearish (ha_bear ), indicating a pullback.
The fast moving average (ma1) is above the slow moving average (ma2), confirming an uptrend.
The current candle is bullish (ha_bull), showing trend continuation.
The Heikin Ashi close is above the fast moving average (ma1), reinforcing the bullish bias.
The real price close is above the open (close > open), ensuring bullish momentum in actual price data.
The signal is confirmed on the closed candle (barstate.isconfirmed) to avoid premature signals.
dir is undefined (na(dir)), preventing repeated signals in the same direction.
A sell signal is generated when:
The previous candle is bullish (ha_bull ), indicating a temporary upward move before a potential reversal.
The fast moving average (ma1) is below the slow moving average (ma2), confirming a downtrend.
The current candle is bearish (ha_bear), showing trend continuation to the downside.
The Heikin Ashi close is below the fast moving average (ma1), reinforcing bearish pressure.
The real price close is below the open (close < open), confirming bearish momentum in actual price data.
The signal is confirmed after the candle closes (barstate.isconfirmed), avoiding premature entries.
dir is undefined (na(dir)), preventing consecutive signals in the same direction.
In simple terms, this setup looks for trend continuation after a pullback, confirming entries with both Heikin Ashi and real price action, supported by moving average alignment to avoid false signals.
If the price reaches a 1:1 risk-to-reward ratio, the stop will be moved to the entry point. However, if the slow moving average surpasses this level, it will become the new exit point, acting as a trailing stop
🔷Why It’s Unique
Easily visualizes the benefits of using risk-to-reward ratios when trading instead of fixed percentages.
Provides a simple and straightforward approach to trading, embracing the "keep it simple" concept.
Offers clear visualization of DCA Bot entry and exit points based on user preferences.
Includes an option to review the message format before sending signals to bots, with compatibility for multi-pair and futures contract pairs.
🔷 Considerations Before Using the Indicator
⚠️Very important: The indicator must be used on charts with real price data, such as Japanese candlesticks, line charts, etc. Do not use it on Heikin Ashi charts, as this may lead to unrealistic results.
🔸Since this is a trend-following strategy, use it on timeframes above 4 hours, where market noise is reduced and trends are clearer. Also, carefully review the statistics before using it, focusing on pairs that tend to have long periods of well-defined trends.
🔸Disadvantages:
False Signals in Ranges: Consolidating markets can generate unreliable signals.
Lagging Indicator: Being based on moving averages, it may react late to sudden price movements.
🔸Advantages:
Trend Focused: Simplifies the identification of trending markets.
Noise Reduction: Uses Heikin Ashi candles to identify trend continuation after pullbacks.
Broad Applicability: Suitable for forex, crypto, stocks, and commodities.
🔸The strategy provides a systematic way to analyze markets but does not guarantee successful outcomes. Use it as an additional tool rather than relying solely on an automated system.
Trading results depend on various factors, including market conditions, trader discipline, and risk management. Past performance does not ensure future success, so always approach the market cautiously.
🔸Risk Management: Define stop-loss levels, position sizes, and profit targets before entering any trade. Be prepared for potential losses and ensure your approach aligns with your overall trading plan.
🔷 STRATEGY PROPERTIES
Symbol: BINANCE:BTCUSDT (Spot).
Timeframe: 4h.
Test Period: All historical data available.
Initial Capital: 10000 USDT.
Order Size per Trade: 1% of Capital, you can use a higher value e.g. 5%, be cautious that the Max Drawdown does not exceed 10%, as it would indicate a very risky trading approach.
Commission: Binance commission 0.1%, adjust according to the exchange being used, lower numbers will generate unrealistic results. By using low values e.g. 5%, it allows us to adapt over time and check the functioning of the strategy.
Slippage: 5 ticks, for pairs with low liquidity or very large orders, this number should be increased as the order may not be filled at the desired level.
Margin for Long and Short Positions: 100%.
Indicator Settings: Default Configuration.
MA1 Length: 9.
MA2 Length: 18.
MA Calculations: EMA.
Take Profit Ratio: Disable. Ratio 1:4.
Breakeven Ratio: Enable, Ratio 1:1.
Strategy: Long & Short.
🔷 STRATEGY RESULTS
⚠️Remember, past results do not guarantee future performance.
Net Profit: +324.88 USDT (+3.25%).
Max Drawdown: -81.18 USDT (-0.78%).
Total Closed Trades: 672.
Percent Profitable: 35.57%.
Profit Factor: 1.347.
Average Trade: +0.48 USDT (+0.48%).
Average # Bars in Trades: 13.
🔷 HOW TO USE
🔸 Adjust Settings:
The default values—MA1 (9) and MA2 (18) with EMA calculation—generally work well. However, you can increase these values, such as 20 and 40, to better identify stronger trends.
🔸 Choose a Symbol that Typically Trends:
Select an asset that tends to form clear trends. Keep in mind that the Strategy Tester results may show poor performance for certain assets, making them less suitable for sending signals to bots.
🔸 Experiment with Ratios:
Test different take profit and breakeven ratios to compare various scenarios—especially to observe how the strategy performs when only the trade is protected.
🔸This is an example of how protecting the trade works: once the price moves in favor of the position with a 1:1 risk-to-reward ratio, the stop loss is moved to the entry price. If the Slow MA surpasses this level, it will act as a trailing stop, aiming to follow the trend and maximize potential gains.
🔸In contrast, in this example, for the same trade, if we set a take profit at a 1:3 risk-to-reward ratio—which is generally considered a good risk-reward relationship—we can see how a significant portion of the upward move is left on the table.
🔸Results Review:
It is important to check the Max Drawdown. This value should ideally not exceed 10% of your capital. Consider adjusting the trade size to ensure this threshold is not surpassed.
Remember to include the correct values for commission and slippage according to the symbol and exchange where you are conducting the tests. Otherwise, the results will not be realistic.
If you are satisfied with the results, you may consider automating your trades. However, it is strongly recommended to use a small amount of capital or a demo account to test proper execution before committing real funds.
🔸Create alerts to trigger the DCA Bot:
Verify Messages: Ensure the message matches the one specified by the DCA Bot.
Multi-Pair Configuration: For multi-pair setups, enable the option to add the symbol in the correct format.
Signal Settings: Enable whether you want to receive long or short signals (Entry | TP | SL), copy and paste the the messages for the DCA Bots configured.
Alert Setup:
When creating an alert, set the condition to the indicator and choose "alert() function call only.
Enter any desired Alert Name.
Open the Notifications tab, enable Webhook URL, and paste the Webhook URL.
For more details, refer to the section: "How to use TradingView Custom Signals".
Finalize Alerts: Click Create, you're done! Alerts will now be sent automatically in the correct format.
🔷 INDICATOR SETTINGS
MA 1: Fast MA Length
MA 2: Slow MA Length
MA Calc: MA's Calculations (SMA,EMA, RMA,WMA)
TP Ratio: This is the take profit ratio relative to the stop loss, where the trade will be closed in profit.
BE Ratio: This is the breakeven ratio relative to the stop loss, where the stop loss will be updated to breakeven or if the MA2 is greater than this level.
Strategy: Order Type direction in which trades are executed.
Use Custom Test Period: When enabled signals only works in the selected time window. If disabled it will use all historical data available on the chart.
Test Start and End: Once the Custom Test Period is enabled, here you select the start and end date that you want to analyze.
Check Messages: Enable the table to review the messages to be sent to the bot.
Entry | TP | SL: Enable this options to send Buy Entry, Take Profit (TP), and Stop Loss (SL) signals.
Deal Entry and Deal Exit : Copy and paste the message for the deal start signal and close order at Market Price of the DCA Bot. This is the message that will be sent with the alert to the Bot, you must verify that it is the same as the bot so that it can process properly so that it executes and starts the trade.
DCA Bot Multi-Pair: You must activate it if you want to use the signals in a DCA Bot Multi-pair in the text box you must enter (using the correct format) the symbol in which you are creating the alert, you can check the format of each symbol when you create the bot.
👨🏻💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented.
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The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
Smart MA Crossover BacktesterSmart MA Crossover Backtester - Strategy Overview
Strategy Name: Smart MA Crossover Backtester
Published on: TradingView
Applicable Markets: Works well on crypto (tested profitably on ETH)
Strategy Concept
The Smart MA Crossover Backtester is an improved Moving Average (MA) crossover strategy that incorporates a trend filter and an ATR-based stop loss & take profit mechanism for better risk management. It aims to capture trends efficiently while reducing false signals by only trading in the direction of the long-term trend.
Core Components & Logic
Moving Averages (MA) for Entry Signals
Fast Moving Average (9-period SMA)
Slow Moving Average (21-period SMA)
A trade signal is generated when the fast MA crosses the slow MA.
Trend Filter (200-period SMA)
Only enters long positions if price is above the 200-period SMA (bullish trend).
Only enters short positions if price is below the 200-period SMA (bearish trend).
This helps in avoiding counter-trend trades, reducing whipsaws.
ATR-Based Stop Loss & Take Profit
Uses the Average True Range (ATR) with a multiplier of 2 to calculate stop loss.
Risk-Reward Ratio = 1:2 (Take profit is set at 2x ATR).
This ensures dynamic stop loss and take profit levels based on market volatility.
Trading Rules
✅ Long Entry (Buy Signal):
Fast MA (9) crosses above Slow MA (21)
Price is above the 200 MA (bullish trend filter active)
Stop Loss: Below entry price by 2× ATR
Take Profit: Above entry price by 4× ATR
✅ Short Entry (Sell Signal):
Fast MA (9) crosses below Slow MA (21)
Price is below the 200 MA (bearish trend filter active)
Stop Loss: Above entry price by 2× ATR
Take Profit: Below entry price by 4× ATR
Why This Strategy Works Well for Crypto (ETH)?
🔹 Crypto markets are highly volatile – ATR-based stop loss adapts dynamically to market conditions.
🔹 Long-term trend filter (200 MA) ensures trading in the dominant direction, reducing false signals.
🔹 Risk-reward ratio of 1:2 allows for profitable trades even with a lower win rate.
This strategy has been tested on Ethereum (ETH) and has shown profitable performance, making it a strong choice for crypto traders looking for trend-following setups with solid risk management. 🚀
Stochastic-Dynamic Volatility Band ModelThe Stochastic-Dynamic Volatility Band Model is a quantitative trading approach that leverages statistical principles to model market volatility and generate buy and sell signals. The strategy is grounded in the concepts of volatility estimation and dynamic market regimes, where the core idea is to capture price fluctuations through stochastic models and trade around volatility bands.
Volatility Estimation and Band Construction
The volatility bands are constructed using a combination of historical price data and statistical measures, primarily the standard deviation (σ) of price returns, which quantifies the degree of variation in price movements over a specific period. This methodology is based on the classical works of Black-Scholes (1973), which laid the foundation for using volatility as a core component in financial models. Volatility is a crucial determinant of asset pricing and risk, and it plays a pivotal role in this strategy's design.
Entry and Exit Conditions
The entry conditions are based on the price’s relationship with the volatility bands. A long entry is triggered when the price crosses above the lower volatility band, indicating that the market may have been oversold or is experiencing a reversal to the upside. Conversely, a short entry is triggered when the price crosses below the upper volatility band, suggesting overbought conditions or a potential market downturn.
These entry signals are consistent with the mean reversion theory, which asserts that asset prices tend to revert to their long-term average after deviating from it. According to Poterba and Summers (1988), mean reversion occurs due to overreaction to news or temporary disturbances, leading to price corrections.
The exit condition is based on the number of bars that have elapsed since the entry signal. Specifically, positions are closed after a predefined number of bars, typically set to seven bars, reflecting a short-term trading horizon. This exit mechanism is in line with short-term momentum trading strategies discussed in literature, where traders capitalize on price movements within specific timeframes (Jegadeesh & Titman, 1993).
Market Adaptability
One of the key features of this strategy is its dynamic nature, as it adapts to the changing volatility environment. The volatility bands automatically adjust to market conditions, expanding in periods of high volatility and contracting when volatility decreases. This dynamic adjustment helps the strategy remain robust across different market regimes, as it is capable of identifying both trend-following and mean-reverting opportunities.
This dynamic adaptability is supported by the adaptive market hypothesis (Lo, 2004), which posits that market participants evolve their strategies in response to changing market conditions, akin to the adaptive nature of biological systems.
References:
Black, F., & Scholes, M. (1973). The Pricing of Options and Corporate Liabilities. Journal of Political Economy, 81(3), 637-654.
Bollinger, J. (1980). Bollinger on Bollinger Bands. Wiley.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
Lo, A. W. (2004). The Adaptive Markets Hypothesis: Market Efficiency from an Evolutionary Perspective. Journal of Portfolio Management, 30(5), 15-29.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
