EMA 5 Alert Candle ShortThe 5 EMA (Exponential Moving Average) Strategy is a simple yet effective trading strategy that helps traders identify short-term trends and potential entry and exit points. This strategy is widely used in intraday and swing trading, particularly in forex, stocks, and crypto markets.
Components of the 5 EMA Strategy
5 EMA: A fast-moving average that reacts quickly to price movements.
15-minute or 1-hour timeframe (commonly used, but adaptable to other timeframes).
Candlestick Patterns: To confirm entry signals.
How the 5 EMA Strategy Works
Buy (Long) Setup:
Price Above the 5 EMA: The price should be trading above the 5 EMA.
Pullback to the 5 EMA: A minor retracement or consolidation near the 5 EMA.
Bullish Candlestick Confirmation: A bullish candle (e.g., engulfing or pin bar) forms near the 5 EMA.
Entry: Enter a long trade at the close of the bullish candle.
Stop Loss: Place below the recent swing low or 5-10 pips below the 5 EMA.
Take Profit: Aim for a risk-reward ratio of at least 1:2 or trail the stop using a higher EMA (e.g., 10 or 20 EMA).
Sell (Short) Setup:
Price Below the 5 EMA: The price should be trading below the 5 EMA.
Pullback to the 5 EMA: A small retracement towards the 5 EMA.
Bearish Candlestick Confirmation: A bearish candle (e.g., engulfing or pin bar) near the 5 EMA.
Entry: Enter a short trade at the close of the bearish candle.
Stop Loss: Place above the recent swing high or 5-10 pips above the 5 EMA.
Take Profit: Aim for a 1:2 risk-reward ratio or use a trailing stop.
Additional Filters for Better Accuracy
Higher Timeframe Confirmation: Check the trend on a higher timeframe (e.g., 1-hour or 4-hour).
Volume Confirmation: Enter trades when volume is increasing.
Avoid Sideways Market: Use the strategy only when the market is trending.
Advantages of the 5 EMA Strategy
✔️ Simple and easy to use.
✔️ Works well in trending markets.
✔️ Helps traders capture short-term momentum.
Disadvantages
❌ Less effective in choppy or sideways markets.
❌ Requires discipline in following stop-loss rules.
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SMA Strategy Builder: Create & Prove Profitability📄 Pine Script Strategy Description (For Publishing on TradingView)
🎯 Strategy Title:
SMA Strategy Builder: Create & Prove Profitability
✨ Description:
This tool is designed for traders who want to build, customize, and prove their own SMA-based trading strategies. The strategy tracks capital growth in real-time, providing clear evidence of profitability after each trade. Users can adjust key parameters such as SMA period, take profit levels, and initial capital, making it a flexible solution for backtesting and strategy validation.
🔍 Key Features:
✅ SMA-Based Logic:
Core trading logic revolves around the Simple Moving Average (SMA).
SMA period is fully adjustable to suit various trading styles.
🎯 Customizable Take Profit (TP):
User-defined TP percentages per position.
TP line displayed as a Step Line with Breaks for clear segmentation.
Visual 🎯TP label for quick identification of profit targets.
💵 Capital Tracking (Proof of Profitability):
Initial capital is user-defined.
Capital balance updates after each closed trade.
Shows both absolute profit/loss and percentage changes for every position.
Darker green profit labels for better readability and dark red for losses.
📈 Capital Curve (Performance Visualization):
Capital growth curve available (hidden by default, can be enabled via settings).
📏 Dynamic Label Positioning:
Label positions adjust dynamically based on the price range.
Ensures consistent visibility across low and high-priced assets.
⚡ How It Works:
Long Entry:
Triggered when the price crosses above the SMA.
TP level is calculated as a user-defined percentage above the entry price.
Short Entry:
Triggered when the price crosses below the SMA.
TP level is calculated as a user-defined percentage below the entry price.
TP Execution:
Positions close immediately once the TP level is reached (no candle close confirmation needed).
🔔 Alerts:
🟩 Long Signal Alert: When the price crosses above the SMA.
🟥 Short Signal Alert: When the price crosses below the SMA.
🎯 TP Alert: When the TP target is reached.
⚙️ Customization Options:
📅 SMA Period: Choose the moving average period that best fits your strategy.
🎯 Take Profit (%): Adjust TP percentages for flexible risk management.
💵 Initial Capital: Set the starting capital for realistic backtesting.
📈 Capital Curve Toggle: Enable or disable the capital curve to track overall performance.
🌟 Why Use This Tool?
🔧 Flexible Strategy Creation: Adjust core parameters and create tailored SMA-based strategies.
📈 Performance Proof: Capital tracking acts as real proof of profitability after each trade.
🎯 Immediate TP Execution: No waiting for candle closures; profits lock in as soon as targets are hit.
💹 Comprehensive Performance Insights: Percentage-based and absolute capital tracking with dynamic visualization.
🏦 Clean Visual Indicators: Strategy insights made clear with dynamic labeling and adjustable visuals.
⚠️ Disclaimer:
This script is provided for educational and informational purposes only. Trading financial instruments carries risk, and past performance does not guarantee future results. Always perform your own due diligence before making any trading decisions.
Indicator BMS V5 [Traderhood]Introducing BMS (Base Market Strategy)
Overview
Base Market Strategy (BMS) is a trend-following and oscillator indicator designed to detect market trends with high accuracy while providing clear entry signals. BMS utilizes four Exponential Moving Averages (EMA) to filter trends across multiple timeframes and Bollinger Bands (BB) to identify overbought and oversold zones. This approach makes BMS highly suitable for scalping strategies in lower timeframes with a high win rate potential.
Key Features
📈 Multi-EMA Trend Filtering
Uses 4 EMAs to confirm the dominant trend.
Separates trend detection between lower timeframes and H1 for additional validation.
🎯 Dynamic Overbought & Oversold Detection
Sell signal occurs when the price touches the Bollinger Bands Upper.
Buy signal occurs when the price touches the Bollinger Bands Lower.
🔥 High Win Rate Scalping Strategy
Designed to capture quick price movements in trending markets.
Ideal for traders looking for fast executions with controlled risk.
🎨 Customizable Visual Enhancements
Users can adjust indicator colors to match their personal preferences.
How It Works
1️⃣ EMA-Based Trend Identification
The indicator applies 4 EMAs to determine short-term and medium-term trends.
If the price is above all EMAs → Bullish trend.
If the price is below all EMAs → Bearish trend.
2️⃣ Bollinger Bands Signal Generation
Sell Entry: When the price touches Bollinger Bands Upper, indicating an overbought area.
Buy Entry: When the price touches Bollinger Bands Lower, indicating an oversold area.
3️⃣ Scalping Execution
Entries are executed only on lower timeframes with trend confirmation from H1 EMA.
Profit targets are adjusted based on volatility, while stop loss is placed outside the Bollinger Bands.
4️⃣ Visual Customization
Indicator colors can be modified for better visibility.
Practical Applications
✅ Scalping Strategy – Uses Bollinger Bands and EMA filtering for fast trades.
✅ Trend Confirmation – Multi-timeframe EMA validation ensures precise entries.
✅ Dynamic Support & Resistance – Bollinger Bands help identify potential reversals.
✅ Noise Reduction – EMA filtering removes minor price fluctuations for clearer signals.
🛠 Settings
EMA Periods: 4 EMAs for trend filtering.
Bollinger Bands Length: 20 (default), adjustable.
Bollinger Bands Deviation: 2 (default).
Color Customization: Users can personalize indicator colors as needed.
📌 Conclusion
Base Market Strategy (BMS) is a high win-rate scalping indicator, combining trend-following EMA filtering with momentum reversal detection from Bollinger Bands. With a dynamic and adaptive approach, this indicator provides precise entry signals while reducing noise from insignificant price movements.
Key Takeaways:
✔ High Accuracy – A combination of EMA and Bollinger Bands provides clear signals.
✔ Scalping Optimization – Works best on lower timeframes with H1 validation.
✔ Visual Customization – Users can adjust the indicator colors to their preference.
✔ Simple Yet Powerful – Easy to use but highly effective in capturing market opportunities.
🔹 Disclaimer: Trading carries high risks. Always backtest and optimize settings to align with your risk tolerance before live trading.
PRC-ALMA | QuantEdgeBIntroducing PRC-ALMA by QuantEdgeB
Overview
The PRC-ALMA (Percentile Adaptive ALMA) is an advanced dynamic trend and volatility filtering indicator that leverages the Arnaud Legoux Moving Average (ALMA) combined with Percentile Rank Filtering and Median Absolute Deviation (MAD) Bands. It is designed to enhance market structure clarity, detect breakout zones, and provide trade signals by dynamically adjusting its filtering based on recent price action.
____
Key Features
1. 📈 Adaptive ALMA Smoothing:
- Uses ALMA for smoothing price action while reducing lag.
- Provides a more responsive moving average than traditional EMAs and SMAs.
2. 📊 Percentile Rank-Based Thresholds:
- Determines upper and lower regions using 75th and 25th percentile ranks.
- Allows for adaptive thresholding based on historical price movements.
3. 🎯 Median Absolute Deviation (MAD) Volatility Filtering:
- Filters out noise using robust statistical deviation measures.
- MAD Bands dynamically adjust based on volatility expansion and contraction.
4. 🔄 Dynamic Trade Signals:
- Generates long signals when price exceeds the upper threshold.
- Generates short signals when price drops below the lower threshold.
5. 🎨 Customizable Color Modes & Visual Enhancements:
- Choose between multiple color schemes to match trading preferences.
- Optional candlestick coloring to indicate market sentiment shifts.
____
How It Works
1. ALMA Calculation:
- The indicator starts by computing the ALMA (Arnaud Legoux Moving Average) with a customizable length, offset, and sigma.
2. Percentile Rank Filtering:
- It then calculates the 75th and 25th percentile ranks over a selected period, determining dynamic levels for trend identification.
3. Volatility Adjustment Using Median Absolute Deviation (MAD):
- MAD is applied to filter noise and adapt the upper/lower bands based on market volatility.
- The higher the MAD multiplier, the wider the bands, allowing more price fluctuations before a signal triggers.
4. Entry & Exit Conditions:
- Long Entry: When price crosses above the upper percentile band + MAD filter.
- Short Entry: When price crosses below the lower percentile band - MAD filter.
5. Visual Enhancements:
- Dynamic band plotting with shading between percentile ranks.
- Candlestick coloring to visually indicate long/short sentiment shifts.
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Practical Applications
✅ Trend Following & Momentum Trading – Uses ALMA for trend smoothing and percentile-based breakouts.
✅ Mean Reversion Strategies – Adaptive MAD filtering ensures only significant deviations trigger signals.
✅ Multi-Timeframe Trading – Works on intraday, daily, and weekly timeframes based on user customization.
✅ Noise Reduction – Eliminates minor fluctuations while capturing meaningful market moves.
____
🛠 Settings
-ALMA Length: 24 – Defines the smoothing period for the Arnaud Legoux Moving Average.
-ALMA Offset: 0.7 – Adjusts the shift factor, controlling responsiveness.
-ALMA Sigma: 4 – Determines the smoothing strength, balancing trend-following and noise reduction.
-Percentile Length: 21 – Lookback period for calculating percentile rank levels.
-Median Period: 21 – The period used for the Median Absolute Deviation (MAD) filter.
-Median Multiplier: 1.8 – Adjusts the sensitivity of the MAD filter, impacting how signals are generated.
-Color Mode: Strategy – Various visual themes available for better chart readability.
-Signal Label: Off - If turned off the indicator produced a Long or Cash signal when the trend changes.
📌 Conclusion
The PRC-ALMA | QuantEdgeB is an advanced valuation and signal generation tool that dynamically adjusts based on market conditions. By combining ALMA for trend smoothing, percentile rank thresholds, and MAD-based volatility filtering, it provides traders with a versatile indicator for momentum, breakout, and mean reversion strategies.
Key Takeaways:
✔ Smooth & Adaptive – ALMA ensures minimal lag while maintaining trend responsiveness.
✔ Dynamic Overbought/Oversold Zones – Adjusts to real-time market conditions using percentile-based bands.
✔ Volatility-Aware Filtering – Uses MAD to eliminate market noise, making signals more reliable.
✔ Customizable & Multi-Timeframe Ready – Works on various asset classes and timeframes with adjustable settings.
🔹 Disclaimer: Past performance is not indicative of future results. No trading strategy can guarantee success in financial markets.
🔹 Strategic Advice: Always backtest, optimize, and align parameters with your trading objectives and risk tolerance before live trading.
EMA Crossover Backtest [BarScripts]This indicator lets you backtest an EMA crossover strategy with built-in risk management and trade tracking. It simulates long and short trades based on EMA crossovers, allowing you to fine-tune entry conditions, stop-loss placement, and reward/risk settings.
🔹 How It Works:
Long Entry: Fast EMA crosses above Slow EMA, and price closes above Fast EMA.
Short Entry: Fast EMA crosses below Slow EMA, and price closes below Fast EMA.
Stop Loss: Set based on previous bars or a fixed amount.
Take Profit: Adjustable reward/risk ratio.
Higher Timeframe Confluence: Confirms trades based on a larger timeframe.
Trade Hours Filter: Limits trades to specific time windows.
🔹 Key Features:
✅ Shows Entry & Exit Points with visual trade lines.
✅ Customizable EMA Lengths to fit any strategy.
✅ P&L Tracking & Statistics to measure performance.
✅ Position Sizing Options: Fixed position, fixed risk, or percentage of balance.
✅ Commissions Tracking (based on total trades, not contracts).
Use this tool to fine-tune your EMA crossover strategy and see how it performs over time! 🚀
💬 Let me know your feedback—suggest improvements, report issues, or request new features!
Prev Day High EMA Crossover with 7-Day SMA Trailing StopPrev Day High EMA Crossover with 7-Day SMA Trailing Stop
Overview
This indicator is designed for traders who seek high-probability breakout trades using a combination of Exponential Moving Averages (EMAs), the previous day's high, and a 7-day Simple Moving Average (SMA) trailing stop. It helps identify bullish and bearish crossover signals while ensuring confirmation with price action above or below key levels.
How It Works
1. Entry Signals:
✅ Bullish Entry:
The 9 EMA crosses above the 15 EMA (bullish momentum).
The price is above the previous day’s high (confirming a breakout).
The candle closes above the open (bullish confirmation).
✅ Bearish Entry:
The 9 EMA crosses below the 15 EMA (bearish momentum).
The price is below the previous day’s high (confirming a failure to break higher).
The candle closes below the open (bearish confirmation).
2. Exit Strategy (Trailing Stop):
📌 Long Exit: If in a long trade, exit when the price closes below the 7-day SMA.
📌 Short Exit: If in a short trade, exit when the price closes above the 7-day SMA.
Bitcoin 1H-15M Breakout StrategyKey Features
1H and 15M Timeframes:
The script uses the 1-hour timeframe for the range and 15-minute timeframe for breakout conditions.
request.security is used to fetch the higher timeframe data.
Risk Management:
Variables entry_price, sl_price, and tp_price are declared explicitly as float with na initialization to handle dynamic assignment.
Stop-loss and take-profit levels are calculated based on the specified Risk-Reward Ratio (RRR) and buffer (in pips).
Trade Logic:
Long trade triggered when the 15-minute candle closes above the 1-hour high.
Short trade triggered when the 15-minute candle closes below the 1-hour low.
Visualization:
The range_high and range_low (previous 1-hour high and low) are plotted on the chart using dashed lines.
Debugging:
Enabling the show_debug input displays labels showing stop-loss and take-profit values for easier troubleshooting.
JJ Highlight Time Ranges with First 5 Minutes and LabelsTo effectively use this Pine Script as a day trader , here’s how the various elements can help you manage trades, track time sessions, and monitor price movements:
Key Components for a Day Trader:
1. First 5-Minute Highlight:
- Purpose: Day traders often rely on the first 5 minutes of the trading session to gauge market sentiment, watch for opening price gaps, or plan entries. This script draws a horizontal line at the high or low of the first 5 minutes, which can act as a key level for the rest of the day.
- How to Use: If the price breaks above or below the first 5-minute line, it can signal momentum. You might enter a long position if the price breaks above the first 5-minute high or a short if it breaks below the first 5-minute low.
2. Session Time Highlights:
- Morning Session (9:15–10:30 AM): The market often shows its strongest price action during the first hour of trading. This session is highlighted in yellow. You can use this highlight to focus on the most volatile period, as this is when large institutional moves tend to occur.
- Afternoon Session (12:30–2:55 PM): The blue highlight helps you track the mid-afternoon session, where liquidity may decrease, and price action can sometimes be choppier. Day traders should be more cautious during this period.
- How to Use: By highlighting these key times, you can:
- Focus on key breakouts during the morning session.
- Be more conservative in your trades during the afternoon, as market volatility may drop.
3. Dynamic Labels:
- Top/Bottom Positioning: The script places labels dynamically based on the selected position (Top or Bottom). This allows you to quickly glance at the session's start and identify where you are in terms of time.
- How to Use: Use these labels to remind yourself when major time segments (morning or afternoon) begin. You can adjust your trading strategy depending on the session, e.g., being more aggressive in the morning and more cautious in the afternoon.
Trading Strategy Suggestions:
1. Momentum Trades:
- After the first 5 minutes, use the high/low of that period to set up breakout trades.
- Long Entry: If the price breaks the high of the first 5 minutes (especially if there's a strong trend).
- Short Entry: If the price breaks the low of the first 5 minutes, signaling a potential downtrend.
2. Session-Based Strategy:
- Morning Session (9:15–10:30 AM):
- Look for strong breakout patterns such as support/resistance levels, moving average crossovers, or candlestick patterns (like engulfing candles or pin bars).
- This is a high liquidity period, making it ideal for executing quick trades.
- Afternoon Session (12:30–2:55 PM):
- The market tends to consolidate or show less volatility. Scalping and mean-reversion strategies work better here.
- Avoid chasing big moves unless you see a clear breakout in either direction.
3. Support and Resistance:
- The first 5-minute high/low often acts as a key support or resistance level for the rest of the day. If the price holds above or below this level, it’s an indication of trend continuation.
4. Breakout Confirmation:
- Look for breakouts from the highlighted session time ranges (e.g., 9:15 AM–10:30 AM or 12:30 PM–2:55 PM).
- If a breakout happens during a key time window, combine that with other technical indicators like volume spikes , RSI , or MACD for confirmation.
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Example Day Trader Usage:
1. First 5 Minutes Strategy: After the market opens at 9:15 AM, watch the price action for the first 5 minutes. The high and low of these 5 minutes are critical levels. If the price breaks above the high of the first 5 minutes, it might indicate a strong bullish trend for the day. Conversely, breaking below the low may suggest bearish movement.
2. Morning Session: After the first 5 minutes, focus on the **9:15 AM–10:30 AM** window. During this time, look for breakout setups at key support/resistance levels, especially when paired with high volume or momentum indicators. This is when many institutions make large trades, so price action tends to be more volatile and predictable.
3. Afternoon Session: From 12:30 PM–2:55 PM, the market might experience lower volatility, making it ideal for scalping or range-bound strategies. You could look for reversals or fading strategies if the market becomes too quiet.
Conclusion:
As a day trader, you can use this script to:
- Track and react to key price levels during the first 5 minutes.
- Focus on high volatility in the morning session (9:15–10:30 AM) and **be cautious** during the afternoon.
- Use session-based timing to adjust your strategies based on the time of day.
Dynamic Volatility Differential Model (DVDM)The Dynamic Volatility Differential Model (DVDM) is a quantitative trading strategy designed to exploit the spread between implied volatility (IV) and historical (realized) volatility (HV). This strategy identifies trading opportunities by dynamically adjusting thresholds based on the standard deviation of the volatility spread. The DVDM is versatile and applicable across various markets, including equity indices, commodities, and derivatives such as the FDAX (DAX Futures).
Key Components of the DVDM:
1. Implied Volatility (IV):
The IV is derived from options markets and reflects the market’s expectation of future price volatility. For instance, the strategy uses volatility indices such as the VIX (S&P 500), VXN (Nasdaq 100), or RVX (Russell 2000), depending on the target market. These indices serve as proxies for market sentiment and risk perception (Whaley, 2000).
2. Historical Volatility (HV):
The HV is computed from the log returns of the underlying asset’s price. It represents the actual volatility observed in the market over a defined lookback period, adjusted to annualized levels using a multiplier of \sqrt{252} for daily data (Hull, 2012).
3. Volatility Spread:
The difference between IV and HV forms the volatility spread, which is a measure of divergence between market expectations and actual market behavior.
4. Dynamic Thresholds:
Unlike static thresholds, the DVDM employs dynamic thresholds derived from the standard deviation of the volatility spread. The thresholds are scaled by a user-defined multiplier, ensuring adaptability to market conditions and volatility regimes (Christoffersen & Jacobs, 2004).
Trading Logic:
1. Long Entry:
A long position is initiated when the volatility spread exceeds the upper dynamic threshold, signaling that implied volatility is significantly higher than realized volatility. This condition suggests potential mean reversion, as markets may correct inflated risk premiums.
2. Short Entry:
A short position is initiated when the volatility spread falls below the lower dynamic threshold, indicating that implied volatility is significantly undervalued relative to realized volatility. This signals the possibility of increased market uncertainty.
3. Exit Conditions:
Positions are closed when the volatility spread crosses the zero line, signifying a normalization of the divergence.
Advantages of the DVDM:
1. Adaptability:
Dynamic thresholds allow the strategy to adjust to changing market conditions, making it suitable for both low-volatility and high-volatility environments.
2. Quantitative Precision:
The use of standard deviation-based thresholds enhances statistical reliability and reduces subjectivity in decision-making.
3. Market Versatility:
The strategy’s reliance on volatility metrics makes it universally applicable across asset classes and markets, ensuring robust performance.
Scientific Relevance:
The strategy builds on empirical research into the predictive power of implied volatility over realized volatility (Poon & Granger, 2003). By leveraging the divergence between these measures, the DVDM aligns with findings that IV often overestimates future volatility, creating opportunities for mean-reversion trades. Furthermore, the inclusion of dynamic thresholds aligns with risk management best practices by adapting to volatility clustering, a well-documented phenomenon in financial markets (Engle, 1982).
References:
1. Christoffersen, P., & Jacobs, K. (2004). The importance of the volatility risk premium for volatility forecasting. Journal of Financial and Quantitative Analysis, 39(2), 375-397.
2. Engle, R. F. (1982). Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation. Econometrica, 50(4), 987-1007.
3. Hull, J. C. (2012). Options, Futures, and Other Derivatives. Pearson Education.
4. Poon, S. H., & Granger, C. W. J. (2003). Forecasting volatility in financial markets: A review. Journal of Economic Literature, 41(2), 478-539.
5. Whaley, R. E. (2000). The investor fear gauge. Journal of Portfolio Management, 26(3), 12-17.
This strategy leverages quantitative techniques and statistical rigor to provide a systematic approach to volatility trading, making it a valuable tool for professional traders and quantitative analysts.
Fibonacci Retracement Strategy for CryptoThe Enhanced Fibonacci Retracement Strategy is designed to help traders capitalize on key Fibonacci levels for both long and short trades. This script automatically identifies significant swing highs and lows within a customizable lookback period and dynamically plots Fibonacci retracement levels (0%, 23.6%, 38.2%, 50%, 61.8%, 78.6%, and 100%) as support and resistance levels.
Key Features:
Automatic Fibonacci Levels:
The script identifies the highest high and lowest low over a user-defined lookback period to calculate Fibonacci retracement levels.
Dual-Directional Trading:
Long Trades: Triggered when the price crosses above the 61.8% retracement level, anticipating a reversal.
Short Trades: Triggered when the price crosses below the 38.2% retracement level, capturing potential downward movement.
Compact Line Option:
Users can toggle "Compact Fibonacci Lines" to reduce visual clutter on the chart, making the lines shorter and easier to interpret.
Dynamic Alerts:
Alerts are embedded directly into the strategy logic for entry and exit points.
Long Entry: Triggered when the price bounces above the 61.8% level.
Long Exit: Triggered when the price reaches the 23.6% level.
Short Entry: Triggered when the price crosses below the 38.2% level.
Short Exit: Triggered when the price reaches the 78.6% level.
Clear Visualization:
Fibonacci levels are plotted with distinct colors and dashed lines (optional compact view),
providing traders with clear and actionable levels to make decisions.
Inputs:
Lookback Period: Number of candles to calculate swing highs and lows.
Plot Fibonacci Levels: Toggle to enable/disable plotting levels.
Compact Fibonacci Lines: Reduce the length of Fibonacci lines for a cleaner chart.
How It Works:
The strategy identifies a high-low range within the lookback period.
Fibonacci levels are calculated based on the range and plotted on the chart.
Long Trade Example:
Enter when the price crosses above the 61.8% level.
Exit when the price reaches the 23.6% level.
Short Trade Example:
Enter when the price crosses below the 38.2% level.
Exit when the price reaches the 78.6% level.
Best Use Cases:
Trending Markets: Use retracements to time entries in the direction of the trend.
Range-Bound Markets: Identify and trade reversals near key Fibonacci levels.
Important Notes:
This strategy is not financial advice and should be backtested thoroughly before live trading.
Risk management is crucial! Consider using stop-loss orders for protection.
Customize inputs to suit your preferred timeframe and trading style.
Forex Pair Yield Momentum This Pine Script strategy leverages yield differentials between the 2-year government bond yields of two countries to trade Forex pairs. Yield spreads are widely regarded as a fundamental driver of currency movements, as highlighted by international finance theories like the Interest Rate Parity (IRP), which suggests that currencies with higher yields tend to appreciate due to increased capital flows:
1. Dynamic Yield Spread Calculation:
• The strategy dynamically calculates the yield spread (yield_a - yield_b) for the chosen Forex pair.
• Example: For GBP/USD, the spread equals US 2Y Yield - UK 2Y Yield.
2. Momentum Analysis via Bollinger Bands:
• Yield momentum is computed as the difference between the current spread and its moving
Bollinger Bands are applied to identify extreme deviations:
• Long Entry: When momentum crosses below the lower band.
• Short Entry: When momentum crosses above the upper band.
3. Reversal Logic:
• An optional checkbox reverses the trading logic, allowing long trades at the upper band and short trades at the lower band, accommodating different market conditions.
4. Trade Management:
• Positions are held for a predefined number of bars (hold_periods), and each trade uses a fixed contract size of 100 with a starting capital of $20,000.
Theoretical Basis:
1. Yield Differentials and Currency Movements:
• Empirical studies, such as Clarida et al. (2009), confirm that interest rate differentials significantly impact exchange rate dynamics, especially in carry trade strategies .
• Higher-yields tend to appreciate against lower-yielding currencies due to speculative flows and demand for higher returns.
2. Bollinger Bands for Momentum:
• Bollinger Bands effectively capture deviations in yield momentum, identifying opportunities where price returns to equilibrium (mean reversion) or extends in trend-following scenarios (momentum breakout).
• As Bollinger (2001) emphasized, this tool adapts to market volatility by dynamically adjusting thresholds .
References:
1. Dornbusch, R. (1976). Expectations and Exchange Rate Dynamics. Journal of Political Economy.
2. Obstfeld, M., & Rogoff, K. (1996). Foundations of International Macroeconomics.
3. Clarida, R., Davis, J., & Pedersen, N. (2009). Currency Carry Trade Regimes. NBER.
4. Bollinger, J. (2001). Bollinger on Bollinger Bands.
5. Mendelsohn, L. B. (2006). Forex Trading Using Intermarket Analysis.
Sunil High-Frequency Strategy with Simple MACD & RSISunil High-Frequency Strategy with Simple MACD & RSI
This high-frequency trading strategy uses a combination of MACD and RSI to identify quick market opportunities. By leveraging these indicators, combined with dynamic risk management using ATR, it aims to capture small but frequent price movements while ensuring tight control over risk.
Key Features:
Indicators Used:
MACD (Moving Average Convergence Divergence): The strategy uses a shorter MACD configuration (Fast Length of 6 and Slow Length of 12) to capture quick price momentum shifts. A MACD crossover above the signal line triggers a buy signal, while a crossover below the signal line triggers a sell signal.
RSI (Relative Strength Index): A shorter RSI length of 7 is used to gauge overbought and oversold market conditions. The strategy looks for RSI confirmation, with a long trade initiated when RSI is below the overbought level (70) and a short trade initiated when RSI is above the oversold level (30).
Risk Management:
Dynamic Stop Loss and Take Profit: The strategy uses ATR (Average True Range) to calculate dynamic stop loss and take profit levels based on market volatility.
Stop Loss is set at 0.5x ATR to limit risk.
Take Profit is set at 1.5x ATR to capture reasonable price moves.
Trailing Stop: As the market moves in the strategy’s favor, the position is protected by a trailing stop set at 0.5x ATR, allowing the strategy to lock in profits as the price moves further.
Entry & Exit Signals:
Long Entry: Triggered when the MACD crosses above the signal line (bullish crossover) and RSI is below the overbought level (70).
Short Entry: Triggered when the MACD crosses below the signal line (bearish crossover) and RSI is above the oversold level (30).
Exit Conditions: The strategy exits long or short positions based on the stop loss, take profit, or trailing stop activation.
Frequent Trades:
This strategy is designed for high-frequency trading, with trade signals occurring frequently as the MACD and RSI indicators react quickly to price movements. It works best on lower timeframes such as 1-minute, 5-minute, or 15-minute charts, but can be adjusted for different timeframes based on the asset’s volatility.
Customizable Parameters:
MACD Settings: Adjust the Fast Length, Slow Length, and Signal Length to tune the MACD’s sensitivity.
RSI Settings: Customize the RSI Length, Overbought, and Oversold levels to better match your trading style.
ATR Settings: Modify the ATR Length and multipliers for Stop Loss, Take Profit, and Trailing Stop to optimize risk management according to market volatility.
Important Notes:
Market Conditions: This strategy is designed to capture smaller, quicker moves in trending markets. It may not perform well during choppy or sideways markets.
Optimizing for Asset Volatility: Adjust the ATR multipliers based on the asset’s volatility to suit the risk-reward profile that fits your trading goals.
Backtesting: It's recommended to backtest the strategy on different assets and timeframes to ensure optimal performance.
Summary:
The Sunil High-Frequency Strategy leverages a simple combination of MACD and RSI with dynamic risk management (using ATR) to trade small but frequent price movements. The strategy ensures tight stop losses and reasonable take profits, with trailing stops to lock in profits as the price moves in favor of the trade. It is ideal for scalping or intraday trading on lower timeframes, aiming for quick entries and exits with controlled risk.
EMA Crossover with RSI and DistanceEMA Crossover with RSI and Distance Strategy
This strategy combines Exponential Moving Averages (EMA) with Relative Strength Index (RSI) and distance-based conditions to generate buy, sell, and neutral signals. It is designed to help traders identify entry and exit points based on multiple technical indicators.
Key Components:
Exponential Moving Averages (EMA):
The strategy uses four EMAs: EMA 5, EMA 13, EMA 40, and EMA 55.
A buy signal (long) is triggered when EMA 5 crosses above EMA 13 and EMA 40 crosses above EMA 55.
A sell signal (short) is generated when EMA 55 crosses above EMA 40.
The distance between EMAs (5 and 13) is also important. If the current distance between EMA 5 and EMA 13 is smaller than the average distance over the last 5 candles, a neutral condition is triggered, preventing a signal even if all other conditions are met.
Relative Strength Index (RSI):
The 14-period RSI is used to determine market strength and direction.
The strategy requires RSI to be above 50 and greater than the average RSI (over the past 14 periods) for a buy signal.
If the RSI is above 60, a green signal is given, indicating a strong bullish condition, even if the EMA conditions are not fully met.
If the RSI is below 40, a red signal is given, indicating a strong bearish condition, regardless of the EMA crossover.
Distance Conditions:
The strategy calculates the distance between EMA 5 and EMA 13 on each candle and compares it to the average distance of the last 5 candles.
If the current distance between EMA 5 and EMA 13 is lower than the average of the last 5 candles, a neutral signal is triggered. This helps avoid entering a trade when the market is losing momentum.
Additionally, if the distance between EMA 40 and EMA 13 is greater than the previous distance, the previous signal is kept intact, ensuring that the trend is still strong enough for the signal to remain valid.
Signal Persistence:
Once a buy (green) or sell (red) signal is triggered, it remains intact as long as the price is closing above EMA 5 for long trades or below EMA 55 for short trades.
If the price moves below EMA 5 for long trades or above EMA 55 for short trades, the signal is recalculated based on the most recent conditions.
Signal Display:
Green Signals: Represent a strong buy signal and are shown below the candle when the RSI is above 60.
Red Signals: Represent a strong sell signal and are shown above the candle when the RSI is below 40.
Neutral Signals: Displayed when the conditions for entry are not met, specifically when the EMA distance condition is violated.
Long and Short Signals: Additional signals are shown based on the EMA crossovers and RSI conditions. These signals are plotted below the candle for long positions and above the candle for short positions.
Trade Logic:
Long Entry: Enter a long trade when EMA 5 crosses above EMA 13, EMA 40 crosses above EMA 55, and the RSI is above 50 and greater than the average RSI. Additionally, the current distance between EMA 5 and EMA 13 should be larger than the average distance of the last 5 candles.
Short Entry: Enter a short trade when EMA 55 crosses above EMA 40 and the RSI is below 40.
Neutral Condition: If the distance between EMA 5 and EMA 13 is smaller than the average distance over the last 5 candles, the strategy will not trigger a signal, even if other conditions are met.
Trend Trader-Remastered StrategyOfficial Strategy for Trend Trader - Remastered
Indicator: Trend Trader-Remastered (TTR)
Overview:
The Trend Trader-Remastered is a refined and highly sophisticated implementation of the Parabolic SAR designed to create strategic buy and sell entry signals, alongside precision take profit and re-entry signals based on marked Bill Williams (BW) fractals. Built with a deep emphasis on clarity and accuracy, this indicator ensures that only relevant and meaningful signals are generated, eliminating any unnecessary entries or exits.
Please check the indicator details and updates via the link above.
Important Disclosure:
My primary objective is to provide realistic strategies and a code base for the TradingView Community. Therefore, the default settings of the strategy version of the indicator have been set to reflect realistic world trading scenarios and best practices.
Key Features:
Strategy execution date&time range.
Take Profit Reduction Rate: The percentage of progressive reduction on active position size for take profit signals.
Example:
TP Reduce: 10%
Entry Position Size: 100
TP1: 100 - 10 = 90
TP2: 90 - 9 = 81
Re-Entry When Rate: The percentage of position size on initial entry of the signal to determine re-entry.
Example:
RE When: 50%
Entry Position Size: 100
Re-Entry Condition: Active Position Size < 50
Re-Entry Fill Rate: The percentage of position size on initial entry of the signal to be completed.
Example:
RE Fill: 75%
Entry Position Size: 100
Active Position Size: 50
Re-Entry Order Size: 25
Final Active Position Size:75
Important: Even RE When condition is met, the active position size required to drop below RE Fill rate to trigger re-entry order.
Key Points:
'Process Orders on Close' is enabled as Take Profit and Re-Entry signals must be executed on candle close.
'Calculate on Every Tick' is enabled as entry signals are required to be executed within candle time.
'Initial Capital' has been set to 10,000 USD.
'Default Quantity Type' has been set to 'Percent of Equity'.
'Default Quantity' has been set to 10% as the best practice of investing 10% of the assets.
'Currency' has been set to USD.
'Commission Type' has been set to 'Commission Percent'
'Commission Value' has been set to 0.05% to reflect the most realistic results with a common taker fee value.
IU EMA Channel StrategyIU EMA Channel Strategy
Overview:
The IU EMA Channel Strategy is a simple yet effective trend-following strategy that uses two Exponential Moving Averages (EMAs) based on the high and low prices. It provides clear entry and exit signals by identifying price crossovers relative to the EMAs while incorporating a built-in Risk-to-Reward Ratio (RTR) for effective risk management.
Inputs ( Settings ):
- RTR (Risk-to-Reward Ratio): Define the ratio for risk-to-reward (default = 2).
- EMA Length: Adjust the length of the EMA channels (default = 100).
How the Strategy Works
1. EMA Channels:
- High-based EMA: EMA calculated on the high price.
- Low-based EMA: EMA calculated on the low price.
The area between these two EMAs creates a "channel" that visually highlights potential support and resistance zones.
2. Entry Rules:
- Long Entry: When the price closes above the high-based EMA (crossover).
- Short Entry: When the price closes below the low-based EMA (crossunder).
These entries ensure trades are taken in the direction of momentum.
3. Stop Loss (SL) and Take Profit (TP):
- Stop Loss:
- For long positions, the SL is set at the previous bar's low.
- For short positions, the SL is set at the previous bar's high.
- Take Profit:
- TP is automatically calculated using the Risk-to-Reward Ratio (RTR) you define.
- Example: If RTR = 2, the TP will be 2x the risk distance.
4. Exit Rules:
- Positions are closed at either the stop loss or the take profit level.
- The strategy manages exits automatically to enforce disciplined risk management.
Visual Features
1. EMA Channels:
- The high and low EMAs are dynamically color-coded:
- Green: Price is above the EMA (bullish condition).
- Red: Price is below the EMA (bearish condition).
- The area between the EMAs is shaded for better visual clarity.
2. Stop Loss and Take Profit Zones:
- SL and TP levels are plotted for both long and short positions.
- Zones are filled with:
- Red: Stop Loss area.
- Green: Take Profit area.
Be sure to manage your risk and position size properly.
InspireHER Dynamic EMA RR Positioning IndicatorDynamic EMA and RR Positioning Indicator
This indicator is designed to provide traders with highly customizable buy and sell signals based on EMA (Exponential Moving Average) crossovers and Risk-to-Reward (RR) ratios. It works on any timeframe and allows users to toggle price data and additional position boxes for visualizing trade setups. Additionally, traders can choose between displaying dots or labeled signals for buy/sell indicators, making this tool versatile and user-friendly for different preferences and strategies.
What Makes This Indicator Unique
Customizable Parameters: The script offers extensive options for tailoring the indicator to your preferred trading style and strategy:
EMA: Configurable through settings (default is a 21-period EMA).
Risk-to-Reward Ratio (RR): Adjustable to meet your desired RR levels (default is 1:2.5).
Lookback Period: Visualizes buy/sell signals over the last six months.
Position Boxes for Trade Visualization: The indicator can "draw" position boxes on the chart, showing potential entry points, stop-loss (SL), and take-profit (TP) levels based on the selected RR. These visual aids simplify decision-making and help evaluate trade opportunities directly on the chart.
Price Data Toggle: Traders can choose to view or hide price data related to trade signals, including TP, SL, and RR values. By default, this is turned off to maintain a clean chart but can be activated when needed.
Flexible Signal Display Options:
Dots Mode: Displays buy signals as green dots and sell signals as red dots on the chart.
Label Mode: Displays buy signals as labels with the word "Buy" in green and sell signals as labels with the word "Sell" in red.
This toggle allows traders to customize how signals are displayed for a more personalized trading experience.
Simple Signal View: A toggle option provides a cleaner chart by enabling or disabling additional visual elements like circles or labels.
How It Works
Buy Signal: Triggered when the price crosses the EMA and closes above it.
Entry: Top of the candle.
Stop-Loss: Bottom of the candle.
Take-Profit: Calculated based on the selected RR.
Sell Signal: Triggered when the price crosses the EMA and closes below it.
Entry: Bottom of the candle.
Stop-Loss: Top of the candle.
Take-Profit: Calculated based on the selected RR.
Default Settings
EMA: 21-period.
Risk-to-Reward Ratio: 1:2.5.
Price Data: Off (can be toggled on in settings).
Position Boxes: Off (can be toggled on in settings).
Signal Display: Labels mode with "Buy" (green) and "Sell" (red) enabled by default; can be toggled to Dots mode.
Timeframe: Any timeframe supported.
How to Use
Add the Indicator to Your Chart: Once applied, the EMA line and buy/sell signals will appear by default.
Customize Settings: Navigate to the indicator's settings to adjust EMA, RR, or enable/disable Price Data, Position Boxes, or switch between Dots and Label modes.
Trade with Confidence: Use the visual aids and signals to assess trade opportunities based on your strategy and timeframe.
This indicator combines the reliability of EMA-based signals with the flexibility of configurable RR, visual trade setups, and multiple signal display options, making it a powerful tool for all types of traders. Happy Trading!!
Supertrend and MACD strategyThe Supertrend and MACD Strategy is a comprehensive trading approach designed to capitalize on market trends by using a combination of the Supertrend indicator, the Exponential Moving Average (EMA), and the Moving Average Convergence Divergence (MACD). This strategy aims to identify optimal entry and exit points for both long and short trades, while incorporating strict risk management rules.
Indicators Used:
Supertrend: This indicator is used to identify the overall trend direction. It provides clear signals for trend reversals, helping traders to enter trades in the direction of the prevailing trend.
200-period EMA: This long-term moving average is used to determine the primary trend direction. The strategy only takes long trades when the price is above the 200 EMA and short trades when the price is below it.
MACD: The MACD is used to gauge the momentum and confirm the signals provided by the Supertrend and EMA. It consists of the MACD line, the signal line, and the histogram.
Entry Conditions:
Long Entry:
The Supertrend indicator shows an uptrend (direction > 0).
The MACD line is above the signal line (macd > signal).
The price is above the 200-period EMA (close > ema200).
Short Entry:
The Supertrend indicator shows a downtrend (direction < 0).
The MACD line is below the signal line (macd < signal).
The price is below the 200-period EMA (close < ema200).
Exit Conditions:
Long Exit:
Exit the long position when the MACD line crosses below the signal line (ta.crossunder(macd, signal)).
Set a stop loss (SL) below the lowest low of the last 10 periods (lowestLow - 1).
Short Exit:
Exit the short position when the MACD line crosses above the signal line (ta.crossover(macd, signal)).
Set a stop loss (SL) above the highest high of the last 10 periods (highestHigh + 1).
Risk Management:
The strategy ensures that no new positions are opened if there is already an open trade, preventing overexposure in the market.
Alerts:
Alerts are set to notify traders when the MACD crosses the signal line, providing timely updates for potential exit points.
Composite Oscillation Indicator Based on MACD and OthersThis indicator combines various technical analysis tools to create a composite oscillator that aims to capture multiple aspects of market behavior. Here's a breakdown of its components:
* Individual RSIs (xxoo1-xxoo15): The code calculates the RSI (Relative Strength Index) of numerous indicators, including volume-based indicators (NVI, PVI, OBV, etc.), price-based indicators (CCI, CMO, etc.), and moving averages (WMA, ALMA, etc.). It also includes the RSI of the MACD histogram (xxoo14).
* Composite RSI (xxoojht): The individual RSIs are then averaged to create a composite RSI, aiming to provide a more comprehensive view of market momentum and potential turning points.
* MACD Line RSI (xxoo14): The RSI of the MACD histogram incorporates the momentum aspect of the MACD indicator into the composite measure.
* Double EMA (co, coo): The code employs two Exponential Moving Averages (EMAs) of the composite RSI, with different lengths (9 and 18 periods).
* Difference (jo): The difference between the two EMAs (co and coo) is calculated, aiming to capture the rate of change in the composite RSI.
* Smoothed Difference (xxp): The difference (jo) is further smoothed using another EMA (9 periods) to reduce noise and enhance the signal.
* RSI of Smoothed Difference (cco): Finally, the RSI is applied to the smoothed difference (xxp) to create the core output of the indicator.
Market Applications and Trading Strategies:
* Overbought/Oversold: The indicator's central line (plotted at 50) acts as a reference for overbought/oversold conditions. Values above 50 suggest potential overbought zones, while values below 50 indicate oversold zones.
* Crossovers and Divergences: Crossovers of the cco line above or below its previous bar's value can signal potential trend changes. Divergences between the cco line and price action can also provide insights into potential trend reversals.
* Emoji Markers: The code adds emoji markers ("" for bullish and "" for bearish) based on the crossover direction of the cco line. These can provide a quick visual indication of potential trend shifts.
* Colored Fill: The area between the composite RSI line (xxoojht) and the central line (50) is filled with color to visually represent the prevailing market sentiment (green for above 50, red for below 50).
Trading Strategies (Examples):
* Long Entry: Consider a long entry (buying) signal when the cco line crosses above its previous bar's value and the composite RSI (xxoojht) is below 50, suggesting a potential reversal from oversold conditions.
* Short Entry: Conversely, consider a short entry (selling) signal when the cco line crosses below its previous bar's value and the composite RSI (xxoojht) is above 50, suggesting a potential reversal from overbought conditions.
* Confirmation: Always combine the indicator's signals with other technical analysis tools and price action confirmation for better trade validation.
Additional Notes:
* The indicator offers a complex combination of multiple indicators. Consider testing and optimizing the parameters (EMAs, RSI periods) to suit your trading style and market conditions.
* Backtesting with historical data can help assess the indicator's effectiveness and identify potential strengths and weaknesses in different market environments.
* Remember that no single indicator is perfect, and the cco indicator should be used in conjunction with other forms of analysis to make informed trading decisions.
By understanding the logic behind this composite oscillator and its potential applications, you can incorporate it into your trading strategy to potentially identify trends, gauge market sentiment, and generate trading signals.
HBK Price Action Strategy HBKPrice Action Strategy for XAUUSD with a Favorable Risk-Reward Ratio
Understanding the Strategy:
This strategy leverages price action principles to identify potential entry and exit points for XAUUSD on a 5-minute timeframe. The core idea is to identify price action patterns that suggest a high probability of a particular direction, and then to set stop-loss and take-profit levels to manage risk and reward.
Key Price Action Patterns to Watch:
Pin Bar: A pin bar is a candlestick with a long wick in one direction and a small body in the opposite direction. It often signals a reversal in the current trend.
Inside Bar: An inside bar forms when the current candle's high is lower than the previous candle's high, and the current candle's low is higher than the previous candle's low. It often indicates indecision or a potential breakout.
Engulfing Pattern: An engulfing pattern occurs when the current candle completely engulfs the previous candle. A bullish engulfing pattern signals a potential uptrend, while a bearish engulfing pattern signals a potential downtrend.
Risk-Reward Ratio:
A favorable risk-reward ratio is crucial for long-term trading success. Aim for a minimum risk-reward ratio of 1:2, meaning you risk $1 to potentially gain $2.
Entry and Exit Signals:
Long Entry:
Identify a bullish pin bar or engulfing pattern.
Wait for a confirmation candle to close above the pin bar's high or the engulfing pattern's high.
Place a stop-loss below the recent swing low.
Set a take-profit target at a key resistance level or a multiple of the stop-loss distance.
Short Entry:
Identify a bearish pin bar or engulfing pattern.
Wait for a confirmation candle to close below the pin bar's low or the engulfing pattern's low.
Place a stop-loss above the recent swing high.
Set a take-profit target at a key support level or a multiple of the stop-loss distance.
Additional Tips:
Use Support and Resistance Levels: Identify key support and resistance levels to set your stop-loss and take-profit targets.
Consider Market Sentiment: Pay attention to market sentiment and news events that may impact gold prices.
Manage Risk: Always use stop-loss orders to limit potential losses.
Be Patient: Don't force trades. Wait for high-probability setups.
Practice Discipline: Stick to your trading plan and avoid impulsive decisions.
Remember:
Price action trading requires practice and patience.
Backtest your strategy on historical data to refine your approach.
Always adapt to changing market conditions.
By following these guidelines and practicing disciplined risk management, you can increase your chances of success in trading XAUUSD on a 5-minute timeframe.
XAUUSD 10-Minute StrategyThis XAUUSD 10-Minute Strategy is designed for trading Gold vs. USD on a 10-minute timeframe. By combining multiple technical indicators (MACD, RSI, Bollinger Bands, and ATR), the strategy effectively captures both trend-following and reversal opportunities, with adaptive risk management for varying market volatility. This approach balances high-probability entries with robust volatility management, making it suitable for traders seeking to optimise entries during significant price movements and reversals.
Key Components and Logic:
MACD (12, 26, 9):
Generates buy signals on MACD Line crossovers above the Signal Line and sell signals on crossovers below the Signal Line, helping to capture momentum shifts.
RSI (14):
Utilizes oversold (below 35) and overbought (above 65) levels as a secondary filter to validate entries and avoid overextended price zones.
Bollinger Bands (20, 2):
Uses upper and lower Bollinger Bands to identify potential overbought and oversold conditions, aiming to enter long trades near the lower band and short trades near the upper band.
ATR-Based Stop Loss and Take Profit:
Stop Loss and Take Profit levels are dynamically set as multiples of ATR (3x for stop loss, 5x for take profit), ensuring flexibility with market volatility to optimise exit points.
Entry & Exit Conditions:
Buy Entry: T riggered when any of the following conditions are met:
MACD Line crosses above the Signal Line
RSI is oversold
Price drops below the lower Bollinger Band
Sell Entry: Triggered when any of the following conditions are met:
MACD Line crosses below the Signal Line
RSI is overbought
Price moves above the upper Bollinger Band
Exit Strategy: Trades are closed based on opposing entry signals, with adaptive spread adjustments for realistic exit points.
Backtesting Configuration & Results:
Backtesting Period: July 21, 2024, to October 30, 2024
Symbol Info: XAUUSD, 10-minute timeframe, OANDA data source
Backtesting Capital: Initial capital of $700, with each trade set to 10 contracts (equivalent to approximately 0.1 lots based on the broker’s contract size for gold).
Users should confirm their broker's contract size for gold, as this may differ. This script uses 10 contracts for backtesting purposes, aligned with 0.1 lots on brokers offering a 100-contract specification.
Key Backtesting Performance Metrics:
Net Profit: $4,733.90 USD (676.27% increase)
Total Closed Trades: 526
Win Rate: 53.99%
Profit Factor: 1.44 (1.96 for Long trades, 1.14 for Short trades)
Max Drawdown: $819.75 USD (56.33% of equity)
Sharpe Ratio: 1.726
Average Trade: $9.00 USD (0.04% of equity per trade)
This backtest reflects realistic conditions, with a spread adjustment of 38 points and no slippage or commission applied. The settings aim to simulate typical retail trading conditions. However, please adjust the initial capital, contract size, and other settings based on your account specifics for best results.
Usage:
This strategy is tuned specifically for XAUUSD on a 10-minute timeframe, ideal for both trend-following and reversal trades. The ATR-based stop loss and take profit levels adapt dynamically to market volatility, optimising entries and exits in varied conditions. To backtest this script accurately, ensure your broker’s contract specifications for gold align with the parameters used in this strategy.
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
G-Channel with EMA StrategyThe G-Channel is a custom channel with an upper (a), lower (b), and average (avg) line. These lines are dynamically calculated based on the current and previous closing prices, using the length input (default 100) to smooth the values:
Upper Line (a): This is the maximum value of the current price or the previous upper value, adjusted by the difference between the upper and lower lines divided by the length.
Lower Line (b): This is the minimum value of the current price or the previous lower value, similarly adjusted by the difference between the upper and lower lines.
The average line (avg) is simply the midpoint between the upper and lower lines. The G-Channel signals trend direction:
Bullish Condition: The system looks for the condition when the price crosses over the lower line (b), indicating a potential upward trend.
Bearish Condition: When the price crosses under the upper line (a), it signals a potential downward trend.
Exponential Moving Average (EMA)
The strategy also incorporates an EMA with a default length of 200. The EMA serves as a trend filter to determine whether the market is trending upward or downward:
Price below EMA: Indicates a bearish trend.
Price above EMA: Indicates a bullish trend.
Buy/Sell Conditions
The strategy generates buy or sell signals based on the interaction between the G-Channel signals and the price relative to the EMA:
Buy Signal: The strategy triggers a buy when:
A bullish condition (recent crossover of price over the lower G-Channel line) is detected.
The price is below the EMA, indicating that despite the recent bullish signal, the market might still be undervalued or in a temporary downturn.
Sell Signal: The strategy triggers a sell when:
A bearish condition (recent crossunder of price below the upper G-Channel line) is detected.
The price is above the EMA, suggesting that the market might be overextended and poised for a downturn.
Visualization
The strategy plots:
The upper, lower, and average lines of the G-Channel, with the average line colored based on bullish (green) or bearish (red) conditions.
The EMA (orange) line to provide context on the general trend direction.
Markers for Buy and Sell signals to visually indicate the strategy's entry points.
Strategy Execution
When a buy or sell signal is detected:
Buy Entry: If the bullish condition and price < EMA condition are met, a long (buy) position is opened.
Sell Entry: If the bearish condition and price > EMA condition are met, a short (sell) position is opened.
Purpose
This strategy aims to catch price reversals at critical points (when the price moves through the G-Channel) while filtering trades using the EMA to avoid entering during unfavorable market trends.
Bitcoin CME-Spot Z-Spread - Strategy [presentTrading]This time is a swing trading strategy! It measures the sentiment of the Bitcoin market through the spread of CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. By applying Bollinger Bands to the spread, the strategy seeks to capture mean-reversion opportunities when prices deviate significantly from their historical norms
█ Introduction and How it is Different
The Bitcoin CME-Spot Bollinger Bands Strategy is designed to capture mean-reversion opportunities by exploiting the spread between CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. The strategy uses Bollinger Bands to detect when the spread between these two correlated assets has deviated significantly from its historical norm, signaling potential overbought or oversold conditions.
What sets this strategy apart is its focus on spread trading between futures and spot markets rather than price-based indicators. By applying Bollinger Bands to the spread rather than individual prices, the strategy identifies price inefficiencies across markets, allowing traders to take advantage of the natural reversion to the mean that often occurs in these correlated assets.
BTCUSD 8hr Performance
█ Strategy, How It Works: Detailed Explanation
The strategy relies on Bollinger Bands to assess the volatility and relative deviation of the spread between CME Bitcoin Futures and Bitfinex BTCUSD Spot prices. Bollinger Bands consist of a moving average and two standard deviation bands, which help measure how much the spread deviates from its historical mean.
🔶 Spread Calculation:
The spread is calculated by subtracting the Bitfinex spot price from the CME Bitcoin futures price:
Spread = CME Price - Bitfinex Price
This spread represents the difference between the futures and spot markets, which may widen or narrow based on supply and demand dynamics in each market. By analyzing the spread, the strategy can detect when prices are too far apart (potentially overbought or oversold), indicating a trading opportunity.
🔶 Bollinger Bands Calculation:
The Bollinger Bands for the spread are calculated using a simple moving average (SMA) and the standard deviation of the spread over a defined period.
1. Moving Average (SMA):
The simple moving average of the spread (mu_S) over a specified period P is calculated as:
mu_S = (1/P) * sum(S_i from i=1 to P)
Where S_i represents the spread at time i, and P is the lookback period (default is 200 bars). The moving average provides a baseline for the normal spread behavior.
2. Standard Deviation:
The standard deviation (sigma_S) of the spread is calculated to measure the volatility of the spread:
sigma_S = sqrt((1/P) * sum((S_i - mu_S)^2 from i=1 to P))
3. Upper and Lower Bollinger Bands:
The upper and lower Bollinger Bands are derived by adding and subtracting a multiple of the standard deviation from the moving average. The number of standard deviations is determined by a user-defined parameter k (default is 2.618).
- Upper Band:
Upper Band = mu_S + (k * sigma_S)
- Lower Band:
Lower Band = mu_S - (k * sigma_S)
These bands provide a dynamic range within which the spread typically fluctuates. When the spread moves outside of these bands, it is considered overbought or oversold, potentially offering trading opportunities.
Local view
🔶 Entry Conditions:
- Long Entry: A long position is triggered when the spread crosses below the lower Bollinger Band, indicating that the spread has become oversold and is likely to revert upward.
Spread < Lower Band
- Short Entry: A short position is triggered when the spread crosses above the upper Bollinger Band, indicating that the spread has become overbought and is likely to revert downward.
Spread > Upper Band
🔶 Risk Management and Profit-Taking:
The strategy incorporates multi-step take profits to lock in gains as the trade moves in favor. The position is gradually reduced at predefined profit levels, reducing risk while allowing part of the trade to continue running if the price keeps moving favorably.
Additionally, the strategy uses a hold period exit mechanism. If the trade does not hit any of the take-profit levels within a certain number of bars, the position is closed automatically to avoid excessive exposure to market risks.
█ Trade Direction
The trade direction is based on deviations of the spread from its historical norm:
- Long Trade: The strategy enters a long position when the spread crosses below the lower Bollinger Band, signaling an oversold condition where the spread is expected to narrow.
- Short Trade: The strategy enters a short position when the spread crosses above the upper Bollinger Band, signaling an overbought condition where the spread is expected to widen.
These entries rely on the assumption of mean reversion, where extreme deviations from the average spread are likely to revert over time.
█ Usage
The Bitcoin CME-Spot Bollinger Bands Strategy is ideal for traders looking to capitalize on price inefficiencies between Bitcoin futures and spot markets. It’s especially useful in volatile markets where large deviations between futures and spot prices occur.
- Market Conditions: This strategy is most effective in correlated markets, like CME futures and spot Bitcoin. Traders can adjust the Bollinger Bands period and standard deviation multiplier to suit different volatility regimes.
- Backtesting: Before deployment, backtesting the strategy across different market conditions and timeframes is recommended to ensure robustness. Adjust the take-profit steps and hold periods to reflect the trader’s risk tolerance and market behavior.
█ Default Settings
The default settings provide a balanced approach to spread trading using Bollinger Bands but can be adjusted depending on market conditions or personal trading preferences.
🔶 Bollinger Bands Period (200 bars):
This defines the number of bars used to calculate the moving average and standard deviation for the Bollinger Bands. A longer period smooths out short-term fluctuations and focuses on larger, more significant trends. Adjusting the period affects the responsiveness of the strategy:
- Shorter periods (e.g., 100 bars): Makes the strategy more reactive to short-term market fluctuations, potentially generating more signals but increasing the risk of false positives.
- Longer periods (e.g., 300 bars): Focuses on longer-term trends, reducing the frequency of trades and focusing only on significant deviations.
🔶 Standard Deviation Multiplier (2.618):
The multiplier controls how wide the Bollinger Bands are around the moving average. By default, the bands are set at 2.618 standard deviations away from the average, ensuring that only significant deviations trigger trades.
- Higher multipliers (e.g., 3.0): Require a more extreme deviation to trigger trades, reducing trade frequency but potentially increasing the accuracy of signals.
- Lower multipliers (e.g., 2.0): Make the bands narrower, increasing the number of trade signals but potentially decreasing their reliability.
🔶 Take-Profit Levels:
The strategy has four take-profit levels to gradually lock in profits:
- Level 1 (3%): 25% of the position is closed at a 3% profit.
- Level 2 (8%): 20% of the position is closed at an 8% profit.
- Level 3 (14%): 15% of the position is closed at a 14% profit.
- Level 4 (21%): 10% of the position is closed at a 21% profit.
Adjusting these take-profit levels affects how quickly profits are realized:
- Lower take-profit levels: Capture gains more quickly, reducing risk but potentially cutting off larger profits.
- Higher take-profit levels: Let trades run longer, aiming for bigger gains but increasing the risk of price reversals before profits are locked in.
🔶 Hold Days (20 bars):
The strategy automatically closes the position after 20 bars if none of the take-profit levels are hit. This feature prevents trades from being held indefinitely, especially if market conditions are stagnant. Adjusting this:
- Shorter hold periods: Reduce the duration of exposure, minimizing risks from market changes but potentially closing trades too early.
- Longer hold periods: Allow trades to stay open longer, increasing the chance for mean reversion but also increasing exposure to unfavorable market conditions.
By understanding how these default settings affect the strategy’s performance, traders can optimize the Bitcoin CME-Spot Bollinger Bands Strategy to their preferences, adapting it to different market environments and risk tolerances.
