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.
Wskaźniki i strategie
EMA SHIFT & PARALLEL [n_dot]BINANCE:ETHUSDT.P
This strategy was developed for CRYPTO FUTURES, (the settings for ETHUSDT.P) . I aimed for the strategy to function in a live environment, so I focused on making its operation realistic:
When determining the position, only 80% (adjustable) of the available cash is invested to reduce the risk of position liquidation.
I account for a 0.05% commission, typical on the futures market, for each entry and exit.
Concept:
I modified a simple, well-known method: the crossover of two exponential moving averages (FAST, SLOW) generates the entry and exit signals.
I enhanced the base idea as follows:
For the fast EMA, I incorporated a multiplier (offset) to filter out market noise and focus only on strong signals.
I use different EMAs for long and short entry points; both have their own FAST and SLOW EMAs and their own offset. For longs, the FAST EMA is adjusted downward (<1), while for shorts, it is adjusted upward (>1). Consequently, the signal is generated when the modified FAST EMA crosses the SLOW EMA.
Risk Management:
The position includes the following components:
Separate stop-losses for long and short positions.
Separate trailers for long and short positions.
The strategy operates so that the entry point is determined by the EMA crossover, while the exit is governed only by the Stop Loss or Trailer. Optionally, it can be set to close the position at the EMA recrossing ("Close at Signal").
Trailer Operation:
An entry percentage and offset are defined. The trailer activates when the price surpasses the entry price, calculated automatically by the system.
The trailer closes the position when the price drops by the offset percentage from the highest reached price.
Example for trailer:
Purchase Price = 100
Trailer Enter = 5% → Activation Price = 105 (triggers trailer if market price crosses it).
Trailer Offset = 2%
If the price rises to 110, the exit price becomes 107.8.
If the price goes to 120, the exit price becomes 117.6.
If the price falls below 117.6, the trailer closes the position.
Settings:
Source: Determines the market price reference.
End Close: Closes positions at the end of the simulation to avoid "shadow positions" and provide an objective result.
Lot proportional to free cash (%): Only a portion of free cash is invested to meet margin requirements.
Plot Short, Plot Long: Simplifies displayed information by toggling indicator lines on/off.
Long Position (toggleable):
EMA Fast ws: Window size for FAST EMA.
EMA Slow ws: Window size for SLOW EMA.
EMA Fast down shift: Adjustment factor for FAST EMA.
Stop Loss long (%): Percent drop to close the position.
Trailer enter (%): Percent above the purchase price to activate the trailer.
Trailer offset (%): Percent drop to close the position.
Short Position (toggleable):
EMA Fast ws: Window size for FAST EMA.
EMA Slow ws: Window size for SLOW EMA.
EMA Fast up shift: Adjustment factor for FAST EMA.
Stop Loss short (%): Percent rise to close the position.
Trailer enter (%): Percent below the purchase price to activate the trailer.
Trailer offset (%): Percent rise to close the position.
Operational Framework:
If in a long position and a short EMA crossover occurs, the strategy closes the long and opens a short (flip).
If in a short position and a long EMA crossover occurs, the strategy closes the short and opens a long (flip).
A position can close in three ways:
Stop Loss
Trailer
Signal Recrossing
If none are active, the position remains open until the end of the simulation.
Observations:
Shifts significantly deviating from 1 increase overfitting risk. Recommended ranges: 0.96–0.99 (long) and 1.01–1.05 (short).
The strategy's advantage lies in risk management, crucial in leveraged futures markets. It operates with relatively low DrawDown.
Recommendations:
Bullish Market: Higher entry threshold (e.g., 6%) and larger offset (e.g., 3%).
Volatile/Sideways Market: Tighter parameters (e.g., 3%, 1%).
The method is stable, and minor parameter adjustments do not significantly impact results, helping assess overfitting: if small changes lead to drastic differences, the strategy is over-optimized.
EMA Settings: Adjust FAST and SLOW EMAs based on the asset's volatility and cyclicality.
On the crypto market, especially in the Futures market, short time periods (1–15 minutes) often show significant noise, making patterns/repetitions hard to identify. I recommend setting the interval to at least 1 hour.
I hope this contributes to your success!
DCA Strategy with HedgingThis strategy implements a dynamic hedging system with Dollar-Cost Averaging (DCA) based on the 34 EMA. It can hold simultaneous long and short positions, making it suitable for ranging and trending markets.
Key Features:
Uses 34 EMA as baseline indicator
Implements hedging with simultaneous long/short positions
Dynamic DCA for position management
Automatic take-profit adjustments
Entry confirmation using 3-candle rule
How it Works
Long Entries:
Opens when price closes above 34 EMA for 3 candles
Adds positions every 0.1% price drop
Takes profit at 0.05% above average entry
Short Entries:
Opens when price closes below 34 EMA for 3 candles
Adds positions every 0.1% price rise
Takes profit at 0.05% below average entry
Settings
EMA Length: Controls the EMA period (default: 34)
DCA Interval: Price movement needed for additional entries (default: 0.1%)
Take Profit: Profit target from average entry (default: 0.05%)
Initial Position: Starting position size (default: 1.0)
Indicators
L: Long Entry
DL: Long DCA
S: Short Entry
DS: Short DCA
LTP: Long Take Profit
STP: Short Take Profit
Alerts
Compatible with all standard TradingView alerts:
Position Opens (Long/Short)
DCA Entries
Take Profit Hits
Note: This strategy works best on lower timeframes with high liquidity pairs. Adjust parameters based on asset volatility.
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.
Buy & Hold aka. HODL StrategyThis is a simply HODL or Buy & Hold strategy, which is super useful to see the risk and reward of such a strategy.
The benefit of using this strategy is that you also get to see the Max Drawdown (Risk).
This way you can compare it to the Net Profit (Reward) and decide if it's worth it for you.
This strategy buys on the Start Date and sells either on the End Date or on the last candle if the End Date is in the future.
Remember that the strategy must close the trade (sell) otherwise you don't see any results in the Strategy Tester (this is how it works).
Engulfing Candlestick StrategyEver wondered whether the Bullish or Bearish Engulfing pattern works or has statistical significance? This script is for you. It works across all markets and timeframes.
The Engulfing Candlestick Pattern is a widely used technical analysis pattern that traders use to predict potential price reversals. It consists of two candles: a small candle followed by a larger one that "engulfs" the previous candle. This pattern is considered bullish when it occurs in a downtrend (bullish engulfing) and bearish when it occurs in an uptrend (bearish engulfing).
Statistical Significance of the Engulfing Pattern:
While many traders rely on candlestick patterns for making decisions, research on the statistical significance of these patterns has produced mixed results. A study by Dimitrios K. Koutoupis and K. M. Koutoupis (2014), titled "Testing the Effectiveness of Candlestick Chart Patterns in Forex Markets," indicates that candlestick patterns, including the engulfing pattern, can provide some predictive power, but their success largely depends on the market conditions and timeframe used. The researchers concluded that while some candlestick patterns can be useful, traders must combine them with other indicators or market knowledge to improve their predictive accuracy.
Another study by Brock, Lakonishok, and LeBaron (1992), "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," explores the profitability of technical indicators, including candlestick patterns, and finds that simple trading rules, such as those based on moving averages or candlestick patterns, can occasionally outperform a random walk in certain market conditions.
However, Jorion (1997), in his work "The Risk of Speculation: The Case of Technical Analysis," warns that the reliability of candlestick patterns, including the engulfing patterns, can vary significantly across different markets and periods. Therefore, it's important to use these patterns as part of a broader trading strategy that includes other risk management techniques and technical indicators.
Application Across Markets:
This script applies to all markets (e.g., stocks, commodities, forex) and timeframes, making it a versatile tool for traders seeking to explore the statistical effectiveness of the bullish and bearish engulfing patterns in their own trading.
Conclusion:
This script allows you to backtest and visualize the effectiveness of the Bullish and Bearish Engulfing patterns across any market and timeframe. While the statistical significance of these patterns may vary, the script provides a clear framework for evaluating their performance in real-time trading conditions. Always remember to combine such patterns with other risk management strategies and indicators to enhance their predictive power.
Daytrading ES Wick Length StrategyThis Pine Script strategy calculates the combined length of upper and lower wicks of candlesticks and uses a customizable moving average (MA) to identify potential long entry points. The strategy compares the total wick length to the MA with an added offset. If the wick length exceeds the offset-adjusted MA, the strategy enters a long position. The position is automatically closed after a user-defined holding period.
Key Features:
1. Calculates the sum of upper and lower wicks for each candlestick.
2. Offers four types of moving averages (SMA, EMA, WMA, VWMA) for analysis.
3. Allows the user to set a customizable MA length and an offset to shift the MA.
4. Automatically exits positions after a specified number of bars.
5. Visualizes the wick length as a histogram and the offset-adjusted MA as a line.
References:
• Candlestick wick analysis: Nison, S. (1991). Japanese Candlestick Charting Techniques.
• Moving averages: Brock, W., Lakonishok, J., & LeBaron, B. (1992). “Simple Technical Trading Rules and the Stochastic Properties of Stock Returns”. Journal of Finance.
This strategy is suitable for identifying candlesticks with significant volatility and long wicks, which can indicate potential trend reversals or continuations.
Up Gap Strategy with DelayThis strategy, titled “Up Gap Strategy with Delay,” is based on identifying up gaps in the price action of an asset. A gap is defined as the percentage difference between the current bar’s open price and the previous bar’s close price. The strategy triggers a long position if the gap exceeds a user-defined threshold and includes a delay period before entering the position. After entering, the position is held for a set number of periods before being closed.
Key Features:
1. Gap Threshold: The strategy defines an up gap when the gap size exceeds a specified threshold (in percentage terms). The gap threshold is an input parameter that allows customization based on the user’s preference.
2. Delay Period: After the gap occurs, the strategy waits for a delay period before initiating a long position. This delay can help mitigate any short-term volatility that might occur immediately after the gap.
3. Holding Period: Once the position is entered, it is held for a user-defined number of periods (holdingPeriods). This is to capture the potential post-gap trend continuation, as gaps often indicate strong directional momentum.
4. Gap Plotting: The strategy visually plots up gaps on the chart by placing a green label beneath the bar where the gap condition is met. Additionally, the background color turns green to highlight up-gap occurrences.
5. Exit Condition: The position is exited after the defined holding period. The strategy ensures that the position is closed after this time, regardless of whether the price is in profit or loss.
Scientific Background:
The gap theory has been widely studied in financial literature and is based on the premise that gaps in price often represent areas of significant support or resistance. According to research by Kaufman (2002), gaps in price action can be indicators of future price direction, particularly when they occur after a period of consolidation or a trend reversal. Moreover, Gaps and their Implications in Technical Analysis (Murphy, 1999) highlights that gaps can reflect imbalances between supply and demand, leading to high momentum and potential price continuation or reversal.
In trading strategies, utilizing gaps with specific conditions, such as delay and holding periods, can enhance the ability to capture significant price moves. The strategy’s delay period helps avoid potential market noise immediately after the gap, while the holding period seeks to capitalize on the price continuation that often follows gap formation.
This methodology aligns with momentum-based strategies, which rely on the persistence of trends in financial markets. Several studies, including Jegadeesh & Titman (1993), have documented the existence of momentum effects in stock prices, where past price movements can be predictive of future returns.
Conclusion:
This strategy incorporates gap detection and momentum principles, supported by empirical research in technical analysis, to attempt to capitalize on price movements following significant gaps. By waiting for a delay period and holding the position for a specified time, it aims to mitigate the risk associated with early volatility while maximizing the potential for sustained price moves.
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.
Omega_galskyThe strategy uses three Exponential Moving Averages (EMAs) — EMA8, EMA21, and EMA89 — to decide when to open buy or sell trades. It also includes a mechanism to move the Stop Loss (SL) to the Break-Even (BE) point, which is the entry price, once the price reaches a Risk-to-Reward (R2R) ratio of 1:1.
Key Steps:
Calculating EMAs: The script computes the EMA values for the specified periods. These help identify market trends and potential entry points.
Buy Conditions:
EMA8 crosses above EMA21.
The candle that causes the crossover is green (closing price is higher than the opening price).
The closing price is above EMA89.
If all conditions are met, a buy order is executed.
Sell Conditions:
EMA8 crosses below EMA21.
The candle that causes the crossover is red (closing price is lower than the opening price).
The closing price is below EMA89.
If all conditions are met, a sell order is executed.
Stop Loss and Take Profit:
Initial Stop Loss and Take Profit levels are calculated based on the entry price and a percentage defined by the user.
These levels help protect against large losses and lock in profits.
Break-Even Logic:
When the price moves favorably to reach a 1:1 R2R ratio:
For a buy trade, the Stop Loss is moved to the entry price if the price increases sufficiently.
For a sell trade, the Stop Loss is moved to the entry price if the price decreases sufficiently.
This ensures the trade is risk-free after the price reaches the predefined level.
Visual Representation:
The EMAs are plotted on the chart for easy visualization of trends and crossovers.
Entry and exit points are also marked on the chart to track trades.
Purpose:
The strategy is designed to capitalize on EMA crossovers while minimizing risks using Break-Even logic and predefined Stop Loss/Take Profit levels. It automates decision-making for trend-following traders and ensures disciplined risk management.
IU Higher Timeframe MA Cross StrategyIU Higher Timeframe MA Cross Strategy
The IU Higher Timeframe MA Cross Strategy is a versatile trading tool designed to identify trend by utilizing two customizable moving averages (MAs) across different timeframes and types. This strategy includes detailed entry and exit rules with fully configurable inputs, offering flexibility to suit various trading styles.
Key Features:
- Two moving averages (MA1 and MA2) with customizable types, lengths, sources, and timeframes.
- Both long and short trade setups based on MA crossovers.
- Integrated risk management with adjustable stop-loss and take-profit levels based on a user-defined risk-to-reward (RTR) ratio.
- Clear visualization of MAs, entry points, stop-loss, and take-profit zones.
Inputs:
1. Risk-to-Reward Ratio (RTR):
- Defines the take-profit level in relation to the stop-loss distance. Default is 2.
2. MA1 Settings:
- Source: Select the data source for calculating MA1 (e.g., close, open, high, low). Default is close.
- Timeframe: Specify the timeframe for MA1 calculation. Default is 60 (60-minute chart).
- Length: Set the lookback period for MA1 calculation. Default is 20.
- Type: Choose the type of moving average (options: SMA, EMA, SMMA, WMA, VWMA). Default is EMA.
- Smooth: Option to enable or disable smoothing of MA1 to merge gaps. Default is true.
3. MA2 Settings:
- Source: Select the data source for calculating MA2 (e.g., close, open, high, low). Default is close.
- Timeframe: Specify the timeframe for MA2 calculation. Default is 60 (60-minute chart).
- Length: Set the lookback period for MA2 calculation. Default is 50.
- Type: Choose the type of moving average (options: SMA, EMA, SMMA, WMA, VWMA). Default is EMA.
- Smooth: Option to enable or disable smoothing of MA2 to merge gaps. Default is true.
Entry Rules:
- Long Entry:
- Triggered when MA1 crosses above MA2 (crossover).
- Entry is confirmed only when the bar is closed and no existing position is active.
- Short Entry:
- Triggered when MA1 crosses below MA2 (crossunder).
- Entry is confirmed only when the bar is closed and no existing position is active.
Exit Rules:
- Stop-Loss:
- For long positions: Set at the low of the bar preceding the entry.
- For short positions: Set at the high of the bar preceding the entry.
- Take-Profit:
- For long positions: Calculated as (Entry Price - Stop-Loss) * RTR + Entry Price.
- For short positions: Calculated as Entry Price - (Stop-Loss - Entry Price) * RTR.
Visualization:
- Plots MA1 and MA2 on the chart with distinct colors for easy identification.
- Highlights stop-loss and take-profit levels using shaded zones for clear visual representation.
- Displays the entry level for active positions.
This strategy provides a robust framework for traders to identify and act on trend reversals while maintaining strict risk management. The flexibility of its inputs allows for seamless customization to adapt to various market conditions and trading preferences.
HOD/LOD/PMH/PML/PDH/PDL Strategy by @tradingbauhaus This script is a trading strategy @tradingbauhaus designed to trade based on key price levels, such as the High of Day (HOD), Low of Day (LOD), Premarket High (PMH), Premarket Low (PML), Previous Day High (PDH), and Previous Day Low (PDL). Below, I’ll explain in detail what the script does:
Core Functionality of the Script:
Calculates Key Price Levels:
HOD (High of Day): The highest price of the current day.
LOD (Low of Day): The lowest price of the current day.
PMH (Premarket High): The highest price during the premarket session (before the market opens).
PML (Premarket Low): The lowest price during the premarket session.
PDH (Previous Day High): The highest price of the previous day.
PDL (Previous Day Low): The lowest price of the previous day.
Draws Horizontal Lines on the Chart:
Plots horizontal lines on the chart for each key level (HOD, LOD, PMH, PML, PDH, PDL) with specific colors for easy visual identification.
Defines Entry and Exit Rules:
Long Entry (Buy): If the price crosses above the PMH (Premarket High) or the PDH (Previous Day High).
Short Entry (Sell): If the price crosses below the PML (Premarket Low) or the PDL (Previous Day Low).
Long Exit: If the price reaches the HOD (High of Day) during a long position.
Short Exit: If the price reaches the LOD (Low of Day) during a short position.
How the Script Works Step by Step:
Calculates Key Levels:
Uses the request.security function to fetch the HOD and LOD of the current day, as well as the highs and lows of the previous day (PDH and PDL).
Calculates the PMH and PML during the premarket session (before 9:30 AM).
Plots Levels on the Chart:
Uses the plot function to draw horizontal lines on the chart representing the key levels (HOD, LOD, PMH, PML, PDH, PDL).
Each level has a specific color for easy identification:
HOD: White.
LOD: Purple.
PDH: Orange.
PDL: Blue.
PMH: Green.
PML: Red.
Defines Trading Rules:
Uses conditions with ta.crossover and ta.crossunder to detect when the price crosses key levels.
Long Entry: If the price crosses above the PMH or PDH, a long position (buy) is opened.
Short Entry: If the price crosses below the PML or PDL, a short position (sell) is opened.
Long Exit: If the price reaches the HOD during a long position, the position is closed.
Short Exit: If the price reaches the LOD during a short position, the position is closed.
Executes Orders Automatically:
Uses the strategy.entry and strategy.close functions to open and close positions automatically based on the defined rules.
Advantages of This Strategy:
Based on Key Levels: Uses important price levels that often act as support and resistance.
Easy to Visualize: Horizontal lines on the chart make it easy to identify levels.
Automated: Entries and exits are executed automatically based on the defined rules.
Limitations of This Strategy:
Dependent on Volatility: Works best in markets with significant price movements.
False Crosses: There may be false crosses that generate incorrect signals.
No Advanced Risk Management: Does not include dynamic stop-loss or take-profit mechanisms.
How to Improve the Strategy:
Add Stop-Loss and Take-Profit: To limit losses and lock in profits.
Filter Signals with Indicators: Use RSI, MACD, or other indicators to confirm signals.
Optimize Levels: Adjust key levels based on the asset’s behavior.
In summary, this script is a trading strategy that operates based on key price levels, such as HOD, LOD, PMH, PML, PDH, and PDL. It is useful for traders who want to trade based on significant support and resistance levels.
Gold Trade Setup Strategy
Title: Profitable Gold Setup Strategy with Adaptive Moving Average & Supertrend
Introduction:
This trading strategy for Gold (XAU/USD) combines the Adaptive Moving Average (AMA) and Supertrend, tailored for high-probability setups during specific trading hours. The AMA identifies the trend, while the Supertrend confirms entry and exit points. The strategy is optimized for swing and intraday traders looking to capitalize on Gold’s price movements with precise trade timing.
Strategy Components:
1. Adaptive Moving Average (AMA):
• Reacts dynamically to market conditions, filtering noise in choppy markets.
• Serves as the primary trend indicator.
2. Supertrend:
• Confirms entry signals with clear buy and sell levels.
• Acts as a trailing stop-loss to protect profits.
Trading Rules:
Trading Hours:
• Only take trades between 8:30 AM and 10:30 PM IST.
• Avoid trading outside these hours to reduce noise and low-volume setups.
Buy Setup:
1. Trend Confirmation: The Adaptive Moving Average (AMA) must be green.
2. Signal Confirmation: The Supertrend should turn green after the AMA is green.
3. Trigger: Take the trade when the high of the trigger candle (the candle that turned Supertrend green) is broken.
Sell Setup (Optional if included):
• Reverse the rules for a short trade: AMA and Supertrend should both indicate bearish conditions (red), and take the trade when the low of the trigger candle is broken.
Stop-Loss and Targets:
• Place the stop-loss at the low of the trigger candle for long trades.
• Set a 1:2 risk-reward ratio or use the Supertrend line as a trailing stop-loss.
Timeframes:
• Recommended timeframes: 1H, 4H, or Daily for swing trading.
• For intraday trading, use 15-minute or 30-minute charts.
Why This Strategy Works:
• Combines trend-following (AMA) with momentum-based entries (Supertrend).
• Focused trading hours filter out low-probability setups.
• Provides precise entry, stop-loss, and target levels for disciplined trading.
Conclusion:
This Gold Setup Strategy is designed for traders seeking a structured approach to trading Gold. Follow the rules strictly, backtest the strategy extensively, and share your results. Let’s master the Gold market together!
Tags: #Gold #XAUUSD #SwingTrading #Intraday #Supertrend #AMA #TechnicalAnalysis #GoldStrategy
Bollinger Band Touch with SMI and MACD AngleThis strategy is intended for short timeframes to enter and exit when price touches lower and upper bollinger bands with confluence on RSI and MACD
Mean Reversion V-FThis strategy workings on high volatile stock or crypto assets
It using 5 dynamic band's to get in the long position.
In same time depends on the band increases the units of the asset to get in the next position.
The unit's of the asset can be adjusted. Make sure to adjust the unit for different asset.
The bands are determined of main SMA.
There is no stop loss.
Take profit is trialing - HMA or % or average price + take profit - note if you use % trailing back test is not realistic but is working on real time.
Deviations can be adjust depends on the asset volatility.
EMA RSI Trend Reversal Ver.1Overview:
The EMA RSI Trend Reversal indicator combines the power of two well-known technical indicators—Exponential Moving Averages (EMAs) and the Relative Strength Index (RSI)—to identify potential trend reversal points in the market. The strategy looks for key crossovers between the fast and slow EMAs, and uses the RSI to confirm the strength of the trend. This combination helps to avoid false signals during sideways market conditions.
How It Works:
Buy Signal:
The Fast EMA (9) crosses above the Slow EMA (21), indicating a potential shift from a downtrend to an uptrend.
The RSI is above 50, confirming strong bullish momentum.
Visual Signal: A green arrow below the price bar and a Buy label are plotted on the chart.
Sell Signal:
The Fast EMA (9) crosses below the Slow EMA (21), indicating a potential shift from an uptrend to a downtrend.
The RSI is below 50, confirming weak or bearish momentum.
Visual Signal: A red arrow above the price bar and a Sell label are plotted on the chart.
Key Features:
EMA Crossovers: The Fast EMA crossing above the Slow EMA signals potential buying opportunities, while the Fast EMA crossing below the Slow EMA signals potential selling opportunities.
RSI Confirmation: The RSI helps confirm trend strength—values above 50 indicate bullish momentum, while values below 50 indicate bearish momentum.
Visual Cues: The strategy uses green arrows and red arrows along with Buy and Sell labels for clear visual signals of when to enter or exit trades.
Signal Interpretation:
Green Arrow / Buy Label: The Fast EMA (9) has crossed above the Slow EMA (21), and the RSI is above 50. This is a signal to buy or enter a long position.
Red Arrow / Sell Label: The Fast EMA (9) has crossed below the Slow EMA (21), and the RSI is below 50. This is a signal to sell or exit the long position.
Strategy Settings:
Fast EMA Length: Set to 9 (this determines how sensitive the fast EMA is to recent price movements).
Slow EMA Length: Set to 21 (this smooths out price movements to identify the broader trend).
RSI Length: Set to 14 (default setting to track momentum strength).
RSI Level: Set to 50 (used to confirm the strength of the trend—above 50 for buy signals, below 50 for sell signals).
Risk Management (Optional):
Use take profit and stop loss based on your preferred risk-to-reward ratio. For example, you can set a 2:1 risk-to-reward ratio (2x take profit for every 1x stop loss).
Backtesting and Optimization:
Backtest the strategy on TradingView by opening the Strategy Tester tab. This will allow you to see how the strategy would have performed on historical data.
Optimization: Adjust the EMA lengths, RSI period, and risk-to-reward settings based on your asset and time frame.
Limitations:
False Signals in Sideways Markets: Like any trend-following strategy, this indicator may generate false signals during periods of low volatility or sideways movement.
Not Suitable for All Market Conditions: This indicator performs best in trending markets. It may underperform in choppy or range-bound markets.
Strategy Example:
XRP/USD Example:
If you're trading XRP/USD and the Fast EMA (9) crosses above the Slow EMA (21), while the RSI is above 50, the indicator will signal a Buy.
Conversely, if the Fast EMA (9) crosses below the Slow EMA (21), and the RSI is below 50, the indicator will signal a Sell.
Bitcoin (BTC/USD):
On the BTC/USD chart, when the indicator shows a green arrow and a Buy label, it’s signaling a potential long entry. Similarly, a red arrow and Sell label indicate a short entry or exit from a previous long position.
Summary:
The EMA RSI Trend Reversal Indicator helps traders identify potential trend reversals with clear buy and sell signals based on the EMA crossovers and RSI confirmations. By using green arrows and red arrows, along with Buy and Sell labels, this strategy offers easy-to-understand visual signals for entering and exiting trades. Combine this with effective risk management and backtesting to optimize your trading performance.
Kernel Regression Envelope with SMI OscillatorThis script combines the predictive capabilities of the **Nadaraya-Watson estimator**, implemented by the esteemed jdehorty (credit to him for his excellent work on the `KernelFunctions` library and the original Nadaraya-Watson Envelope indicator), with the confirmation strength of the **Stochastic Momentum Index (SMI)** to create a dynamic trend reversal strategy. The core idea is to identify potential overbought and oversold conditions using the Nadaraya-Watson Envelope and then confirm these signals with the SMI before entering a trade.
**Understanding the Nadaraya-Watson Envelope:**
The Nadaraya-Watson estimator is a non-parametric regression technique that essentially calculates a weighted average of past price data to estimate the current underlying trend. Unlike simple moving averages that give equal weight to all past data within a defined period, the Nadaraya-Watson estimator uses a **kernel function** (in this case, the Rational Quadratic Kernel) to assign weights. The key parameters influencing this estimation are:
* **Lookback Window (h):** This determines how many historical bars are considered for the estimation. A larger window results in a smoother estimation, while a smaller window makes it more reactive to recent price changes.
* **Relative Weighting (alpha):** This parameter controls the influence of different time frames in the estimation. Lower values emphasize longer-term price action, while higher values make the estimator more sensitive to shorter-term movements.
* **Start Regression at Bar (x\_0):** This allows you to exclude the potentially volatile initial bars of a chart from the calculation, leading to a more stable estimation.
The script calculates the Nadaraya-Watson estimation for the closing price (`yhat_close`), as well as the highs (`yhat_high`) and lows (`yhat_low`). The `yhat_close` is then used as the central trend line.
**Dynamic Envelope Bands with ATR:**
To identify potential entry and exit points around the Nadaraya-Watson estimation, the script uses **Average True Range (ATR)** to create dynamic envelope bands. ATR measures the volatility of the price. By multiplying the ATR by different factors (`nearFactor` and `farFactor`), we create multiple bands:
* **Near Bands:** These are closer to the Nadaraya-Watson estimation and are intended to identify potential immediate overbought or oversold zones.
* **Far Bands:** These are further away and can act as potential take-profit or stop-loss levels, representing more extreme price extensions.
The script calculates both near and far upper and lower bands, as well as an average between the near and far bands. This provides a nuanced view of potential support and resistance levels around the estimated trend.
**Confirming Reversals with the Stochastic Momentum Index (SMI):**
While the Nadaraya-Watson Envelope identifies potential overextended conditions, the **Stochastic Momentum Index (SMI)** is used to confirm a potential trend reversal. The SMI, unlike a traditional stochastic oscillator, oscillates around a zero line. It measures the location of the current closing price relative to the median of the high/low range over a specified period.
The script calculates the SMI on a **higher timeframe** (defined by the "Timeframe" input) to gain a broader perspective on the market momentum. This helps to filter out potential whipsaws and false signals that might occur on the current chart's timeframe. The SMI calculation involves:
* **%K Length:** The lookback period for calculating the highest high and lowest low.
* **%D Length:** The period for smoothing the relative range.
* **EMA Length:** The period for smoothing the SMI itself.
The script uses a double EMA for smoothing within the SMI calculation for added smoothness.
**How the Indicators Work Together in the Strategy:**
The strategy enters a long position when:
1. The closing price crosses below the **near lower band** of the Nadaraya-Watson Envelope, suggesting a potential oversold condition.
2. The SMI crosses above its EMA, indicating positive momentum.
3. The SMI value is below -50, further supporting the oversold idea on the higher timeframe.
Conversely, the strategy enters a short position when:
1. The closing price crosses above the **near upper band** of the Nadaraya-Watson Envelope, suggesting a potential overbought condition.
2. The SMI crosses below its EMA, indicating negative momentum.
3. The SMI value is above 50, further supporting the overbought idea on the higher timeframe.
Trades are closed when the price crosses the **far band** in the opposite direction of the trade. A stop-loss is also implemented based on a fixed value.
**In essence:** The Nadaraya-Watson Envelope identifies areas where the price might be deviating significantly from its estimated trend. The SMI, calculated on a higher timeframe, then acts as a confirmation signal, suggesting that the momentum is shifting in the direction of a potential reversal. The ATR-based bands provide dynamic entry and exit points based on the current volatility.
**How to Use the Script:**
1. **Apply the script to your chart.**
2. **Adjust the "Kernel Settings":**
* **Lookback Window (h):** Experiment with different values to find the smoothness that best suits the asset and timeframe you are trading. Lower values make the envelope more reactive, while higher values make it smoother.
* **Relative Weighting (alpha):** Adjust to control the influence of different timeframes on the Nadaraya-Watson estimation.
* **Start Regression at Bar (x\_0):** Increase this value if you want to exclude the initial, potentially volatile, bars from the calculation.
* **Stoploss:** Set your desired stop-loss value.
3. **Adjust the "SMI" settings:**
* **%K Length, %D Length, EMA Length:** These parameters control the sensitivity and smoothness of the SMI. Experiment to find settings that work well for your trading style.
* **Timeframe:** Select the higher timeframe you want to use for SMI confirmation.
4. **Adjust the "ATR Length" and "Near/Far ATR Factor":** These settings control the width and sensitivity of the envelope bands. Smaller ATR lengths make the bands more reactive to recent volatility.
5. **Customize the "Color Settings"** to your preference.
6. **Observe the plots:**
* The **Nadaraya-Watson Estimation (yhat)** line represents the estimated underlying trend.
* The **near and far upper and lower bands** visualize potential overbought and oversold zones based on the ATR.
* The **fill areas** highlight the regions between the near and far bands.
7. **Look for entry signals:** A long entry is considered when the price touches or crosses below the lower near band and the SMI confirms upward momentum. A short entry is considered when the price touches or crosses above the upper near band and the SMI confirms downward momentum.
8. **Manage your trades:** The script provides exit signals when the price crosses the far band. The fixed stop-loss will also close trades if the price moves against your position.
**Justification for Combining Nadaraya-Watson Envelope and SMI:**
The combination of the Nadaraya-Watson Envelope and the SMI provides a more robust approach to identifying potential trend reversals compared to using either indicator in isolation. The Nadaraya-Watson Envelope excels at identifying potential areas where the price is overextended relative to its recent history. However, relying solely on the envelope can lead to false signals, especially in choppy or volatile markets. By incorporating the SMI as a confirmation tool, we add a momentum filter that helps to validate the potential reversals signaled by the envelope. The higher timeframe SMI further helps to filter out noise and focus on more significant shifts in momentum. The ATR-based bands add a dynamic element to the entry and exit points, adapting to the current market volatility. This mashup aims to leverage the strengths of each indicator to create a more reliable trading strategy.
IU 4 Bar UP StrategyIU 4 Bar UP Strategy
The IU 4 Bar UP Strategy is a trend-following strategy designed to identify and execute long trades during strong bullish momentum, combined with confirmation from the SuperTrend indicator. This strategy is suitable for traders aiming to capitalize on sustained upward market movements.
Features :
1. SuperTrend Confirmation: Incorporates the SuperTrend indicator as a dynamic support/resistance line to filter trades in the direction of the trend.
2. 4 Consecutive Bullish Bars: Detects a series of 4 bullish candles as a signal for strong upward momentum, ensuring robust trade setups.
3. Dynamic Alerts: Sends alerts for trade entries and exits to keep traders informed.
4. Visual Enhancements:
- Plots the SuperTrend indicator on the chart.
- Changes the background color while a trade is active for easy visualization.
Inputs :
- SuperTrend ATR Period: The period used to calculate the Average True Range (ATR) for the SuperTrend indicator.
- SuperTrend ATR Factor: The multiplier for the ATR in the SuperTrend calculation.
Entry Conditions :
A long entry is triggered when:
1. The last 4 consecutive candles are bullish (closing prices are higher than opening prices).
2. The current price is above the SuperTrend line.
3. The strategy is not already in a position.
4. The bar is confirmed (not a partially formed bar).
When all these conditions are met, the strategy enters a long position and provides an alert:
"Long Entry triggered"
Exit Conditions :
The strategy exits the long position when:
1. The closing price drops below the SuperTrend line.
2. An alert is generated: "Close the long Trade"
Visualization :
- The SuperTrend line is plotted, dynamically colored:
- Green when the trend is bullish.
- Red when the trend is bearish.
- The background color turns semi-transparent green while a trade is active, indicating a long position.
Do use proper risk management while using this strategy.
Temporary Help Services Jobs - Trend Allocation StrategyThis strategy is designed to capitalize on the economic trends represented by the Temporary Help Services (TEMPHELPS) index, which is published by the Federal Reserve Economic Data (FRED). Temporary Help Services Jobs are often regarded as a leading indicator of labor market conditions, as changes in temporary employment levels frequently precede broader employment trends.
Methodology:
Data Source: The strategy uses the FRED dataset TEMPHELPS for monthly data on temporary help services.
Trend Definition:
Uptrend: When the current month's value is greater than the previous month's value.
Downtrend: When the current month's value is less than the previous month's value.
Entry Condition: A long position is opened when an uptrend is detected, provided no position is currently held.
Exit Condition: The long position is closed when a downtrend is detected.
Scientific Basis:
The TEMPHELPS index serves as a leading economic indicator, as noted in studies analyzing labor market cyclicality (e.g., Katz & Krueger, 1999). Temporary employment is often considered a proxy for broader economic conditions, particularly in predicting recessions or recoveries. Incorporating this index into trading strategies allows for aligning trades with potential macroeconomic shifts, as suggested by research on employment trends and market performance (Autor, 2001; Valetta & Bengali, 2013).
Usage:
This strategy is best suited for long-term investors or macroeconomic trend followers who wish to leverage labor market signals for equity or futures trading. It operates exclusively on end-of-month data, ensuring minimal transaction costs and noise.
Moving Average Crossover Strategy with Take Profit and Stop LossThe Moving Average Crossover Strategy is a popular trading technique that utilizes two moving averages (MAs) of different periods to identify potential buy and sell signals. By incorporating take profit and stop loss levels, traders can effectively manage their risk while maximizing potential returns. Here’s a detailed explanation of how this strategy works:
Overview of the Moving Average Crossover Strategy
Moving Averages:
A short-term moving average (e.g., 50-day MA) reacts more quickly to price changes, while a long-term moving average (e.g., 200-day MA) smooths out price fluctuations over a longer period.
The strategy generates trading signals based on the crossover of these two averages:
Buy Signal: When the short-term MA crosses above the long-term MA (often referred to as a "Golden Cross").
Sell Signal: When the short-term MA crosses below the long-term MA (known as a "Death Cross").
Implementing Take Profit and Stop Loss
1. Setting Take Profit Levels
Definition: A take profit order automatically closes a trade when it reaches a specified profit level.
Strategy:
Determine a realistic profit target based on historical price action, support and resistance levels, or a fixed risk-reward ratio (e.g., 2:1).
For instance, if you enter a buy position at $100, you might set a take profit at $110 if you anticipate that level will act as resistance.
2. Setting Stop Loss Levels
Definition: A stop loss order limits potential losses by closing a trade when the price reaches a specified level.
Strategy:
Place the stop loss just below the most recent swing low for buy orders or above the recent swing high for sell orders.
Alternatively, you can use a percentage-based method (e.g., 2-3% below the entry point) to define your stop loss.
For example, if you enter a buy position at $100 with a stop loss set at $95, your maximum loss would be limited to $5 per share.
Example of Using Moving Average Crossover with Take Profit and Stop Loss
Entry Signal:
You observe that the 50-day MA crosses above the 200-day MA at $100. You enter a buy position.
Setting Take Profit and Stop Loss:
You analyze historical price levels and set your take profit at $110.
You place your stop loss at $95 based on recent swing lows.
Trade Management:
If the price rises to $110, your take profit order is executed, securing your profit.
If the price falls to $95, your stop loss is triggered, limiting your losses.
Relative StrengthThis strategy employs a custom "strength" function to assess the relative strength of a user-defined source (e.g., closing price, moving average) compared to its historical performance over various timeframes (8, 34, 20, 50, and 200 periods). The strength is calculated as a percentage change from an Exponential Moving Average (EMA) for shorter timeframes and a Simple Moving Average (SMA) for longer timeframes. Weights are then assigned to each timeframe based on a logarithmic scale, and a weighted average strength is computed.
Key Features:
Strength Calculation:
Calculates the relative strength of the source using EMAs and SMAs over various timeframes.
Assigns weights to each timeframe based on a logarithmic scale, emphasizing shorter timeframes.
Calculates a weighted average strength for a comprehensive view.
Visualizations:
Plots the calculated strength as a line, colored green for positive strength and red for negative strength.
Fills the background area below the line with green for positive strength and red for negative strength, enhancing visualization.
Comparative Analysis:
Optionally displays the strength of Bitcoin (BTC), Ethereum (ETH), S&P 500, Nasdaq, and Dow Jones Industrial Average (DJI) for comparison with the main source strength.
Backtesting:
Allows users to specify a start and end time for backtesting the strategy's performance.
Trading Signals:
Generates buy signals when the strength turns positive from negative and vice versa for sell signals.
Entry and exit are conditional on the backtesting time range.
Basic buy and sell signal plots are commented out (can be uncommented for visual representation).
Risk Management:
Closes all open positions and cancels pending orders outside the backtesting time range.
Disclaimer:
Backtesting results do not guarantee future performance. This strategy is for educational purposes only and should be thoroughly tested and refined before risking capital.
Additional Notes:
- The strategy uses a custom "strength" function that can be further customized to explore different timeframes and weighting schemes.
- Consider incorporating additional technical indicators or filters to refine the entry and exit signals.
- Backtesting with different parameters and market conditions is crucial for evaluating the strategy's robustness.
McClellan A-D Volume Integration ModelThe strategy integrates the McClellan A-D Oscillator with an adjustment based on the Advance/Decline (A-D) volume data. The McClellan Oscillator is calculated by taking the difference between the short-term and long-term exponential moving averages (EMAs) of the A-D line. This strategy introduces an enhancement where the A-D volume (the difference between the advancing and declining volume) is factored in to adjust the oscillator value.
Inputs:
• ema_short_length: The length for the short-term EMA of the A-D line.
• ema_long_length: The length for the long-term EMA of the A-D line.
• osc_threshold_long: The threshold below which the oscillator must drop for an entry signal to trigger.
• exit_periods: The number of periods after which the position is closed.
• Data Sources:
• ad_advance and ad_decline are the data sources for advancing and declining issues, respectively.
• vol_advance and vol_decline are the volume data for the advancing and declining issues. If volume data is unavailable, it defaults to na (Not Available), and the fallback logic ensures that the strategy continues to function.
McClellan Oscillator with Volume Adjustment:
• The A-D line is calculated by subtracting the declining issues from the advancing issues. Then, the volume difference is applied to this line, creating a “weighted” A-D line.
• The short and long EMAs are calculated for the weighted A-D line to generate the McClellan Oscillator.
Entry Condition:
• The strategy looks for a reversal signal, where the oscillator falls below the threshold and then rises above it again. The condition is designed to trigger a long position when this reversal happens.
Exit Condition:
• The position is closed after a set number of periods (exit_periods) have passed since the entry.
Plotting:
• The McClellan Oscillator and the threshold are plotted on the chart for visual reference.
• Entry and exit signals are highlighted with background colors to make the signals more visible.
Scientific Background:
The McClellan A-D Oscillator is a popular market breadth indicator developed by Sherman and Marian McClellan. It is used to gauge the underlying strength of a market by analyzing the difference between the number of advancing and declining stocks. The oscillator is typically calculated using exponential moving averages (EMAs) of the A-D line, with the idea being that crossovers of these EMAs indicate potential changes in the market’s direction.
The integration of A-D volume into this model adds another layer of analysis, as volume is often considered a leading indicator of price movement. By factoring in volume, the strategy becomes more sensitive to not just the number of advancing or declining stocks but also how significant those movements are based on trading volume, as discussed in Schwager, J. D. (1999). Technical Analysis of the Financial Markets. This enhanced version aims to capture stronger and more sustainable trends in the market, helping to filter out false signals.
Additionally, volume analysis is often used to confirm price movements, as described in Wyckoff, R. (1931). The Day Trading System. Therefore, incorporating the volume of advancing and declining stocks in the McClellan Oscillator offers a more robust signal for trading decisions.
