Dynamic Engulfing Trend Strategy
Author: ChaoZhang, Date: 2024-02-29 11:24:18Tags:
Overview
The Dynamic Engulfing Trend strategy is a trading strategy that takes long or short positions based on engulfing patterns in the direction of the trend. This strategy uses Average True Range (ATR) to gauge market volatility, Supertrend indicator to determine the market trend direction, and enters trades when engulfing patterns align with the trend direction. Stop loss and take profit levels are also calculated dynamically based on the engulfing patterns.
Strategy Logic
- Calculate ATR to measure market volatility.
- Calculate Supertrend indicator to identify the market trend.
- Define conditions for uptrend and downtrend.
- Identify bullish engulfing (in uptrend) and bearish engulfing (in downtrend).
- Calculate Stop Loss (SL) and Take Profit (TP) levels based on the engulfing patterns.
- Enter trades when engulfing patterns match the trend direction.
- Exit trades when price hits the SL or TP levels.
- Plot the engulfing patterns on the chart.
Advantage Analysis
The advantages of this strategy include:
- Improved signal quality by combining engulfing patterns with trend.
- Ability to identify trend reversals for precise entries.
- Clear long/short signals for better timing.
- Engulfing stop strategy follows the trend while managing risks.
- Modular code framework for easy optimizations.
Risk Analysis
There are also some risks to consider:
- Engulfing patterns may turn out to be false breakouts.
- Difficult to determine optimal parameters like pattern size, duration etc.
- Imperfect trend determination may lead to false signals.
- Stop loss and take profit levels rely on discretions and may be subjective.
- Performance depends on parameter tuning based on historical data.
The risks can be mitigated by:
- Adding filters to remove false breakout signals.
- Using adaptive ATR for robust parameter calculations.
- Improving trend determination using machine learning.
- Finding optimal parameters via genetic algorithms.
- Backtesting over longer durations to ensure robustness.
Optimization Directions
There is scope for further optimization:
- Machine learning can improve trend determinations.
- New pattern recognition methods can better identify engulfing patterns.
- Latest stop loss/take profit strategies can dynamically optimize levels.
- High frequency data can develop shorter-term system.
- Parameter tuning for different instruments.
Conclusion
In summary, the Dynamic Engulfing Trend strategy combines the high-quality engulfing pattern signals with accurate trend determination to generate a trading system with precise entries and reasonable stop losses and profit taking. Further enhancements in parameters, risk management and technology integration can improve its stability and profitability. The structured code framework also makes this strategy customizable across different markets.
/*backtest
start: 2024-01-01 00:00:00
end: 2024-01-31 23:59:59
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © Malikdrajat
//@version=4
strategy("Engulfing with Trend", overlay=true)
Periods = input(title="ATR Period", type=input.integer, defval=10)
src = input(hl2, title="Source")
Multiplier = input(title="ATR Multiplier", type=input.float, step=0.1, defval=3.0)
changeATR= input(title="Change ATR Calculation Method ?", type=input.bool, defval=true)
showsignals = input(title="Show Buy/Sell Signals ?", type=input.bool, defval=true)
highlighting = input(title="Highlighter On/Off ?", type=input.bool, defval=true)
atr2 = sma(tr, Periods)
atr= changeATR ? atr(Periods) : atr2
up=src-(Multiplier*atr)
up1 = nz(up[1],up)
up := close[1] > up1 ? max(up,up1) : up
dn=src+(Multiplier*atr)
dn1 = nz(dn[1], dn)
dn := close[1] < dn1 ? min(dn, dn1) : dn
trend = 1
trend := nz(trend[1], trend)
trend := trend == -1 and close > dn1 ? 1 : trend == 1 and close < up1 ? -1 : trend
upPlot = plot(trend == 1 ? up : na, title="Up Trend", style=plot.style_linebr, linewidth=2, color=color.green)
buySignal = trend == 1 and trend[1] == -1
plotshape(buySignal ? up : na, title="UpTrend Begins", location=location.absolute, style=shape.circle, size=size.tiny, color=color.green, transp=0)
plotshape(buySignal and showsignals ? up : na, title="Buy", text="Buy", location=location.absolute, style=shape.labelup, size=size.tiny, color=color.green, textcolor=color.white, transp=0)
dnPlot = plot(trend == 1 ? na : dn, title="Down Trend", style=plot.style_linebr, linewidth=2, color=color.red)
sellSignal = trend == -1 and trend[1] == 1
plotshape(sellSignal ? dn : na, title="DownTrend Begins", location=location.absolute, style=shape.circle, size=size.tiny, color=color.red, transp=0)
plotshape(sellSignal and showsignals ? dn : na, title="Sell", text="Sell", location=location.absolute, style=shape.labeldown, size=size.tiny, color=color.red, textcolor=color.white, transp=0)
mPlot = plot(ohlc4, title="", style=plot.style_circles, linewidth=0)
longFillColor = highlighting ? (trend == 1 ? color.green : color.white) : color.white
shortFillColor = highlighting ? (trend == -1 ? color.red : color.white) : color.white
fill(mPlot, upPlot, title="UpTrend Highligter", color=longFillColor)
fill(mPlot, dnPlot, title="DownTrend Highligter", color=shortFillColor)
alertcondition(buySignal, title="SuperTrend Buy", message="SuperTrend Buy!")
alertcondition(sellSignal, title="SuperTrend Sell", message="SuperTrend Sell!")
changeCond = trend != trend[1]
alertcondition(changeCond, title="SuperTrend Direction Change", message="SuperTrend has changed direction!")
// Define Downtrend and Uptrend conditions
downtrend = trend == -1
uptrend = trend == 1
// Engulfing
boringThreshold = input(25, title="Boring Candle Threshold (%)", minval=1, maxval=100, step=1)
engulfingThreshold = input(50, title="Engulfing Candle Threshold (%)", minval=1, maxval=100, step=1)
stopLevel = input(200, title="Stop Level (Pips)", minval=1)
// Boring Candle (Inside Bar) and Engulfing Candlestick Conditions
isBoringCandle = abs(open[1] - close[1]) * 100 / abs(high[1] - low[1]) <= boringThreshold
isEngulfingCandle = abs(open - close) * 100 / abs(high - low) <= engulfingThreshold
// Bullish and Bearish Engulfing Conditions
bullEngulfing = uptrend and close[1] < open[1] and close > open[1] and not isBoringCandle and not isEngulfingCandle
bearEngulfing = downtrend and close[1] > open[1] and close < open[1] and not isBoringCandle and not isEngulfingCandle
// Stop Loss, Take Profit, and Entry Price Calculation
bullStop = close + (stopLevel * syminfo.mintick)
bearStop = close - (stopLevel * syminfo.mintick)
bullSL = low
bearSL = high
bullTP = bullStop + (bullStop - low)
bearTP = bearStop - (high - bearStop)
// Entry Conditions
enterLong = bullEngulfing and uptrend
enterShort = bearEngulfing and downtrend
// Exit Conditions
exitLong = crossover(close, bullTP) or crossover(close, bullSL)
exitShort = crossover(close, bearTP) or crossover(close, bearSL)
// Check if exit conditions are met by the next candle
exitLongNextCandle = exitLong and (crossover(close[1], bullTP[1]) or crossover(close[1], bullSL[1]))
exitShortNextCandle = exitShort and (crossover(close[1], bearTP[1]) or crossover(close[1], bearSL[1]))
// Strategy Execution
strategy.entry("Buy", strategy.long, when=enterLong )
strategy.entry("Sell", strategy.short, when=enterShort )
// Exit Conditions for Long (Buy) Positions
if (bullEngulfing and not na(bullTP) and not na(bullSL))
strategy.exit("Exit Long", from_entry="Buy", stop=bullSL, limit=bullTP)
// Exit Conditions for Short (Sell) Positions
if (bearEngulfing and not na(bearTP) and not na(bearSL))
strategy.exit("Exit Short", from_entry="Sell", stop=bearSL, limit=bearTP)
// Plot Shapes and Labels
plotshape(bullEngulfing, style=shape.triangleup, location=location.abovebar, color=color.green)
plotshape(bearEngulfing, style=shape.triangledown, location=location.abovebar, color=color.red)
// Determine OP, SL, and TP
plot(bullEngulfing ? bullStop : na, title="Bullish Engulfing stop", color=color.red, linewidth=3, style=plot.style_linebr)
plot(bearEngulfing ? bearStop : na, title="Bearish Engulfing stop", color=color.red, linewidth=3, style=plot.style_linebr)
plot(bullEngulfing ? bullSL : na, title="Bullish Engulfing SL", color=color.red, linewidth=3, style=plot.style_linebr)
plot(bearEngulfing ? bearSL : na, title="Bearish Engulfing SL", color=color.red, linewidth=3, style=plot.style_linebr)
plot(bullEngulfing ? bullTP : na, title="Bullish Engulfing TP", color=color.green, linewidth=3, style=plot.style_linebr)
plot(bearEngulfing ? bearTP : na, title="Bearish Engulfing TP", color=color.green, linewidth=3, style=plot.style_linebr)
More
- Momentum Crossover Strategy with Dynamic Trailing Stop Loss
- EMA and RSI Quantitative Trading Strategy
- Momentum Trend Strategy Based on MACD and Bollinger Bands
- Multi-Timeframe Stochastic Strategy
- Moving Average Crossover Strategy with Intraday Candlestick Patterns
- Bitcoin Scalping Strategy Based on Moving Average Crossover and Candlestick Patterns
- Momentum and Moving Average Combination Long Strategy
- Momentum Average Directional Movement Index Moving Average Crossover Strategy
- Dual EMA Crossover Trend Tracking Strategy
- Double Moving Average and MACD Combination Trading Strategy
- Multi Timeframe Moving Average Pullback Trading Strategy
- Dual Moving Average Volatility Tracking Strategy
- Short-term Trading Strategy Based on Bollinger Bands
- Trend Riding Strategy Based on MOST and KAMA
- Dual Timeframe Trend Following Strategy
- Bitlinc MARSI Trading Strategy
- The Bollinger Bands Tracking Strategy
- SuperTrend Breakout Strategy
- The Double EMA Strategy Analysis
- The Breakthrough Callback Trading Strategy