Tags:

This is a breakout strategy based on price Channel, combined with moving average indicators and trailing stop/take profit for entry and exit. It uses moving average of high/low prices to construct the price Channel, and enter long/short when price breaks out of the Channel, with fixed stop loss or trailing stop to control risks.

The strategy calculates moving averages of high/low prices to form a price Channel. Specifically, it computes length 10 SMA of high/low prices to plot the upper and lower band of the Channel. When price breaks out above the lower band into the upper band, it enters long. When price breaks down from the upper band into the lower band, it enters short.

After entry, the strategy uses either fixed stop loss or trailing stop for exit. The trailing stop consists of two parameters: fixed take profit level, and activating offset. When price reaches the activating offset, the take profit level starts to trail the price. This allows locking in profits while keeping some open space.

The strategy also combines time range filter, only running backtest within specified historical timeframe, to test performance across different market stages.

The strategy exploits price Channel and trend following with trailing stop, which allows it to capture mid-to-long term trend directions. Compared to simple moving average strategies, it avoids ineffective trades due to price fluctuations. With trailing stops, it can dynamically trail prices to lock in profits.

Overall, the strategy has clear logic, minimal indicators and parameters, easy to backtest, suitable for mid-to-long term trend trading, and can profit from strong trends.

The strategy tends to get stopped out easily during ranging, choppy markets, unable to sustain profits. Also during extreme moves, price may break out the stop loss aggressively leading to large losses.

The parameter tuning is quite subjective, requiring adjustments across different market stages. The fixed take profit and activating offset fails to adapt to varying market volatility.

Other indicators such as volume, Bollinger Bands can be incorporated to filter entry signals, avoiding traps. Or dynamic stops can be used based on ATR or price volatility.

Exit rules may be upgraded to trailing stop or Chandelier Exit. Partial profit targets can be considered when price re-enters Channel. Optimizing entry filters and exit rules can greatly improve stability of the strategy.

In summary, this is a quantitative strategy based on price Channel, trend following, stop loss/profit taking management. It has clear logic flow, simple parameter structure, easy to understand and backtest. It is suitable to learn algorithmic trading concepts. The strategy can be enhanced in various aspects to improve stability and profitability. The core idea is to capture trend direction, and manage risks via stop loss and take profit. It can be applied to various products over different timeframes.

/*backtest start: 2023-12-01 00:00:00 end: 2023-12-21 23:59:59 period: 3h basePeriod: 15m exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}] */ //@version=3 strategy("Generalized SSL Backtest w/ TSSL", shorttitle="GSSL Backtest", overlay=true ) // Generalized SSL: // This is the very first time the SSL indicator, whose acronym I ignore, is on Tradingview. // It is based on moving averages of the highs and lows. // Similar channel indicators can be found, whereas // this one implements the persistency inside the channel, which is rather tricky. // The green line is the base line which decides entries and exits, possibly with trailing stops. // With respect to the original version, here one can play with different moving averages. // The default settings are (10,SMA) // // Vitelot/Yanez/Vts March 2019 lb = input(10, title="Lb", minval=1) maType = input( defval="SMA", title="MA Type", options=["SMA","EMA","HMA","McG","WMA","Tenkan"]) fixedSL = input(title="SL Activation", defval=300) trailSL = input(title="SL Trigger", defval=1) fixedTP = input(title="TP Activation", defval=150) trailTP = input(title="TP Trigger", defval=1) FromMonth = input(defval = 1, title = "From Month", minval = 1, maxval = 12) FromDay = input(defval = 1, title = "From Day", minval = 1, maxval = 31) FromYear = input(defval = 2019, title = "From Year", minval = 2017) ToMonth = input(defval = 6, title = "To Month", minval = 1, maxval = 12) ToDay = input(defval = 19, title = "To Day", minval = 1, maxval = 31) ToYear = input(defval = 2020, title = "To Year", minval = 2017) start = timestamp(FromYear, FromMonth, FromDay, 00, 00) // backtest start window finish = timestamp(ToYear, ToMonth, ToDay, 23, 59) // backtest finish window startTimeOk() => true // create function "within window of time" if statement true // QUANDL:BCHAIN/ETRVU is USD-denominated daily transaction value on BTC blockchain // QUANDL:BCHAIN/MKTCP is USD-denominated Bitcoin marketcap hma(sig, n) => // Hull moving average definition wma( 2*wma(sig,round(n/2))-wma(sig,n), round(sqrt(n))) mcg(sig,length) => // Mc Ginley MA definition mg = 0.0 mg := na(mg[1]) ? ema(sig, length) : mg[1] + (sig - mg[1]) / (length * pow(sig/mg[1], 4)) tenkan(sig,len) => 0.5*(highest(sig,len)+lowest(sig,len)) ma(t,sig,len) => sss=na if t =="SMA" sss := sma(sig,len) if t == "EMA" sss := ema(sig,len) if t == "HMA" sss := hma(sig,len) if t == "McG" // Mc Ginley sss := mcg(sig,len) if t == "Tenkan" sss := tenkan(sig,len) if t == "WMA" sss := wma(sig,len) sss base(mah, mal) => bbb = na inChannel = close<mah and close>mal belowChannel = close<mah and close<mal bbb := inChannel? bbb[1]: belowChannel? -1: 1 uuu = bbb==1? mal: mah ddd = bbb==1? mah: mal [uuu, ddd] maH = ma(maType, high, lb) maL = ma(maType, low, lb) [up, dn] = base(maH,maL) plot(up, title="High MA", color=lime, linewidth=3) plot(dn, title="Low MA", color=orange, linewidth=3) long = crossover(dn,up) short = crossover(up,dn) // === STRATEGY - LONG POSITION EXECUTION === strategy.entry("Long", strategy.long, when= long and startTimeOk()) strategy.exit("Exit", qty_percent = 100, loss=fixedSL, trail_offset=trailTP, trail_points=fixedTP) strategy.exit("Exit", when= short) // === STRATEGY - SHORT POSITION EXECUTION === strategy.entry("Short", strategy.short, when= short and startTimeOk()) strategy.exit("Exit", qty_percent = 100, loss=fixedSL, trail_offset=trailTP, trail_points=fixedTP) strategy.exit("Exit", when= long)

- Multi Timeframe RSI Strategy
- Bollinger Bands and K-line Combined Strategy
- Aroon Oscillator Based Stock Trading Strategy
- EintSimple Pullback Strategy
- Polarized Fractal Efficiency (PFE) Trading Strategy
- Eleven Moving Averages Crossover Strategy
- Dual Moving Average Reversal Trading Strategy
- RSI of MACD Reversal Strategy
- Lunar Phase Based Bitcoin Trading Strategy
- Volatility Filtered Market Timing Strategy
- Quantitative Trading Dual Indicator Strategy
- Bidirectional Moving Average Reversion Trading Strategy
- RSI Bullish and Bearish Divergence Trading Strategy
- Box Breakout Based Silver Bullet Strategy
- Dual EMA and AC Indicator Based Trend Following Strategy
- Zero Lag Volatility Breakout EMA Trend Strategy
- Robust Trend Tracking Strategy
- Spiral Breakout Moving Average Strategy
- Quantitative Trading Strategy Based on Supertrend Indicator and Equity Curve Trading
- Multi-timeframe Super Trend Tracking Strategy