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Triple Overlapping Stochastic Momentum Strategy

Author: ChaoZhang, Date: 2024-01-26 12:15:20
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Overview

The Triple Overlapping Stochastic Momentum strategy is a typical short-term trading strategy. It calculates three Stochastic Momentum Index (SMI) indicators with different parameter settings and generates trading signals when all three show overbought or oversold conditions simultaneously. By combining multi-timeframe analysis, this strategy can effectively filter market noise and improve signal quality.

Strategy Logic

The core indicator of this strategy is the Stochastic Momentum Index (SMI). The SMI is calculated as follows:

SMI = 100 * EMA(EMA(Close - Midpoint of High-Low Range, N1), N2) / 0.5 * EMA(EMA(High - Low, N1), N2)

Where N1 and N2 are the parameter lengths. The SMI oscillates between -100 and 100. Values above 0 indicate the close is in the upper half of the daily range, while values below 0 indicate the close is in the lower half.

Similar to the traditional Stochastic Oscillator, overbought (e.g. 40)/oversold (e.g. -40) levels indicate potential reversal signals. Bullish and bearish signals are generated when the SMI crosses above/below its moving average line.

The strategy employs three SMI indicators with different parameter sets, specifically:

  • SMI1: %K Period 10, %K Slowing Period 3
  • SMI2: %K Period 20, %K Slowing Period 3
  • SMI3: %K Period 5, %K Slowing Period 3

Trading signals are generated when all three SMIs concurrently show overbought or oversold conditions. This filters out false signals and improves reliability.

Advantages

  • Multi-timeframe analysis for robust signals
  • SMI enhances usability over traditional Stochastic
  • Triple overlay improves reliability over single indicator
  • Flexible parameters for optimization
  • Well suited for short-term/high frequency trading

Risks

  • Multiple indicators may lag signals
  • High trading frequency increases costs
  • Backtest overfitting
  • Parameters may fail with market regime changes

Risk Mitigations:

  • Optimize parameters to reduce lag
  • Adjust holding period to lower trading costs
  • Perform statistical testing to validate robustness
  • Dynamically adapt parameters

Enhancements

  • Test different SMI parameter combinations
  • Add statistical metrics to evaluate parameter stability
  • Incorporate supporting indicators like volume, Bollinger Bands etc.
  • Dynamic parameter switching based on environment
  • Optimize stop loss strategies

Conclusion

The Triple Overlapping Stochastic Momentum strategy combines robust signal generation across multiple timeframes by overlaying three SMI indicators with unique parameters. Compared to single oscillators, this multi-indicator approach filters more noise and improves consistency. Further refinements can be made going forward through parameter optimization, statistical validation, auxiliary indicators etc. to enhance strategy robustness.

/*backtest
start: 2023-12-26 00:00:00
end: 2024-01-25 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=2
strategy("Stochastic Momentum multi strategy", "Stochastic Momentum Index multi strategy", overlay=false)

q = input(10, title="%K Length")
r = input(3, title="%K Smoothing Length")
s = input(3, title="%K Double Smoothing Length")
nsig = input(10, title="Signal Length")
matype = input("ema", title="Signal MA Type")  // possible: ema, sma, wma, trima, hma, dema, tema, zlema
overbought = input(40, title="Overbought Level", type=float)
oversold = input(-40, title="Oversold Level", type=float)

trima(src, length) => sma(sma(src,length),length)
hma(src, length) => wma(2*wma(src, length/2)-wma(src, length), round(sqrt(length)))
dema(src, length) => 2*ema(src,length) - ema(ema(src,length),length)
tema(src, length) => (3*ema(src,length) - 3*ema(ema(src,length),length)) + ema(ema(ema(src,length),length),length)
zlema(src, length) => ema(src,length) + (ema(src,length) - ema(ema(src,length),length))

smi = 100 * ema(ema(close-0.5*(highest(q)+lowest(q)),r),s) / (0.5 * ema(ema(highest(q)-lowest(q),r),s))
sig = matype=="ema" ? ema(smi,nsig) : matype=="sma" ? sma(smi,nsig) : matype=="wma" ? wma(smi,nsig) : matype=="trima" ? trima(smi,nsig) : matype=="hma" ? hma(smi,nsig) : matype=="dema" ? dema(smi,nsig) : matype=="tema" ? tema(smi,nsig) : matype=="zlema" ? zlema(smi,nsig) : ema(smi,nsig)

p_smi = plot(smi, title="SMI", color=aqua)
p_sig = plot(sig, title="Signal", color=red)

// plotchar(crossover(smi, sig), title= "low", location=location.bottom, color=green, char="▲", size= size.tiny)
// plotchar(crossunder(smi, sig), title= "high", location=location.top, color=red, char="▼", size= size.tiny)

/////////////////////////////2
q2 = input(20, title="%K Length 2")
r2 = input(3, title="%K Smoothing Length 2")
s2 = input(3, title="%K Double Smoothing Length 2")
nsig2 = input(10, title="Signal Length 2")
matype2 = input("ema", title="Signal MA Type 2")  // possible: ema, sma, wma, trima, hma, dema, tema, zlema
overbought2 = input(40, title="Overbought Level 2", type=float)
oversold2 = input(-40, title="Oversold Level 2", type=float)

trima2(src2, length2) => sma(sma(src2,length2),length2)
hma2(src2, length2) => wma(2*wma(src2, length2/2)-wma(src2, length2), round(sqrt(length2)))
dema2(src2, length2) => 2*ema(src2,length2) - ema(ema(src2,length2),length2)
tema2(src2, length2) => (3*ema(src2,length2) - 3*ema(ema(src2,length2),length2)) + ema(ema(ema(src2,length2),length2),length2)
zlema2(src2, length2) => ema(src2,length2) + (ema(src2,length2) - ema(ema(src2,length2),length2))

smi2 = 100 * ema(ema(close-0.5*(highest(q2)+lowest(q2)),r2),s2) / (0.5 * ema(ema(highest(q2)-lowest(q2),r2),s2))
sig2 = matype2=="ema" ? ema(smi2,nsig2) : matype2=="sma 2" ? sma(smi2,nsig2) : matype2=="wma 2" ? wma(smi2,nsig2) : matype2=="trima 2" ? trima2(smi2,nsig2) : matype2=="hma 2" ? hma2(smi2,nsig2) : matype=="dema 2" ? dema2(smi2,nsig2) : matype2=="tema 2" ? tema2(smi2,nsig2) : matype2=="zlema 2" ? zlema2(smi2,nsig2) : ema(smi2,nsig2)

p_smi2 = plot(smi2, title="SMI 2", color=aqua)
p_sig2 = plot(sig2, title="Signal2", color=red)

// plotchar(crossover(smi2, sig2), title= "low2", location=location.bottom, color=green, char="▲", size= size.tiny)
// plotchar(crossunder(smi2, sig2), title= "high2", location=location.top, color=red, char="▼", size= size.tiny)

/////////////////////////////3
q3 = input(5, title="%K Length 3")
r3 = input(3, title="%K Smoothing Length 3")
s3 = input(3, title="%K Double Smoothing Length 3")
nsig3 = input(10, title="Signal Length 3")
matype3 = input("ema", title="Signal MA Type 3")  // possible: ema, sma, wma, trima, hma, dema, tema, zlema
overbought3 = input(40, title="Overbought Level 3", type=float)
oversold3 = input(-40, title="Oversold Level 3", type=float)

trima3(src3, length3) => sma(sma(src3,length3),length3)
hma3(src3, length3) => wma(2*wma(src3, length3/2)-wma(src3, length3), round(sqrt(length3)))
dema3(src3, length3) => 2*ema(src3,length3) - ema(ema(src3,length3),length3)
tema3(src3, length3) => (3*ema(src3,length3) - 3*ema(ema(src3,length3),length3)) + ema(ema(ema(src3,length3),length3),length3)
zlema3(src3, length3) => ema(src3,length3) + (ema(src3,length3) - ema(ema(src3,length3),length3))

smi3 = 100 * ema(ema(close-0.5*(highest(q3)+lowest(q3)),r3),s3) / (0.5 * ema(ema(highest(q3)-lowest(q3),r3),s3))
sig3 = matype3=="ema" ? ema(smi3,nsig3) : matype3=="sma 3" ? sma(smi3,nsig3) : matype3=="wma 3" ? wma(smi3,nsig3) : matype3=="trima 3" ? trima3(smi3,nsig3) : matype3=="hma 3" ? hma3(smi3,nsig3) : matype=="dema 3" ? dema3(smi3,nsig3) : matype3=="tema 3" ? tema3(smi3,nsig3) : matype3=="zlema 3" ? zlema3(smi3,nsig3) : ema(smi3,nsig3)

p_smi3 = plot(smi3, title="SMI 3", color=aqua)
p_sig3 = plot(sig3, title="Signal3", color=red)

// plotchar(crossover(smi3, sig3) and crossover(smi2, sig2) and crossover(smi, sig), title= "low3", location=location.bottom, color=green, char="▲", size= size.tiny)
// plotchar(crossunder(smi3, sig3) and crossunder(smi2, sig2) and crossunder(smi, sig), title= "high3", location=location.top, color=red, char="▼", size= size.tiny)
plotchar (((smi3 < sig3) and (smi2 < sig2) and (smi < sig)), title= "low3", location=location.bottom, color=green, char="▲", size= size.tiny)
plotchar (((smi3 > sig3) and (smi2 > sig2) and (smi > sig)), title= "high3", location=location.top, color=red, char="▼", size= size.tiny)

// === BACKTEST RANGE ===
FromMonth = input(defval = 8, title = "From Month", minval = 1, maxval = 12)
FromDay   = input(defval = 1, title = "From Day", minval = 1, maxval = 31)
FromYear  = input(defval = 2018, title = "From Year", minval = 2014)
ToMonth   = input(defval = 12, title = "To Month", minval = 1, maxval = 12)
ToDay     = input(defval = 31, title = "To Day", minval = 1, maxval = 31)
ToYear    = input(defval = 2018, title = "To Year", minval = 2014)

longCondition = ((smi3 < sig3) and (smi2 < sig2) and (smi < sig))
shortCondition = ((smi3 > sig3) and (smi2 > sig2) and (smi > sig))

// buy = longCondition == 1 and longCondition[1] == 1 ? longCondition : na
buy = longCondition == 1 ? longCondition : na
sell = shortCondition == 1? shortCondition : na

// === ALERTS ===
strategy.entry("L", strategy.long, when=buy)

strategy.entry("S", strategy.short, when=sell)

alertcondition(((smi3 < sig3) and (smi2 < sig2) and (smi < sig)), title='Low Fib.', message='Low Fib. Buy')
alertcondition(((smi3 > sig3) and (smi2 > sig2) and (smi > sig)), title='High Fib.', message='High Fib. Low')
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