This strategy combines the Relative Strength Index (RSI) with the Stochastic oscillator to form a dual strategy for more accurately identifying overbought and oversold market conditions, thus generating more reliable trading signals.
The RSI in this strategy has a period of 14, with overbought threshold at 70 and oversold threshold at 30. The %K line of the Stochastic oscillator uses a 3-period SMA, and its %D line is a 3-period SMA of %K. A bullish crossover happens when %K crosses above %D, while a bearish crossover occurs when %K crosses below %D.
The trading signals are generated based on the combined indicators:
When a bullish crossover happens on the Stochastic and RSI is above 70, an overbought signal is generated for going short.
When a bearish crossover happens on the Stochastic and RSI is below 30, an oversold signal is generated for going long.
This dual strategy takes advantage of RSI’s strength in identifying overbought/oversold levels, while using the Stochastic’s trend-following feature to filter out false signals, resulting in more reliable trade entries.
The biggest advantage of this dual strategy is the significantly reduced false signals and improved reliability.
RSI alone can generate excessive false signals. This is because RSI only reflects price overextension levels without considering trend direction. Thus, standalone RSI signals tend to be unreliable.
On the other hand, the Stochastic oscillator can identify trend direction. An upward crossover suggests upside momentum may persist, making overbought RSI signals more reliable.
Conversely, a downward crossover implies impending trend reversal. Oversold RSI signals may be false signals in this case.
Therefore, combining RSI and the Stochastic can better identify both overextension levels and trend directionality, filtering out unreliable signals and locating high-probability turning points.
There are also risks to consider when using this strategy:
The dual indicator approach may filter out some valid signals, causing missed trading opportunities.
Fine tuning of parameters like RSI period and Stochastic smoothing is key, otherwise signal accuracy could be compromised.
Price momentum and volume confirmation are still necessary when taking signals to avoid false breakouts.
Be aware of systemic risks and avoid blind trading during high market volatility.
This strategy can be further enhanced from several aspects:
Optimize RSI and Stochastic parameters through backtesting to find ideal combinations. Machine learning techniques can also be applied for dynamic parameter optimization.
Incorporate volume indicators for signal confirmation, like volume spikes.
Add trend-following overlays like moving averages to avoid market noise and whipsaws. Only consider buy signals when the trend is up.
Utilize machine learning to uncover more sophisticated signal combinations incorporating Bollinger Bands, price patterns, etc. to improve consistency.
Leverage deep learning and big data analytics to develop more intelligent multipurpose trading systems with higher sample efficiency.
In summary, the RSI-Stochastic dual strategy effectively utilizes the strengths of each through ensemble modeling. Compared to standalone RSI, it offers superior filtering capacity and signal precision. Caveats include parameter optimization and risk control. The methodology can be extended to combining other indicators for discovering novel effective trading strategies.
/*backtest
start: 2022-09-30 00:00:00
end: 2023-10-06 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/
//@version=2
//Based on Divergences and Hidden Divergences
//Locates bottom market and reversals
strategy("Vix FIX / StochRSI Strategy", pyramiding=9, initial_capital=10000, default_qty_type=strategy.percent_of_equity, default_qty_value=3, overlay=false)
///////////// Stochastic Slow
Stochlength = input(14, minval=1, title="lookback length of Stochastic")
StochOverBought = input(80, title="Stochastic overbought condition")
StochOverSold = input(20, title="Stochastic oversold condition")
smoothK = input(3, title="smoothing of Stochastic %K ")
smoothD = input(3, title="moving average of Stochastic %K")
k = sma(stoch(close, high, low, Stochlength), smoothK)
d = sma(k, smoothD)
///////////// RSI
RSIlength = input( 14, minval=1 , title="lookback length of RSI")
RSIOverBought = input( 70 , title="RSI overbought condition")
RSIOverSold = input( 30 , title="RSI oversold condition")
RSIprice = close
vrsi = rsi(RSIprice, RSIlength)
///////////// Double strategy: RSI strategy + Stochastic strategy
pd = input(22, title="LookBack Period Standard Deviation High")
bbl = input(20, title="Bolinger Band Length")
mult = input(2.0 , minval=1, maxval=5, title="Bollinger Band Standard Devaition Up")
lb = input(50 , title="Look Back Period Percentile High")
ph = input(.85, title="Highest Percentile - 0.90=90%, 0.95=95%, 0.99=99%")
new = input(false, title="-------Text Plots Below Use Original Criteria-------" )
sbc = input(false, title="Show Text Plot if WVF WAS True and IS Now False")
sbcc = input(false, title="Show Text Plot if WVF IS True")
new2 = input(false, title="-------Text Plots Below Use FILTERED Criteria-------" )
sbcFilt = input(true, title="Show Text Plot For Filtered Entry")
sbcAggr = input(true, title="Show Text Plot For AGGRESSIVE Filtered Entry")
ltLB = input(40, minval=25, maxval=99, title="Long-Term Look Back Current Bar Has To Close Below This Value OR Medium Term--Default=40")
mtLB = input(14, minval=10, maxval=20, title="Medium-Term Look Back Current Bar Has To Close Below This Value OR Long Term--Default=14")
str = input(3, minval=1, maxval=9, title="Entry Price Action Strength--Close > X Bars Back---Default=3")
//Alerts Instructions and Options Below...Inputs Tab
new4 = input(false, title="-------------------------Turn On/Off ALERTS Below---------------------" )
new5 = input(false, title="----To Activate Alerts You HAVE To Check The Boxes Below For Any Alert Criteria You Want----")
sa1 = input(false, title="Show Alert WVF = True?")
sa2 = input(false, title="Show Alert WVF Was True Now False?")
sa3 = input(false, title="Show Alert WVF Filtered?")
sa4 = input(false, title="Show Alert WVF AGGRESSIVE Filter?")
//Williams Vix Fix Formula
wvf = ((highest(close, pd)-low)/(highest(close, pd)))*100
sDev = mult * stdev(wvf, bbl)
midLine = sma(wvf, bbl)
lowerBand = midLine - sDev
upperBand = midLine + sDev
rangeHigh = (highest(wvf, lb)) * ph
//Filtered Bar Criteria
upRange = low > low[1] and close > high[1]
upRange_Aggr = close > close[1] and close > open[1]
//Filtered Criteria
filtered = ((wvf[1] >= upperBand[1] or wvf[1] >= rangeHigh[1]) and (wvf < upperBand and wvf < rangeHigh))
filtered_Aggr = (wvf[1] >= upperBand[1] or wvf[1] >= rangeHigh[1]) and not (wvf < upperBand and wvf < rangeHigh)
//Alerts Criteria
alert1 = wvf >= upperBand or wvf >= rangeHigh ? 1 : 0
alert2 = (wvf[1] >= upperBand[1] or wvf[1] >= rangeHigh[1]) and (wvf < upperBand and wvf < rangeHigh) ? 1 : 0
alert3 = upRange and close > close[str] and (close < close[ltLB] or close < close[mtLB]) and filtered ? 1 : 0
alert4 = upRange_Aggr and close > close[str] and (close < close[ltLB] or close < close[mtLB]) and filtered_Aggr ? 1 : 0
//Coloring Criteria of Williams Vix Fix
col = wvf >= upperBand or wvf >= rangeHigh ? lime : gray
isOverBought = (crossover(k,d) and k > StochOverBought) ? 1 : 0
isOverBoughtv2 = k > StochOverBought ? 1 : 0
filteredAlert = alert3 ? 1 : 0
aggressiveAlert = alert4 ? 1 : 0
plot(isOverBought, "Overbought / Crossover", style=line, color=red)
plot(filteredAlert, "Filtered Alert", style=line, color=fuchsia)
plot(aggressiveAlert, "Aggressive Alert", style=line, color=orange)
if (filteredAlert or aggressiveAlert)
strategy.entry("Long", strategy.long)
if (isOverBought)
strategy.close("Long")