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RSI Indicator Based Reversal Strategy

Author: ChaoZhang, Date: 2024-01-08 16:47:07
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Overview

This strategy identifies reversal opportunities after overbought or oversold situations based on the RSI indicator. It will monitor the divergence between price and RSI after RSI enters overbought or oversold zones to determine potential future reversal chances.

Strategy Logic

This strategy uses the RSI indicator to determine the overbought and oversold situations in the market. After RSI enters a preset overbought or oversold zone, it will start monitoring reversal divergences.

Specifically, if RSI enters the overbought zone, it will monitor whether the price continues to rise (forming higher lows) while RSI forms lower lows - a regular bullish divergence; or the price forms lower lows and RSI forms higher lows – a hidden bullish divergence. Both situations signal potential downside reversals ahead.

Similarly, if RSI enters the oversold zone, it will monitor whether the price continues to fall (forming lower highs) while RSI forms higher highs – a regular bearish divergence; or the price forms higher highs and RSI forms lower highs – a hidden bearish divergence. Both situations also signal potential upside reversals ahead.

Once the above reversal signals are detected, long or short positions will be taken according to the configured parameters.

Advantages

The biggest advantage of this strategy is being able to identify extreme market situations where reversal probabilities are high and the profit margin for reversal operations is large. Compared to simple trend-following strategies, counter-trend strategies like this one have higher win rates and profitability.

In addition, the strategy incorporates monitoring for both regular and hidden divergences so that more reversal opportunities can be identified and good chances will not be missed due to one-off situations.

Risks

The biggest risk this strategy faces is even more extreme overbought or oversold situations, the so-called “straight up, 90 degrees down”. Continuing with long or short operations is more likely in such cases, and taking reversal action can easily result in stop loss.

Besides, if the parameters are not set properly and there are errors in judging overbought and oversold situations, mistakes can easily occur.

The way to handle this is to reasonably set the upper and lower limits for overbought and oversold zones to avoid overly extreme situations. Also scale down the position size in live trading to control the amount for a single stop loss.

Optimization Directions

The strategy can be optimized in the following aspects:

  1. Incorporate other indicators to determine overbought and oversold conditions to avoid relying solely on RSI

  2. Add logic to identify consolidation before breakouts when reversal probability is higher

  3. Optimize profit target settings after reversals to enable more scientific position sizing

  4. Use machine learning methods on recent years of historical data to automatically optimize parameters

  5. Improve stop loss logic optimization, e.g. timely profit taking, staggered stop loss, trailing stop loss etc.

Conclusion

In conclusion, this is a typical statistical arbitrage strategy. It tries to capture opportunities when the market rebounds from extreme situations back to equilibrium. Compared to trend-following strategies, it has higher win rates and profitability but also faces greater risks. With parameter optimization and risk control this type of strategies can profit steadily.


/*backtest
start: 2023-01-01 00:00:00
end: 2024-01-07 00:00:00
period: 1d
basePeriod: 1h
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/
// made by Imal_Max 
// thanks to neo the crypto trader's idea
//
// thanks to JayTradingCharts RSI Divergence /w Alerts indicator for the base code. 
// we modified this to detect the divergence only if price was oversold or overbought recently and a few more settings
// also now you can backtest the settings easy

//@version=5

// 🔥 comment out the line below to disable the alerts and enable the backtester 
//indicator(title="RSI Divergence Indicator with Alerts Overbought Oversold", shorttitle="RSI OB/OS Divergence", format=format.price, timeframe="")



// 🔥 uncomment the line below to enable the backtester + uncomment the lines slightly below and at the bottom of the script
strategy(title="RSI Divergence Indicator with Alerts Overbought Oversold", shorttitle="RSI OB/OS Divergence", overlay=true)





len = input.int(title='RSI Period', minval=1, defval=14, group='regular RSI settings')
src = input.source(title='RSI Source', defval=close, group='regular RSI settings')
lbR = input.int(title='Pivot Lookback Right', defval=5, group='regular RSI settings')
lbL = input.int(title='Pivot Lookback Left', defval=5, group='regular RSI settings')


rangeUpper = input.int(title='Max of Lookback Range', defval=60, group='regular RSI settings')
rangeLower = input.int(title='Min of Lookback Range', defval=5, group='regular RSI settings')
plotBull = input.bool(title='Plot Bullish', defval=true, group='regular RSI settings')
plotHiddenBull = input.bool(title='Plot Hidden Bullish', defval=true, group='regular RSI settings')
plotBear = input.bool(title='Plot Bearish', defval=true, group='regular RSI settings')
plotHiddenBear = input.bool(title='Plot Hidden Bearish', defval=true, group='regular RSI settings')



// ob/os divergence settings

obvalue = input.int(title='OB RSI Value', defval=70, group='look for RSI divergence after OverBought/OverSold', inline='Input 0', tooltip="min RSI Level needed within lookback period to look for bullish divergences")
oblookback = input.int(title='OB lookback period', defval=30, group='look for RSI divergence after OverBought/OverSold', inline='Input 0')
osvalue = input.int(title='OS RSI Value', defval=35, group='look for RSI divergence after OverBought/OverSold', inline='Input 1', tooltip="max RSI Level needed within lookback period to look for bearish divergences")
oslookback = input.int(title='OS lookback period', defval=30, group='look for RSI divergence after OverBought/OverSold', inline='Input 1')
minBearRSI = input.int(title='min RSI for bear Alerts', defval=60, group='look for RSI divergence after OverBought/OverSold', tooltip="min RSI needed at the time where bearish divergence gets detected")
maxBullRSI = input.int(title='max RSI for Bull Alerts', defval=50, group='look for RSI divergence after OverBought/OverSold', tooltip="max RSI needed at the time where bullish divergence gets detected")


// Backtesteer Info
enableBacktesterInfo = input(true, title="to enable the Backtester, uncomment/comment the 🔥 lines in the source code", group='enable Backtester')


// Backtester input stuff

// long settings - 🔥 uncomment the 3 lines below to disable the alerts and enable the backtester 
longTrading = input(true, title="enable Long Backtester (to disable uncheck 'plot Bullish' and 'plot hidden Bullish as well')", group='Long Backtester')
longStopLoss = input.float(0.5, title='Stop Loss %', group='Long Backtester') / 100
longTakeProfit = input.float(2.0, title='Take Profit %', group='Long Backtester') / 100

// short settings - 🔥 uncomment the 3 lines below to disable the alerts and enable the backtester 
shortTrading = input(true, title="enable Short Backtester (to disable uncheck 'plot Bearish' and 'plot hidden Bearish as well'", group='Short Backtester')
shortStopLoss = input.float(0.5, title='Stop Loss %', group='Short Backtester') / 100
shortTakeProfit = input.float(2.0, title='Take Profit %', group='Short Backtester') / 100

// Backtesting Range settings - 🔥 uncomment the 6 lines below to disable the alerts and enable the backtester 
startDate = input.int(title='Start Date', defval=1, minval=1, maxval=31, group='Backtesting range')
startMonth = input.int(title='Start Month', defval=1, minval=1, maxval=12, group='Backtesting range')
startYear = input.int(title='Start Year', defval=2016, minval=1800, maxval=2100, group='Backtesting range')
endDate = input.int(title='End Date', defval=1, minval=1, maxval=31, group='Backtesting range')
endMonth = input.int(title='End Month', defval=1, minval=1, maxval=12, group='Backtesting range')
endYear = input.int(title='End Year', defval=2040, minval=1800, maxval=2100, group='Backtesting range')





bearColor = color.red
bullColor = color.green
hiddenBullColor = color.new(color.green, 80)
hiddenBearColor = color.new(color.red, 80)
textColor = color.white
noneColor = color.new(color.white, 100)
osc = ta.rsi(src, len)

plot(osc, title='RSI', linewidth=2, color=color.new(#00bcd4, 0))
obLevel = hline(obvalue, title='Overbought', linestyle=hline.style_dotted)
osLevel = hline(osvalue, title='Oversold', linestyle=hline.style_dotted)

minRSIline = hline(minBearRSI, title='max RSI for Bull divergence', linestyle=hline.style_dotted)
maxRSIline = hline(maxBullRSI, title='max RSI for Bull divergence', linestyle=hline.style_dotted)

fill(obLevel, minRSIline, title='Bear Zone Background', color=color.new(#f44336, 90))
fill(osLevel, maxRSIline, title='Bull Zone Background', color=color.new(#4caf50, 90))

RSI0line = hline(0, title='RSI 0 Line', linestyle=hline.style_dotted)
RSI100line = hline(100, title='RSI 100 Line', linestyle=hline.style_dotted)

fill(obLevel, RSI100line, title='Overbought Zone Background', color=color.new(#e91e63, 75))
fill(osLevel, RSI0line, title='Oversold Zone Background', color=color.new(#4caf50, 75))


plFound = na(ta.pivotlow(osc, lbL, lbR)) ? false : true
phFound = na(ta.pivothigh(osc, lbL, lbR)) ? false : true
_inRange(cond) =>
    bars = ta.barssince(cond == true)
    rangeLower <= bars and bars <= rangeUpper


// check if RSI was OS or OB recently

obHighestRsi = ta.highest(osc, oblookback)
osLowestRsi = ta.lowest(osc, oslookback)


//------------------------------------------------------------------------------
// Regular Bullish
// Osc: Higher Low

oscHL = osc[lbR] > ta.valuewhen(plFound, osc[lbR], 1) and _inRange(plFound[1])

// Price: Lower Low

priceLL = low[lbR] < ta.valuewhen(plFound, low[lbR], 1)


bullCond = plotBull and priceLL and oscHL and plFound and osLowestRsi < osvalue and osc < maxBullRSI


plot(plFound ? osc[lbR] : na, offset=-lbR, title='Regular Bullish', linewidth=2, color=bullCond ? bullColor : noneColor, transp=0)

plotshape(bullCond ? osc[lbR] : na, offset=-lbR, title='Regular Bullish Label', text=' Bull ', style=shape.labelup, location=location.absolute, color=bullColor, textcolor=textColor, transp=0)

//------------------------------------------------------------------------------
// Hidden Bullish
// Osc: Lower Low

oscLL = osc[lbR] < ta.valuewhen(plFound, osc[lbR], 1) and _inRange(plFound[1])

// Price: Higher Low

priceHL = low[lbR] > ta.valuewhen(plFound, low[lbR], 1)


hiddenBullCond = plotHiddenBull and priceHL and oscLL and plFound and osLowestRsi < osvalue and osc < maxBullRSI


plot(plFound ? osc[lbR] : na, offset=-lbR, title='Hidden Bullish', linewidth=2, color=hiddenBullCond ? hiddenBullColor : noneColor, transp=0)

plotshape(hiddenBullCond ? osc[lbR] : na, offset=-lbR, title='Hidden Bullish Label', text=' H Bull ', style=shape.labelup, location=location.absolute, color=bullColor, textcolor=textColor, transp=0)

//------------------------------------------------------------------------------
// Regular Bearish
// Osc: Lower High

oscLH = osc[lbR] < ta.valuewhen(phFound, osc[lbR], 1) and _inRange(phFound[1])

// Price: Higher High

priceHH = high[lbR] > ta.valuewhen(phFound, high[lbR], 1)

bearCond = plotBear and priceHH and oscLH and phFound and obHighestRsi > obvalue and osc > minBearRSI

plot(phFound ? osc[lbR] : na, offset=-lbR, title='Regular Bearish', linewidth=2, color=bearCond ? bearColor : noneColor, transp=0)

plotshape(bearCond ? osc[lbR] : na, offset=-lbR, title='Regular Bearish Label', text=' Bear ', style=shape.labeldown, location=location.absolute, color=bearColor, textcolor=textColor, transp=0)

//------------------------------------------------------------------------------
// Hidden Bearish
// Osc: Higher High

oscHH = osc[lbR] > ta.valuewhen(phFound, osc[lbR], 1) and _inRange(phFound[1])

// Price: Lower High

priceLH = high[lbR] < ta.valuewhen(phFound, high[lbR], 1)



hiddenBearCond = plotHiddenBear and priceLH and oscHH and phFound and obHighestRsi > obvalue and osc > minBearRSI



plot(phFound ? osc[lbR] : na, offset=-lbR, title='Hidden Bearish', linewidth=2, color=hiddenBearCond ? hiddenBearColor : noneColor, transp=0)

plotshape(hiddenBearCond ? osc[lbR] : na, offset=-lbR, title='Hidden Bearish Label', text=' H Bear ', style=shape.labeldown, location=location.absolute, color=bearColor, textcolor=textColor, transp=0)



alertcondition(bullCond, title='Bullish divergence', message='Regular Bull Div {{ticker}} XXmin')
alertcondition(bearCond, title='Bearish divergence', message='Regular Bear Div {{ticker}} XXmin')
alertcondition(hiddenBullCond, title='Hidden Bullish divergence', message='Hidden Bull Div {{ticker}} XXmin')
alertcondition(hiddenBearCond, title='Hidden Bearish divergence', message='Hidden Bear Div {{ticker}} XXmin')




// 🔥 uncomment the all lines below for the backtester and revert for alerts
longTP = strategy.position_size > 0 ? strategy.position_avg_price * (1 + longTakeProfit) : strategy.position_size < 0 ? strategy.position_avg_price * (1 - longTakeProfit) : na
longSL = strategy.position_size > 0 ? strategy.position_avg_price * (1 - longStopLoss) : strategy.position_size < 0 ? strategy.position_avg_price * (1 + longStopLoss) : na
shortTP = strategy.position_size > 0 ? strategy.position_avg_price * (1 + shortTakeProfit) : strategy.position_size < 0 ? strategy.position_avg_price * (1 - shortTakeProfit) : na
shortSL = strategy.position_size > 0 ? strategy.position_avg_price * (1 - shortStopLoss) : strategy.position_size < 0 ? strategy.position_avg_price * (1 + shortStopLoss) : na
strategy.risk.allow_entry_in(longTrading == true and shortTrading == true ? strategy.direction.all : longTrading == true ? strategy.direction.long : shortTrading == true ? strategy.direction.short : na)
strategy.entry('Bull', strategy.long, comment='Long', when=bullCond)
strategy.entry('Bull', strategy.long, comment='Long', when=hiddenBullCond)
strategy.entry('Bear', strategy.short, comment='Short', when=bearCond)
strategy.entry('Bear', strategy.short, comment='Short', when=hiddenBearCond)
strategy.exit(id='longTP-SL', from_entry='Bull', limit=longTP, stop=longSL)
strategy.exit(id='shortTP-SL', from_entry='Bear', limit=shortTP, stop=shortSL)



template: strategy.tpl:40:21: executing "strategy.tpl" at <.api.GetStrategyListByName>: wrong number of args for GetStrategyListByName: want 7 got 6