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Strategy vault / Machine learning

RSI Divergence Trading Strategy

This strategy identifies regular and hidden bullish/bearish RSI divergence signals to determine long and short positions.

Author
ChaoZhang
Complexity
Intermediate · 166 lines
Parameters
10
Backtest bar
1h · intraday
Tested on
BTC/USDT · futures

IMG

Strategy Name

RSI Bullish/Bearish Divergence Trading Strategy

Overview

This strategy identifies regular and hidden bullish/bearish RSI divergence signals to determine long and short positions.

Principles

When price makes a new high and RSI fails to make a new high, it forms bullish divergence, which is treated as selling signal. When price makes a new low and RSI fails to make a new low, it forms bearish divergence, which is treated as buying signal. Regular divergence refers to the obvious divergence between price and RSI while hidden divergence means relatively concealed divergence between them. Long or short positions are determined based on identified regular or hidden bullish/bearish divergence signals.

Advantage Analysis

  1. Divergence signals have relatively high reliability with higher winning rate.
  2. Identification of both regular and hidden bullish/bearish divergence provides extensive coverage.
  3. Adjustable RSI parameters make it adaptable to different market environments.

Risk Analysis

  1. Hidden divergence signals have higher probability of misjudgment.
  2. Manual review is needed to filter out misjudged signals.
  3. Effectiveness depends on RSI parameter settings.

Optimization Directions

  1. Optimize RSI parameters to find best parameter combinations.
  2. Add machine learning algorithms for automatic identification of true signals.
  3. Incorporate more indicators to verify signal reliability.

Summary

This strategy identifies RSI divergence trading signals based on regular and hidden bullish/bearish divergence to determine long or short positions, which provides relatively higher winning rate. Further improvements on strategy effectiveness could be achieved by optimizing RSI parameters, adding other validating indicators.

Parameters

NameDefaultWhat it controls
v_input_int_114RSI Period
v_input_1_close0RSI Source: close | high | low | open | hl2 | hlc3 | hlcc4 | ohlc4
v_input_25Pivot Lookback Right
v_input_35Pivot Lookback Left
v_input_460Max of Lookback Range
v_input_55Min of Lookback Range
v_input_6truePlot Bullish
v_input_7truePlot Hidden Bullish
v_input_8truePlot Bearish
v_input_9truePlot Hidden Bearish

Source Pine Script

/*backtest
start: 2023-12-22 00:00:00
end: 2024-01-21 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy(title="Divergence Indicator")
len = input.int(title="RSI Period", minval=1, defval=14)
src = input(title="RSI Source", defval=close)
lbR = input(title="Pivot Lookback Right", defval=5)
lbL = input(title="Pivot Lookback Left", defval=5)
rangeUpper = input(title="Max of Lookback Range", defval=60)
rangeLower = input(title="Min of Lookback Range", defval=5)
plotBull = input(title="Plot Bullish", defval=true)
plotHiddenBull = input(title="Plot Hidden Bullish", defval=true)
plotBear = input(title="Plot Bearish", defval=true)
plotHiddenBear = input(title="Plot Hidden Bearish", defval=true)
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=#2962FF)
hline(50, title="Middle Line", color=#787B86, linestyle=hline.style_dotted)
obLevel = hline(70, title="Overbought", color=#787B86, linestyle=hline.style_dotted)
osLevel = hline(30, title="Oversold", color=#787B86, linestyle=hline.style_dotted)
fill(obLevel, osLevel, title="Background", color=color.rgb(33, 150, 243, 90))

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

//------------------------------------------------------------------------------
// 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) 
// bull : 상승 Condition : 조건
bullCond = plotBull and priceLL and oscHL and plFound // 상승다이버전스?
strategy.entry("상승 다이버전스 진입", strategy.long, when = bullCond)
strategy.close("상승 다이버전스 진입", when = ta.crossover(osc, 50)) 
plot(
     plFound ? osc[lbR] : na,
     offset=-lbR,
     title="Regular Bullish",
     linewidth=2,
     color=(bullCond ? bullColor : noneColor)
     )

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

//------------------------------------------------------------------------------
// 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
// strategy.entry("히든 상승 다이버전스 진입", strategy.long, when = hiddenBullCond)
// strategy.close("히든 상승 다이버전스 진입", when = ta.crossover(osc, 50))
plot(
	 plFound ? osc[lbR] : na,
	 offset=-lbR,
	 title="Hidden Bullish",
	 linewidth=2,
	 color=(hiddenBullCond ? hiddenBullColor : noneColor)
	 )

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

//------------------------------------------------------------------------------
// 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)
// bear : 하락 
bearCond = plotBear and priceHH and oscLH and phFound
// strategy.entry("하락 다이버전스 진입", strategy.short, when = bearCond)
// strategy.close("하락 다이버전스 진입", when = ta.crossunder(osc, 50)) 
plot(
	 phFound ? osc[lbR] : na,
	 offset=-lbR,
	 title="Regular Bearish",
	 linewidth=2,
	 color=(bearCond ? bearColor : noneColor)
	 )

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

//------------------------------------------------------------------------------
// 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
// strategy.entry("히든 하락 다이버전스 진입", strategy.short, when = hiddenBearCond)
// strategy.close("히든 하락 다이버전스 진입", when = ta.crossunder(osc, 50)) 
plot(
	 phFound ? osc[lbR] : na,
	 offset=-lbR,
	 title="Hidden Bearish",
	 linewidth=2,
	 color=(hiddenBearCond ? hiddenBearColor : noneColor)
	 )

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

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-22. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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