StochRSI Based Quantitative Trading Strategy

Pine ScriptBreakout Mean reversion RSI MACD SMA Bollinger Bands Stochastic

Author: ChaoZhang
Complexity: Intermediate · 57 lines
Parameters: 11
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy is developed based on the StochRSI indicator. The strategy mainly uses the StochRSI indicator to judge overbought and oversold situations. Combined with the RSI indicator to filter out some false signals, go short when the StochRSI indicator shows overbought area and go long when it shows oversold area to make profits.

Strategy Principle

This strategy mainly applies the StochRSI indicator to judge overbought and oversold areas in the market. The StochRSI indicator consists of the K line and the D line. The K line reflects the position of the current RSI value in the RSI price range over a recent period. The D line is the moving average of the K line. When the K line crosses above the D line, it is an overbought area and long positions can be taken. When the K line falls below the D line, it is an oversold area and short positions can be taken.

Specifically, the strategy first calculates the value of the 14-period RSI indicator, and then applies the StochRSI indicator on the RSI indicator. The StochRSI indicator parameters are set with a length of 14, smoothed K line period of 3 and smoothed D line period of 3. When the K line crosses above the user-defined oversold area (default is 1), long position will be taken. When the K line falls below the user-defined overbought area (default is 99), short position will be taken.

In addition, stop loss and take profit parameters are set in the strategy. The stop loss is default to 10000. The take profit uses trailing stop with default trailing points of 300 and offset of 0.

Advantage Analysis

Using StochRSI indicator to determine overbought and oversold areas is more reliable than single RSI indicator
Filtering signals with RSI avoids false breakouts
Setting stop loss and take profit mechanisms to control risks

Risk Analysis

StochRSI indicator may have false signals
Need to set overbought and oversold parameters reasonably, otherwise it will cause misoperation
If stop loss point is too small, it's easy to be trapped. If take profit point is too large, the profit gaining may be limited.

For the above risks, longer cycle parameters can be set or consider using in combination with other indicators to filter out signals, adjust overbought and oversold parameters to adapt to different markets, and test different stop loss and take profit parameters.

Optimization Directions

Consider using in combination with other indicators such as MACD, Bollinger Bands etc to filter out false signals
Test different parameter cycle settings to adapt to more market conditions
Optimize stop loss and take profit points by multiple backtestings to find the optimal parameters

Summary

This strategy trades based on overbought and oversold areas judged by the StochRSI indicator. Compared with single RSI indicator, StochRSI combines the idea of KDJ and can judge turning points more accurately. At the same time, false signals are filtered out by RSI and risks are controlled by stop loss and take profit. There is still large room for optimization, it can be combined with other indicators or optimized parameter settings.

Parameters

Name	Default	What it controls
v_input_1	10	lengthrsi
v_input_2	true	overSold
v_input_3	99	overBought
v_input_4	300	call_trail_stop
v_input_5	false	call_trail_offset
v_input_6	10000	call_sl
v_input_7	3	smoothK
v_input_8	3	smoothD
v_input_9	14	lengthRSI
v_input_10	14	lengthStoch
v_input_11_close	0	RSI Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4

Source Pine Script

/*backtest
start: 2023-11-06 00:00:00
end: 2023-12-06 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version= 2
strategy("STOCHRSI JURE", overlay=false)
lengthrsi = input(10)
overSold = input( 1 )
overBought = input(99)

call_trail_stop = input(300)
call_trail_offset = input(0)
call_sl = input(10000)

price = ohlc4
vrsi = rsi(price, lengthrsi)

smoothK = input(3, minval=1)
smoothD = input(3, minval=1)
lengthRSI = input(14, minval=1)
lengthStoch = input(14, minval=1)
src = input(close, title="RSI Source")

rsi1 = rsi(src, lengthRSI)
k = sma(stoch(rsi1, rsi1, rsi1, lengthStoch), smoothK)
d = sma(k, smoothD)


plot( k, color=blue, linewidth=1, title="K")
plot( d, color=red, linewidth=1, title="D")

if (crossover(k, overSold) ) 
    strategy.entry("BUY", strategy.long, stop=close, oca_name="TREND",  comment="BUY")
    strategy.exit("BUY EXIT", "BUY", trail_points=call_trail_stop, trail_offset=call_trail_offset, loss = call_sl)


if (crossunder(k, overBought) ) 
    strategy.entry("SELL", strategy.short,stop=close, oca_name="TREND", comment="SELL")
    strategy.exit("SELL EXIT", "SELL", trail_points=call_trail_stop, trail_offset=call_trail_offset, loss = call_sl)
    

//if (  ( crossover(k,d)) and ( (vrsi<overSold) or crossover(vrsi,overSold) )  and   year >= yearfrom and year <= yearuntil and month>=monthfrom and month <=monthuntil and dayofmonth>=dayfrom and dayofmonth < dayuntil) 
//    strategy.entry("BUY", strategy.long, stop=close, oca_name="TREND", oca_type=strategy.oca.cancel, comment="BUY")
//else
//    strategy.cancel(id="BUY")

//if ( ( crossunder(k,d) ) and ( (vrsi >overBought) or crossunder(vrsi,overBought) ) and   year >= yearfrom and year <= yearuntil and month>=monthfrom and month <=monthuntil and dayofmonth>=dayfrom and dayofmonth < dayuntil ) 
//    strategy.entry("SELL", strategy.short,stop=close, oca_name="TREND", oca_type=strategy.oca.cancel, comment="SELL")
//else
//    strategy.cancel(id="SELL")

Published by ChaoZhang on the FMZ strategy square · last modified 2023-12-07. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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