Bollinger Band and Stoch RSI Trading Strategy

This strategy combines the Bollinger Bands and Stoch RSI indicators for multiple indicator trading. It belongs to the typical combined indicators strategy type. The Bollinger Bands determine trend direction and the…

Pine ScriptBreakout Trend following Volatility RSI MACD SMA Bollinger Bands Stochastic

Author: ChaoZhang
Complexity: Intermediate · 94 lines
Parameters: 15
Backtest bar: 2d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

The strategy is based on two main indicators:

Bollinger Bands

Calculate the upper, middle and lower bands. A buy signal is generated when price breaks above the lower band.
Stoch RSI

Calculate the Stoch RSI indicator. A buy signal is generated when the K line crosses above the D line.

The specific trading logic is: open long when both the Bollinger Bands lower breakout and Stoch RSI golden cross occur together.

The exit logic uses the bands for take profit and stop loss: close for profit when price touches the upper or middle band again, close for loss when price breaks back below the lower band.

Advantages

Combines Bollinger Bands and Stoch RSI
Bands judge overall trend, Stoch RSI optimizes entry
Stoch RSI filters false band breakouts
Middle and lower bands provide exits
Multiple adjustable parameters for optimizations

Risks

MA-based indicators lag, missing best entries
Purely indicator-driven, slow reaction to sudden events
Improper band settings invalidate stops
Bad Stoch RSI parameters generate false signals
Separate parameter tuning needed for different products

Risks can be reduced by:

Optimizing parameters for higher accuracy
Adding confirming filters like MACD
Using trailing stops instead of band stops
Testing parameters for different products
Adjusting position sizing system

Enhancement Directions

The strategy can be improved by:

Optimizing Bollinger Bands parameters

Adjust upper/lower calculation ratios for best fit
Optimizing Stoch RSI parameters

Finding optimal K and D values
Adding confirming indicators like MACD

Avoid false signals relying on single indicator
Using trailing profit stops instead of fixed stops

Trail stops based on price volatility
Testing parameters separately for different products

Optimal parameters vary across different products

Summary

This strategy leverages the Bollinger Bands for trend direction and Stoch RSI for entry optimization, taking advantage of a multi-indicator approach. But challenges like difficult parameter optimization and signal accuracy exist. Rigorous backtesting for parameter optimization, adding filters, and continuously adjusting rules based on results can improve accuracy while retaining the strengths of a combined system. Persistent optimizations lead to robustness.

Parameters

Name	Default	What it controls
v_input_1	50	bblength
v_input_2	2	Multiplier for BB Upper Band
v_input_3	2	Multiplier for BB Lower Band
v_input_4	6	lengthrsi
v_input_5	20	overSold
v_input_6	70	overBought
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
v_input_12	6	monthfrom
v_input_13	12	monthuntil
v_input_14	true	dayfrom
v_input_15	31	dayuntil

Source Pine Script

/*backtest
start: 2022-09-14 00:00:00
end: 2023-09-20 00:00:00
period: 2d
basePeriod: 1d
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=3

strategy(title = "BB+RSI v2", overlay = true)

price=close
////////// ///////  BB /////////////////////////

bblength = input(50)
bbupmult =input(2,step=0.1,title="Multiplier for BB Upper Band")
bblowmult = input(2,step=0.1,title="Multiplier for BB Lower Band")

basis =  sma(close,bblength)

devup = bbupmult * stdev(close, bblength)
devlow = bblowmult * stdev(close, bblength)

upper = basis + devup
lower = basis - devlow
plot(basis, color=red)
p1 = plot(upper, color=blue)
p2 = plot(lower, color=blue)
fill(p1, p2)


bbbuy= crossover(price,lower)
bbsell = crossunder(price,upper) or price>upper or crossunder(price,basis)



//////////////////// BB //////////////////////




////////////////////////  S RSI  /////////////////////

lengthrsi = input(6)
overSold = input( 20 )
overBought = input( 70 )
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)

SRSIbuy=crossover(k,d)

////////////////////// S  RSI  ///////////////////////

// Conditions



longcond = bbbuy and SRSIbuy
closelong = bbsell


monthfrom =input(6)
monthuntil =input(12)
dayfrom=input(1)
dayuntil=input(31)



if (  longcond ) 
    strategy.entry("BUY", strategy.long, stop=close, oca_name="TREND",  comment="BUY")
    
else
    strategy.cancel(id="BUY")


if ( closelong  ) 

    strategy.close("BUY")

Published by ChaoZhang on the FMZ strategy square · last modified 2023-09-21. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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