Double Bollinger Band Breakout Strategy

The Double Bollinger Band Breakout Strategy is a short-term trading strategy that utilizes the Bollinger Band indicator. It employs two Bollinger Bands with different parameter settings, fast and slow, to identify…

Pine ScriptBreakout Mean reversion Momentum RSI MACD Bollinger Bands ATR

Author: ChaoZhang
Complexity: Intermediate · 197 lines
Parameters: 17
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

The strategy uses a fast Bollinger Band with length of 20 and standard deviation of 1, and a slow Bollinger Band with length of 50 and standard deviation of 1. When the close price breaks above the upper band of the fast Bollinger, a long position is entered using the closing price. When the close price breaks below the lower band of the fast Bollinger, a short position is entered.

Once in a position, the strategy waits for further confirmation by price breaking the upper or lower band of the slow Bollinger. In addition, the RSI indicator is used to determine the trend direction. Buy signals from upper band breakouts are only considered when RSI is above 50. Sell signals from lower band breakouts are only considered when RSI is below 50.

After positions are established, they will be closed when price breaks back inside the fast Bollinger Bands up or down.

Advantage Analysis

The main advantage of the Double Bollinger Band Breakout Strategy lies in its ability to capture small moves. By using the fast Bollinger Band to catch small breakouts and the slow Bollinger Band to filter false signals, it can profit from low-range fluctuations. The addition of RSI also helps avoid missing major trend reversals during ranging markets.

Moreover, as a momentum indicator itself, the Bollinger Band excels at detecting high volatility stages in the market, which benefits short-term trading strategies.

Risk Analysis

The major risk comes from the possibly excessive trading signals generated by the double Bollinger setup, which may fail to filter market noise effectively. This could lead to accumulated losses from erroneous trades. Also, when volatility is low, the width of the bands narrows and trading opportunities decrease.

To mitigate risks, parameters of the Bollinger Bands can be adjusted, using longer slow bands or manual confirmation of signals. Combining other indicators like MACD and KDJ may also enhance stability.

Optimization Directions

The main optimization space lies in adjusting the parameters of the Bollinger Bands and RSI. For example, testing different periods for the fast and slow bands to find the optimal combination. Or try different RSI periods to see if strategy performance can be improved.

Another direction is to add or amend stop loss logic. Currently there is no stop loss mechanism, which increases maximum drawdown risk. Adding fixed percentage or trailing stop loss could significantly improve risk-reward metrics.

Conclusion

The Double Bollinger Band Breakout Strategy is a short-term momentum trading strategy sensitive to market volatility. It captures small price moves within volatile markets when clear signals are given by the double Bollinger setup. However, further proof of reliability is needed. Through parameter tuning and adding stop loss logic, there is good potential to further improve stability.

Parameters

Name	Default	What it controls
v_input_1	false	Strategy Direction
v_input_2	true	-----------------Strategy Inputs-------------------
v_input_3	14	RSI Length
v_input_4	45	Slow BB Band Length
v_input_5	31	Fast BB Band Length
v_input_6	true	-----------------General Inputs-------------------
v_input_7	true	Use Stop Loss and Take Profit
v_input_8	0	Type Of Stop: Strategy Stop \| Swing Lo/Hi \| ATR Stop
v_input_9	10	Swing Point Lookback
v_input_10	true	Swing Point SL Perc Increment
v_input_11	14	ATR Length
v_input_12	5	ATR Multiple
v_input_13	2	Take Profit Risk Reward Ratio
v_input_14	false	Trailing Stop
v_input_15	true	Use Strategy Close Logic
v_input_16	true	Allow Direct Position Reverse
v_input_17	false	Reverse Trades

Source Pine Script

/*backtest
start: 2022-12-27 00:00:00
end: 2024-01-02 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/

// From "Bitcoin Trading Strategies: Algorithmic Trading Strategies For Bitcoin And Cryptocurrency That Work" by David Hanson.

// "Double Bolinger Band Scalping System 
// Recommended Timeframe: 1 minute or 5 minute 

// Required Indicators: 
// - RSI with a length of 14 (default settings) 
// - Bolinger band #1 settings: Length = 50, stDev = 1 Hide the basis/middle line (basis line not needed for this strategy) 
// Note: This is the slower bolinger band in the directions 
// - Bolinger band #2 settings: Length 20, stDev = 1 Hide the basis/middle line (basis line not needed for this strategy) 
// Note: This is the faster bolinger band in the directions 

// Enter Long/Buy Trade When: 
// - RSI is above the level 50 
// - A candle closes above the top of the faster bolinger band 
// Enter a long when a candle then closes above the top of the slower bolinger band, and price is above the top of both bands 
// Place a stop loss under the low of the entry candle Example of a long trade using this strategy 
// Exit Long Trade When: A candle closes below the top band of the fast bolinger band 

// Enter Short/Sell Trade When: 
// - RSI is below the level 50 
// - A candle closes below the bottom of the faster bolinger band 
// Enter a short when a candle then closes below the bottom of the slower bolinger band, and price is below both bands 
// Place a stop loss above the high of the entry candle Example of a short trade using this strategy 
// Exit Short Trade When: Price closes inside the bottom of the faster bolinger band"

// © tweakerID

//@version=4
strategy("Double Bollinger Strategy", 
     overlay=true, 
     default_qty_type=strategy.percent_of_equity, 
     default_qty_value=100, 
     initial_capital=10000, 
     commission_value=0.04, 
     calc_on_every_tick=false, 
     slippage=0)

direction = input(0, title = "Strategy Direction", type=input.integer, minval=-1, maxval=1)
strategy.risk.allow_entry_in(direction == 0 ? strategy.direction.all : (direction < 0 ? strategy.direction.short : strategy.direction.long))

/////////////////////// STRATEGY INPUTS ////////////////////////////////////////
title1=input(true, "-----------------Strategy Inputs-------------------")  

i_RSI=input(14, title="RSI Length")
lengthS = input(45, minval=1, title="Slow BB Band Length")
lengthF = input(31, minval=1, title="Fast BB Band Length")

/////////////////////// BACKTESTER /////////////////////////////////////////////
title2=input(true, "-----------------General Inputs-------------------")  

// Backtester General Inputs
i_SL=input(true, title="Use Stop Loss and Take Profit")
i_SLType=input(defval="Strategy Stop", title="Type Of Stop", options=["Strategy Stop", "Swing Lo/Hi", "ATR Stop"])
i_SPL=input(defval=10, title="Swing Point Lookback")
i_PercIncrement=input(defval=1, step=.1, title="Swing Point SL Perc Increment")*0.01
i_ATR = input(14, title="ATR Length")
i_ATRMult = input(5, step=.1, title="ATR Multiple")
i_TPRRR = input(2, step=.1, title="Take Profit Risk Reward Ratio")
TS=input(false, title="Trailing Stop")

// Bought and Sold Boolean Signal
bought = strategy.position_size > strategy.position_size[1] 
 or strategy.position_size < strategy.position_size[1]

// Price Action Stop and Take Profit
LL=(lowest(i_SPL))*(1-i_PercIncrement)
HH=(highest(i_SPL))*(1+i_PercIncrement)
LL_price = valuewhen(bought, LL, 0)
HH_price = valuewhen(bought, HH, 0)
entry_LL_price = strategy.position_size > 0 ? LL_price : na 
entry_HH_price = strategy.position_size < 0 ? HH_price : na 
tp=strategy.position_avg_price + (strategy.position_avg_price - entry_LL_price)*i_TPRRR
stp=strategy.position_avg_price - (entry_HH_price - strategy.position_avg_price)*i_TPRRR

// ATR Stop
ATR=atr(i_ATR)*i_ATRMult
ATRLong = ohlc4 - ATR
ATRShort = ohlc4 + ATR
ATRLongStop = valuewhen(bought, ATRLong, 0)
ATRShortStop = valuewhen(bought, ATRShort, 0)
LongSL_ATR_price = strategy.position_size > 0 ? ATRLongStop : na 
ShortSL_ATR_price = strategy.position_size < 0 ? ATRShortStop : na 
ATRtp=strategy.position_avg_price + (strategy.position_avg_price - LongSL_ATR_price)*i_TPRRR
ATRstp=strategy.position_avg_price - (ShortSL_ATR_price - strategy.position_avg_price)*i_TPRRR


// Strategy Stop
float LongStop = valuewhen(bought,low[1],0)*(1-i_PercIncrement)
float ShortStop = valuewhen(bought,high[1],0)*(1+i_PercIncrement)
float StratTP = na
float StratSTP = na

/////////////////////// STRATEGY LOGIC /////////////////////////////////////////

//RSI
RSI=rsi(close, i_RSI)

//BOLL1
[middleS, upperS, lowerS] = bb(close, lengthS, 1)
p1 = plot(upperS, "Slow BB Upper Band", color=color.teal)
p2 = plot(lowerS, "Slow BB Lower Band", color=color.teal)
fill(p1, p2, title = "Slow BB Background", color=color.blue, transp=95)

//BOLL2
[middleF, upperF, lowerF] = bb(close, lengthF, 1)
p1F = plot(upperF, "Fast BB Upper Band", color=color.gray)
p2F = plot(lowerF, "Fast BB Lower Band", color=color.gray)
fill(p1F, p2F, title = "Fast BB Background", color=color.white, transp=95)


BUY = bar_index > 40 and (RSI > 50) and (close > upperF) and crossover(close, upperS)
SELL = bar_index > 40 and (RSI < 50) and (close < lowerF) and crossunder(close, lowerS) 

longexit=close < upperF
shortexit=close > lowerF

//Trading Inputs
i_strategyClose=input(true, title="Use Strategy Close Logic")
DPR=input(true, "Allow Direct Position Reverse")
reverse=input(false, "Reverse Trades")

// Entries
if reverse
    if not DPR
        strategy.entry("long", strategy.long, when=SELL and strategy.position_size == 0)
        strategy.entry("short", strategy.short, when=BUY and strategy.position_size == 0)
    else     
        strategy.entry("long", strategy.long, when=SELL)
        strategy.entry("short", strategy.short, when=BUY)
else
    if not DPR 
        strategy.entry("long", strategy.long, when=BUY and strategy.position_size == 0)
        strategy.entry("short", strategy.short, when=SELL and strategy.position_size == 0)
    else
        strategy.entry("long", strategy.long, when=BUY)
        strategy.entry("short", strategy.short, when=SELL)

if i_strategyClose
    strategy.close("long", when=longexit)
    strategy.close("short", when=shortexit)
    


SL= i_SLType == "Swing Lo/Hi" ? entry_LL_price : i_SLType == "ATR Stop" ? LongSL_ATR_price : LongStop
SSL= i_SLType == "Swing Lo/Hi" ? entry_HH_price : i_SLType == "ATR Stop" ? ShortSL_ATR_price : ShortStop
TP= i_SLType == "Swing Lo/Hi" ? tp : i_SLType == "ATR Stop" ? ATRtp : StratTP
STP= i_SLType == "Swing Lo/Hi" ? stp : i_SLType == "ATR Stop" ? ATRstp : StratSTP

//TrailingStop
dif=(valuewhen(strategy.position_size>0 and strategy.position_size[1]<=0, high,0))
 -strategy.position_avg_price
trailOffset     = strategy.position_avg_price - SL
var tstop = float(na)
if strategy.position_size > 0
    tstop := high- trailOffset - dif
    if tstop<tstop[1]
        tstop:=tstop[1]
else
    tstop := na
StrailOffset     = SSL - strategy.position_avg_price
var Ststop = float(na)
Sdif=strategy.position_avg_price-(valuewhen(strategy.position_size<0 
 and strategy.position_size[1]>=0, low,0))
if strategy.position_size < 0
    Ststop := low+ StrailOffset + Sdif
    if Ststop>Ststop[1]
        Ststop:=Ststop[1]
else
    Ststop := na

strategy.exit("TP & SL", "long", limit=TP, stop=TS? tstop : SL, when=i_SL)
strategy.exit("TP & SL", "short", limit=STP, stop=TS? Ststop : SSL, when=i_SL)

/////////////////////// PLOTS //////////////////////////////////////////////////


plot(i_SL and strategy.position_size > 0 and not TS ? SL : i_SL and strategy.position_size > 0 and TS ? tstop : na , title='SL', style=plot.style_cross, color=color.red)
plot(i_SL and strategy.position_size < 0 and not TS ? SSL : i_SL and strategy.position_size < 0 and TS ? Ststop : na , title='SSL', style=plot.style_cross, color=color.red)
plot(i_SL and strategy.position_size > 0 ? TP : na, title='TP', style=plot.style_cross, color=color.green)
plot(i_SL and strategy.position_size < 0 ? STP : na, title='STP', style=plot.style_cross, color=color.green)
// Draw price action setup arrows
plotshape(BUY ? 1 : na, style=shape.triangleup, location=location.belowbar, 
 color=color.green, title="Bullish Setup", size=size.auto)
plotshape(SELL ? 1 : na, style=shape.triangledown, location=location.abovebar, 
 color=color.red, title="Bearish Setup", size=size.auto)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-03. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

Build this with AgenKit

A spec is not a trading system. Paste this into your coding agent and AgenKit runs a specialist team — architecture, test-first build, risk gates, review — with paper trading on by default.

in Claude Code, Cursor, Codex & 4 more

/agenkit build a production-grade trading bot with a backtest engine, risk controls and paper trading by default from strategies/Double-Bollinger-Band-Breakout-Strategy.md

npx agenkit install engineering-kit in your project
Paste the command into your agent and approve each phase
Get tests, backtest, risk controls and a paper-trading switch

Get AgenKit How /agenkit works

Understand it first

Before you run this, read the lesson behind the idea and how to backtest it honestly. Specs like this one are the survivors of an unknown number of trials; deflate their results accordingly.