Bollinger Band Momentum Breakout Trading Strategy

Pine ScriptBreakout Momentum Machine learning RSI SMA Bollinger Bands Volume Pivots / S&R

Author: ChaoZhang
Complexity: Intermediate · 102 lines
Parameters: 17
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy combines Bollinger Band indicator and volume indicators to identify strong momentum breakout opportunities above Bollinger upper band when trading volume is high, and enters long positions. It also uses moving average indicators to determine trend direction and reduce the risk of holding dead positions.

Strategy Logic

Use Bollinger Band indicator to determine if price breaks out above the upper band.
Use trading volume indicators to determine if current volume is significantly higher than past period average.
Enter long position when trading volume is high and price breaks out above Bollinger upper band.
Use moving average indicators to determine short term and medium term trend to cut loss in time.

This strategy mainly considers three factors: price level, momentum and trend. When price breaks out the Bollinger upper band into the buy zone, surge in trading volume indicates strong momentum and capital inflow. This is the right timing to enter long position. Then it uses moving averages to determine market trend to avoid holding dead positions. By combining price action, momentum and risk control, it aims to capture profits from strong trends.

Advantages

Accurate signals, avoids false breakout. Combining volume filter, it only buys on real strong momentum, reducing risk.
Able to cut loss in time via moving average trend determination, reducing holding loss.
Implemented quantitative strategy combining multiple indicators for decision making. Flexible parameters tuning for different products and timeframes.
Clear code structures, easy to read and maintain. Modular design of indicators calculation, signal generation and position management.

Risks

Bollinger Bands could fail during extreme price swings, missing signals or generating false signals.
No profits when overall trading volume is low. Buy signals may not be profitable without enough trading volume.
Moving averages trend determination could also fail, unable to fully ensure effective stop loss.
Improper parameter tuning also affects strategy profitability. For example, trading time window set too short may miss trend reversal.

Optimization Directions

Add more technical indicators for better trend and support/resistance analysis, improving stop loss, e.g. candlestick patterns, channels, key support levels.
Add machine learning models to judge real breakout possibilities, reducing false signals. e.g. LSTM deep learning models.
Optimize capital management strategies like dynamic position sizing, trailing stop loss to reduce single trade loss impact.
Test more products and timeframes, adjust parameters like Bollinger Bands, volume window to improve strategy robustness.

Conclusion

This strategy integrates Bollinger Band and trading volume indicators to identify strong momentum buying opportunities, with moving averages ensuring effective stop loss. Compared to single indicator strategies, it has higher accuracy and risk control capabilities. With modular design, trend filters and stop loss mechanisms, it forms an easy-to-optimize momentum breakout trading strategy.

Parameters

Name	Default	What it controls
v_input_1	true	length1
v_input_2	3	length3
v_input_3	7	length7
v_input_4	9	length9
v_input_5	14	length14
v_input_6	20	length20
v_input_7	60	length60
v_input_8	120	length120
v_input_9	50	Daily MA length
v_input_10	10	Weekly MA length
v_input_11	20	length
v_input_12_close	0	Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_13	2	StdDev
v_input_14	1.5	exp
v_input_15	true	exp1
v_input_16	2.5	exp2
v_input_17	false	Offset

Source Pine Script

/*backtest
start: 2024-01-05 00:00:00
end: 2024-02-04 00:00:00
period: 1h
basePeriod: 15m
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/
// © KAIST291

//@version=4
initial_capital=1000
strategy("prototype", overlay=true)
length1=input(1)
length3=input(3)
length7=input(7)
length9=input(9)
length14=input(14)
length20=input(20)
length60=input(60)
length120=input(120)
ma1= sma(close,length1)
ma3= sma(close,length3)
ma7= sma(close,length7)
ma9= sma(close,length9)
ma14=sma(close,length14)
ma20=sma(close,length20)
ma60=sma(close,length60)
ma120=sma(close,length120)
rsi=rsi(close,14)
// BUYING VOLUME AND SELLING VOLUME //
BV = iff( (high==low), 0, volume*(close-low)/(high-low))
SV = iff( (high==low), 0, volume*(high-close)/(high-low))
vol = iff(volume > 0, volume, 1)
dailyLength = input(title = "Daily MA length", type = input.integer, defval = 50, minval = 1, maxval = 100)
weeklyLength = input(title = "Weekly MA length", type = input.integer, defval = 10, minval = 1, maxval = 100)
//-----------------------------------------------------------
Davgvol = sma(volume, dailyLength)
Wavgvol = sma(volume, weeklyLength)
//-----------------------------------------------------------
length = input(20, minval=1)
src = input(close, title="Source")
mult = input(2.0, minval=0.001, maxval=50, title="StdDev")
mult2= input(1.5, minval=0.001, maxval=50, title="exp")
mult3= input(1.0, minval=0.001, maxval=50, title="exp1")
mult4= input(2.5, minval=0.001, maxval=50, title="exp2")
basis = sma(src, length)
dev = mult * stdev(src, length)
upper = basis + dev
lower = basis - dev
dev2= mult2 * stdev(src, length)
Supper= basis + dev2
Slower= basis - dev2
dev3= mult3 * stdev(src, length)
upper1= basis + dev3
lower1= basis - dev3
dev4= mult4 * stdev(src, length)
upper2=basis + dev4
lower2=basis - dev4
offset = input(0, "Offset", type = input.integer, minval = -500, maxval = 500)
plot(basis, "Basis", color=#FF6D00, offset = offset)
p1 = plot(upper, "Upper", color=#2962FF, offset = offset)
p2 = plot(lower, "Lower", color=#2962FF, offset = offset)
fill(p1, p2, title = "Background", color=color.rgb(33, 150, 243, 95))
//----------------------------------------------------
exit=(close-strategy.position_avg_price / strategy.position_avg_price*100)
bull=( BV>SV and BV>Davgvol)
bull2=(BV>SV and BV>Davgvol)
bux =(close>Supper and close>Slower and volume<Davgvol)
bear=(SV>BV and SV>Davgvol)
con=(BV>Wavgvol and rsi>80)
imInATrade = strategy.position_size != 0
highestPriceAfterEntry = valuewhen(imInATrade, high, 0)
// STRATEGY LONG //
if (bull and close>upper1 and close>Supper and high>upper and rsi<80)
    strategy.entry("Long",strategy.long)

if (strategy.position_avg_price*1.02<close)
    strategy.close("Long")
else if (low<ma9 and strategy.position_avg_price<close)
    strategy.close("Long")
else if (ma20>close and strategy.position_avg_price<close )
    strategy.close("Long")
else if (rsi>80 and strategy.position_avg_price<close)
    strategy.close("Long")
else if (strategy.openprofit < strategy.position_avg_price*0.9-close)
    strategy.close("Long")
else if (high<upper and strategy.position_avg_price<close)
    strategy.close("Long")
//////////////////////////////////////////////////////////////////////////////////

//////////////////////////////////////////////////////////////////////////////////
strategy.entry("Short",strategy.short,when=low<ma20 and low<lower1 and close<Slower and crossunder(ma60,ma120))

if (close<strategy.position_avg_price*0.98)
    strategy.close("Short")

else if (rsi<20)
    strategy.close("Short")

Published by ChaoZhang on the FMZ strategy square · last modified 2024-02-05. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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