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Strategy vault / Breakout

Short term Trading Strategy Based on Bollinger Bands

This strategy conducts short-term trading based on the Bollinger Bands indicator, utilizing the upper and lower rails of Bollinger Bands to provide breakthrough buying and selling signals. It belongs to a simple…

Pine ScriptBreakoutMean reversionMomentumSMABollinger Bands
Author
ChaoZhang
Complexity
Starter · 42 lines
Parameters
2
Backtest bar
1h · intraday
Tested on
BTC/USDT · futures
Jump to codeView in vaultOriginal on FMZ

IMG

Overview

This strategy conducts short-term trading based on the Bollinger Bands indicator, utilizing the upper and lower rails of Bollinger Bands to provide breakthrough buying and selling signals. It belongs to a simple momentum tracking strategy. It is mainly suitable for short-term tracking and chasing price trends.

Strategy Principle

The strategy relies mainly on the Bollinger Bands indicator. Bollinger Bands includes middle rail, upper rail and lower rail. The middle rail represents the N-day simple moving average of the closing price. The upper rail is calculated by the middle rail plus 2 times the standard deviation. The lower rail is calculated by the middle rail minus 2 times the standard deviation. When the price breaks through the lower rail upwards, a buy signal is generated. When the price breaks through the upper rail downwards, a sell signal is generated.

The main trading logic of this strategy is:

  1. Use the sma() function to calculate the N-day (default 20-day) simple moving average of the closing price as the middle rail of Bollinger Bands

  2. Use the stdev() function to calculate the N-day (default 20-day) standard deviation based on the closing price

  3. The upper and lower rails of Bollinger Bands are composed of the middle rail ± 2 times the standard deviation

  4. When the closing price breaks through the lower rail upward, a buy signal is generated

  5. When the closing price breaks through the upper rail downward, a sell signal is generated

  6. Use functions like plotshape to mark buy and sell signals on the candlestick chart

Advantages of the Strategy

  1. The strategy logic is simple and easy to understand and use

  2. Less indicator parameters, easy to optimize and adjust

  3. Can effectively track market trends and chase momentum

  4. Relatively small pullback risk

Risks of the Strategy

  1. Prone to missing reversal risks

  2. Improper parameter settings may lead to excessively high trading frequency

  3. Breakthrough judgements of upper and lower rails are quite sensitive to market fluctuations

  4. The effect is highly related to parameter settings. Careful testing and optimization is needed.

Directions for Strategy Optimization

  1. Adjust parameters of Bollinger Bands, optimize moving average period and times of standard deviation

  2. Add filters with other indicators to avoid wrong trades

  3. Add stop loss mechanisms to control single loss

  4. Different products and cycles need different parameter settings. Separate testing is needed.

Summary

Overall, this is a very typical and practical short-term momentum tracking strategy. It can grasp market trends through a simple indicator framework and suits short-term operations. But there are also some disadvantages like sensitivity to parameters, insufficient signal filtering, etc. Further optimizing indicator parameters or adding other auxiliary indicators can improve the stability and profitability of the strategy.

Parameters

NameDefaultWhat it controls
v_input_120Bollinger Bands Length
v_input_22Multiplier

Source Pine Script

/*backtest
start: 2024-01-01 00:00:00
end: 2024-01-31 23:59:59
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
strategy("arasmuz2.0", overlay=true)

// Bollinger Bands Parametreleri
length = input(20, title="Bollinger Bands Length")
mult = input(2.0, title="Multiplier")

// Bollinger Bands Hesaplamaları
basis = sma(close, length)
upper_band = basis + mult * stdev(close, length)
lower_band = basis - mult * stdev(close, length)

// Long (Alım) Koşulları
longCondition = crossover(close, lower_band)

// Short (Satım) Koşulları
shortCondition = crossunder(close, upper_band)

// Long (Alım) Giriş
strategy.entry("Long", strategy.long, when=longCondition)

// Short (Satım) Giriş
strategy.entry("Short", strategy.short, when=shortCondition)

// Al sinyalini mumun altına koy
plotshape(series=longCondition, title="Buy Signal", color=color.green, style=shape.triangleup, location=location.belowbar, size=size.small)

// Sat sinyalini mumun üstüne koy
plotshape(series=shortCondition, title="Sell Signal", color=color.red, style=shape.triangledown, location=location.abovebar, size=size.small)

// Bollinger Bands'ı Grafik Üzerinde Görüntüle
plot(upper_band, color=color.red, title="Upper Bollinger Band")
plot(lower_band, color=color.green, title="Lower Bollinger Band")

Published by ChaoZhang on the FMZ strategy square · last modified 2024-02-29. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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