Momentum Oscillation Trading Strategy

Pine ScriptMomentum Grid Machine learning SMA Bollinger Bands

Author: ChaoZhang
Complexity: Starter · 46 lines
Parameters: 4
Backtest bar: 1m · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy is based on the Bollinger Bands indicator, combined with momentum indicators to implement a combination trading strategy of Bollinger Bands reversion and momentum breakout. It goes long when the price breaks through the middle line of the Bollinger Bands from below and goes short when the price breaks through the middle line from above. It also tracks stop loss and take profit based on entry price to close positions when target risk-reward ratio is met.

Strategy Logic

The strategy uses Bollinger Bands middle line sma as the moving average indicator, and dynamically adjusts the band width through param mult*stdev. When price breaks through the middle line from below, it indicates upward momentum is gained and thus goes long. When price breaks down through the middle line from above, it shows downward momentum is gained and thus goes short. After entering long/short positions, stop loss and take profit parameters are set to track profits and control risks.

Specifically, Bollinger Bands are calculated with two parameters - length and mult. Length determines the period of the middle line and mult decides the band width. enterLong and enterShort judge the breakout timing. exitLong and exitShort calculate stop loss and take profit prices based on entry price and target percentage.

Advantages

This strategy combines reversion to the mean and momentum, which enables it to capture major trends early on. Compared to simply tracking moving averages, the added momentum judgment based on Bollinger Bands width can filter out some false breakouts. Stop loss and take profit are set directly based on entry price without manual intervention.

Risks

Lagging in Bollinger Bands fitting prices, may miss some moves
Stop loss set too wide may increase loss risks
Short signals in bull market may not turn out well

Parameters like periods, band width and stop loss range can be optimized to make the strategy adaptable to different market conditions.

Enhancement

Add trading volume or volatility to avoid low volume false breakouts
Param grid search to optimize periods, width coefficient and stop loss percentage
Go only long or short based on market regime
Add Machine Learning model to determine trend direction

Conclusion

This strategy combines the strengths of Bollinger Bands reversion and momentum, which enables it to capture some trends early on. Through parameter tuning it can adapt to different market stages. The direct stop loss/take profit calculation reduces manual intervention. There is still room for improvement, e.g. incorporating more auxiliary indicators. These will be incrementally enhanced in further research and optimization.

Parameters

Name	Default	What it controls
v_input_1	20	Length
v_input_2	2	Multiplier
v_input_3	0.5	Target Percent
v_input_4	95	Stop Loss Percent

Source Pine Script

/*backtest
start: 2023-11-13 00:00:00
end: 2023-11-20 00:00:00
period: 1m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=4
strategy("BURATINO", overlay=true)

// Входные параметры
length = input(20, minval=1, title="Length")
mult = input(2.0, minval=0.1, maxval=5, title="Multiplier")
target_percent = input(0.5, minval=0.1, title="Target Percent")
stop_loss_percent = input(95, minval=0.1, title="Stop Loss Percent")

// Расчет полос Боллинджера
basis = sma(close, length)
dev = mult * stdev(close, length)
upper = basis + dev
lower = basis - dev

// Переворот снизу вверх через среднюю линию Боллинджера для открытия лонга
enterLong = cross(close, basis) and close[1] < basis[1]

// Переворот сверху вниз через среднюю линию Боллинджера для открытия шорта
enterShort = cross(basis, close) and close[1] > basis[1]

// Закрытие лонга после роста цены на указанный процент или падения на указанный процент
exitLong = close >= strategy.position_avg_price * (1 + (target_percent / 100)) or close <= strategy.position_avg_price * (1 - (stop_loss_percent / 100))

// Закрытие шорта после падения цены на указанный процент или роста на указанный процент
exitShort = close <= strategy.position_avg_price * (1 - (target_percent / 100)) or close >= strategy.position_avg_price * (1 + (stop_loss_percent / 100))

// Управление позициями и ограничениями на открытие противоположных позиций
strategy.entry("Long", strategy.long, when = enterLong and strategy.position_size == 0)
strategy.entry("Short", strategy.short, when = enterShort and strategy.position_size == 0)

strategy.close("Long", when = exitLong)
strategy.close("Short", when = exitShort)

// Визуализация полос Боллинджера
plot(basis, color=color.blue, title="Basis")
plot(upper, color=color.red, title="Upper")
plot(lower, color=color.green, title="Lower")

Published by ChaoZhang on the FMZ strategy square · last modified 2023-11-21. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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