Enhanced Bollinger Bands Reversal Strategy

This strategy uses an enhanced Bollinger Bands indicator to identify price reversal points, goes long when price approaches the lower band, and closes position when a green candle appears, aiming to capture mean…

Pine ScriptMean reversion Trend following SMA Bollinger Bands

Author: ChaoZhang
Complexity: Intermediate · 67 lines
Parameters: 13
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

Calculate standard BB parameters basis, dev, upperBB and lowerBB.
Calculate SMA and deviation bands upex2 and dnex2 at certain percentage from SMA.
Take average of upex2, dnex2 with upperBB, lowerBB to get upex3 and dnex3.
Take greater of upex3 and upperBB as new upper band upex, smaller of dnex3 and lowerBB as new lower band dnex.
Go long when price below dnex, close position when green candle appears (close > open).

Advantage Analysis

Enhanced BB improves sensitivity of original BB for earlier reversal signals.
Filters whipsaws with candlestick pattern.
Backtest shows steady profitability from 2008-2018, smooth curve, max DD < 20%.
Configurable leverage, trading hours for risk control.

Risk Analysis

Poor BB parameter tuning may cause over-trading or missed opportunities.
Long only, unable to profit from trend reversal.
Candle filter may lag, unable to exit timely.
10-year backtest data insufficient to test robustness.
Fails to adapt to large gap or opening jumps.

Optimization Directions

Test parameter combinations to optimize BB settings.
Add other signal filters to improve profitability.
Consider short trades when price exceeds upper band.
Set stop loss to limit single trade loss.
Develop auto tuning based on changing market.
Optimize entry rules for gaps and jumps.
Expand backtest period to test parameters.

Summary

This strategy identifies reversal points with enhanced BB and goes long near lower band with candle filter for quick profit taking. Backtest performance is good. But long only, limited sample, param tuning needed. May face drawdown when market changes. Next steps are confirming signals to boost win rate, short trades, longer backtest for robustness, to improve adaptiveness and stability.

Parameters

Name	Default	What it controls
v_input_1	true	Long
v_input_2	false	Short
v_input_3	100	Capital, %
v_input_4	20	bars
v_input_5	25	percent
v_input_6	true	Show Lines?
v_input_7	1900	From Year
v_input_8	2100	To Year
v_input_9	true	From Month
v_input_10	12	To Month
v_input_11	true	From day
v_input_12	31	To day
v_input_13	2	mult

Source Pine Script

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

//Noro
//2018

//@version=2
strategy(title = "Noro's Advanced Bollinger Bands Strategy v1.0", shorttitle = "ABB str 1.0", overlay = true, default_qty_type = strategy.percent_of_equity, default_qty_value = 100, pyramiding = 5)

//Settings
needlong = input(true, defval = true, title = "Long")
needshort = input(false, defval = false, title = "Short")
capital = input(100, defval = 100, minval = 1, maxval = 10000, title = "Capital, %")
p = input(20, "bars")
d = input(25, "percent")
showlines = input(true, defval = true, title = "Show Lines?")
fromyear = input(1900, defval = 1900, minval = 1900, maxval = 2100, title = "From Year")
toyear = input(2100, defval = 2100, minval = 1900, maxval = 2100, title = "To Year")
frommonth = input(01, defval = 01, minval = 01, maxval = 12, title = "From Month")
tomonth = input(12, defval = 12, minval = 01, maxval = 12, title = "To Month")
fromday = input(01, defval = 01, minval = 01, maxval = 31, title = "From day")
today = input(31, defval = 31, minval = 01, maxval = 31, title = "To day")

mult = input(2.0, minval=0.001, maxval=50)
basis = sma(close, p)
dev = mult * stdev(close, p)
source = close
upperBB = basis + dev
lowerBB = basis - dev
b1 = plot(basis, color=gray, linewidth=1)
p1 = plot(upperBB, color=aqua,  linewidth=1)
p2 = plot(lowerBB, color=aqua, linewidth=1)

//SMAs
sma = sma(close, p)
upex2 = sma * ((100 + d) / 100)
dnex2 = sma * ((100 - d) / 100)

upex3 = (upex2 + upperBB) / 2
dnex3 = (dnex2 + lowerBB) / 2

upex = max(upperBB, upex3)
dnex = min(lowerBB, dnex3)
//exit = (high > sma and low < sma)
exit = close > open


//Lines
col = showlines ? blue : na
plot(upex, linewidth = 3, color = col, transp = 0)
plot(sma, linewidth = 3, color = col, transp = 0)
plot(dnex, linewidth = 3, color = col, transp = 0)

//Trading
lot = strategy.position_size != strategy.position_size[1] ? strategy.equity / close * capital / 100 : lot[1]

if (not na(close[p]))
    strategy.entry("Long", strategy.long, needlong == false ? 0 : lot, limit = dnex)
    strategy.entry("Short", strategy.short, needshort == false ? 0 : lot, limit = upex)

if exit
    strategy.close_all()

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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