Mean Reversion Trading Strategy Based on Bollinger Bands and Golden Ratio

This strategy uses the golden ratio line of Bollinger Bands combined with moving average formations to trade mean reversions. When the price touches the golden ratio line, it is considered a buy signal to take…

Pine ScriptMean reversion Breakout Trend following MACD EMA SMA Bollinger Bands ATR Fibonacci

Author: ChaoZhang
Complexity: Starter · 59 lines
Parameters: 4
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

Calculate Bollinger Bands middle band, upper band and golden ratio lower band

Middle band: vwma of n periods
Upper band: Middle band + k * n period standard deviation
Golden ratio lower band: Middle band - 0.618 * n period standard deviation

Judge formations

50-day MA above 200-day MA, indicates uptrend
Price touches or below golden ratio lower band, as buy signal

Exit

When price breaks above BB upper band, price is considered to have moved away from lower band, close position

Stop loss

Set fixed percentage stop loss, e.g. 5%

Advantages

Using vwma instead of sma for BB middle line better reflects price movement
Golden ratio is important support/resistance, provides basis for reversion
MA in uptrend ensures overall trend is up
Fixed stop loss controls loss for each trade

Risks

Golden ratio line is not guaranteed support, price may break through
Fixed stop loss may be arbitrary, should consider adjusting based on volatility
MA uptrend may be false breakout, should check more indicators
Unsure of reversion length, need reasonable profit taking exit

Enhancement

Test different combinations of parameters like BB period, SD multiplier, fixed stop loss percentage etc.
Add more indicators to determine market trend and reversion probability, e.g. MACD, KD etc.
Consider dynamic stops, such as ATR or trailing stops
Optimize profit taking like moving profit stop, partial profit taking etc.

Summary

This strategy trades mean reversions using BB golden ratio line, with clear logic, simple parameters, and controllable drawdown. But also has risks, requires further testing and optimization, adding more technical indicators for trend and better stops/exits before actual use. Overall provides idea of using golden ratio in quant trading, worth exploring further.

Parameters

Name	Default	What it controls
v_input_1	50	BB Length
v_input_2_hlc3	0	Source: hlc3 \| high \| low \| open \| hl2 \| close \| hlcc4 \| ohlc4
v_input_3	1.5	multplier
v_input_4	5	Stop Loss

Source Pine Script

/*backtest
start: 2023-10-01 00:00:00
end: 2023-10-31 23:59:59
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/
// © mohanee

//@version=4

strategy(title="Bollinger Band with Fib Golden Ratio (0.618)",  shorttitle="Bollinger Band with Fib Golden Ratio" , overlay=true, pyramiding=1,     default_qty_type=strategy.percent_of_equity,  default_qty_value=20, initial_capital=10000, currency=currency.USD)  

length = input(50,title="BB Length" , minval=1)
src1 = input(hlc3, title="Source")
//mult1 = input(1.33, minval=0.001, maxval=50)
mult = input(1.5,title="multplier", minval=0.001, maxval=50)

stopLoss=input(5,title="Stop Loss",minval=1)

basis = vwma(src1, length)
dev = mult * stdev(src1, length)

//dev3 = mult3 * stdev(src, length)

upper_618= basis + (0.618*dev)
lower_618= basis - (0.618*dev)

//lower_618_dev3= basis - (0.618*dev3)



plot_upper618= plot(upper_618, color=color.purple, linewidth=2, title="0.618")
plot(basis, color=color.purple,style=plot.style_circles,  linewidth=2)

plot_lower618= plot(lower_618, color=color.purple, linewidth=2, title="0.618 entry")
//plot_lower618_dev3= plot(lower_618_dev3, color=color.red, linewidth=1, title="0.618 stop")

//plot_lower618= plot(lower_618, color=color.purple, linewidth=1, title="0.618 entry")

ema200=ema(close,200)
ema50=ema(close,50)

plot (ema200, title="ema200", color=color.orange, linewidth=2)
plot (ema50, title="ema50", color=color.blue , linewidth=2)


longCondition= ema50 > ema200

strategy.entry(id="BB_Fib618", long=true, when = longCondition and ( close < lower_618  or  low <= lower_618)  )

strategy.close(id="BB_Fib618",  comment="points="+tostring(close - strategy.position_avg_price,  "###.##") , when = strategy.position_size >= 1  and crossover(close,upper_618 )) 

//stoploss exit
stopLossVal = strategy.position_size>=1 ?  strategy.position_avg_price * ( 1 - (stopLoss/100) ) : 0.00
strategy.close(id="BB_Fib618", comment="SL="+tostring(close - strategy.position_avg_price,  "###.##"), when=abs(strategy.position_size)>=1 and close < stopLossVal ) //and close > strategy.position_avg_price )

Published by ChaoZhang on the FMZ strategy square · last modified 2023-11-16. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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