DAKELAX XRPUSDT Bollinger Band Mean Reversion Strategy

DAKELAX-XRPUSDT is a trading bot strategy for XRPUSDT on Binance. It is a simple reverse to mean strategy using Bollinger Bands, and performs well in backtest on H1 timeframe from May to Aug 2019, as well as running…

Pine ScriptMean reversion Breakout Trend following EMA SMA Bollinger Bands

Author: ChaoZhang
Complexity: Starter · 81 lines
Parameters: 3
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

The strategy first calculates the 20-period SMA and upper/lower Bollinger Bands. The upper band is SMA + 1.5 standard deviation, and the lower band is SMA - 2.2 standard deviation. It then calculates the contraction rate of the bands. Bands are filled black if contraction > 1.3, yellow if < 0.1, else red.

When close price is below the lower band, it goes long with 20 coins. When close is above upper band, it closes all positions.

The strategy also calculates 7-period EMA fast line and 18-period EMA slow line. Crossover of fast line above slow line is buy signal, and crossover below is sell signal.

Advantage Analysis

Bollinger Bands and contraction rate intuitively identify trends and volatility
Combine with EMA crossover adds strength to signals
Good backtest results and relatively stable in live trading

Risk Analysis

High probability of failure when breakout after band contraction
Fixed amount buying without position sizing risks overtrading
Too many crossovers in ranging markets risks losses
Only considers daily factors, misses larger timeframe trends

Consider dynamic position sizing or stop loss to control risks. Optimize crossover strategy to avoid whipsaws in ranging markets. Add higher timeframe trend indicators to identify larger moves.

Optimization Directions

Adjust buy amount based on band width, less when contracted and more when expanded
Consider accumulating positions when contraction seen but signal not triggered yet
Add longer timeframe trend INDICATOR to determine overall direction, pause strategy when unclear
Incorporate stop loss to control risk, can set near recent lows of bands
Optimize crossover parameters like EMA periods to avoid getting trapped

Summary

DAKELAX-XRPUSDT is a trading bot strategy using Bollinger Band contraction with EMA crossover. It is intuitive and has good backtest results but contains some risks. These can be reduced through position sizing, stopping strategy, adding stop loss and optimizing crossover logic. Overall it provides a clear example of a Bollinger Band strategy, but requires pair-specific optimization for stable live profits.

Parameters

Name	Default	What it controls
v_input_1	20	buyAmount
v_input_2	20	len2
v_input_3_close	0	src2: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4

Source Pine Script

/*backtest
start: 2022-10-26 00:00:00
end: 2023-11-01 00:00:00
period: 1d
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=3
//study(title="Tradebotler DAKELAX Binance:XRPUSDT Study-strategy", overlay=true)
strategy(title="Tradebotler DAKELAX Binance:XRPUSDT Strategy", overlay=true)

buyAmount = input(20, minval=1)

// SMA20
len2 = input(20, minval=1)
src2 = input(close)
out2 = sma(src2, len2)

// BB contraction value (medium tight)
contraction_value = 1.3
// BB contraction value (very tight)
contraction_value2 = 0.1

// 2xSTDEV BB calculation
dev = stdev(src2, len2)
upper_BB = out2  + 1.5*dev
lower_BB = out2  - 2.2*dev
x1 = plot(upper_BB, color=blue, linewidth = 2)
x2 = plot(lower_BB, color=blue, linewidth = 2)

contraction = (upper_BB-lower_BB)/out2

//fills the BBands according to the contraction value (threshold)

// Calculate values
fastMA  = ema(close, 7)
slowMA  = ema(close, 18)

// Determine alert setups
crossUp   = crossover(fastMA, slowMA)
crossDown = crossunder(fastMA, slowMA)

buySignal   = (crossUp or crossUp[1]) and (low > slowMA)
shortSignal = (crossDown or crossDown[1]) and (high < slowMA)

// Highlight alerts on the chart
bgColour =
     (buySignal and barstate.isrealtime) ? green :
     (shortSignal and barstate.isrealtime) ? red :
     na

signalBuy = (buySignal ) ? true : false
signalSell = (shortSignal ) ? true : false

test = true

test := not test[1]

closesBelowLowerBB = close < lower_BB
closesAboveUpperBB = close > upper_BB

tmptext = "blah"

// Plot values
plot(series=fastMA, color=teal)
plot(series=slowMA, color=orange)

plot(out2, color=black, linewidth = 1)
fill(x1, x2, color = contraction > contraction_value ? black : contraction < contraction_value2 ? yellow: red)

isInRed = contraction < contraction_value and contraction >= contraction_value2
isInYellow = contraction < contraction_value and contraction < contraction_value2

if ( closesBelowLowerBB )
    strategy.order('Buy', strategy.long, buyAmount)

if ( closesAboveUpperBB )
    strategy.close_all()

Published by ChaoZhang on the FMZ strategy square · last modified 2023-11-02. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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