Bollinger Bands and RSI Combination Strategy 440426

This strategy combines Bollinger Bands and Relative Strength Index (RSI) to identify opportunities when Bollinger Bands are squeezing and RSI is rising, with trailing stop loss to control risks.

Pine ScriptBreakout Mean reversion Trend following RSI EMA SMA Bollinger Bands ATR

Author: ChaoZhang
Complexity: Intermediate · 116 lines
Parameters: 5
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This strategy combines Bollinger Bands and Relative Strength Index (RSI) to identify opportunities when Bollinger Bands are squeezing and RSI is rising, with trailing stop loss to control risks.

Strategy Logic

The core logic of this strategy is to identify Bollinger Bands squeeze and predict price breakout when RSI is in uptrend. Specifically, when 20-period BB middle band standard deviation is less than ATR*2, we determine BB squeeze happening; meanwhile, if both 10 and 14 period RSI are rising, we predict prices may break above BB upper band soon and go long.

After entering the market, we use ATR safety distance + adaptive stop loss to lock profit and manage risks. Positions will be closed when price hits stop loss or RSI becomes overbought (14-period RSI above 70 and 10-period RSI exceeds 14).

Advantage Analysis

The biggest advantage of this strategy is to identify consolidation period with BB squeeze and predict breakout direction with RSI. Also, using adaptive stop loss based on market volatility rather than fixed stop loss can better lock profit while controlling risk.

Risk Analysis

The major risk of this strategy is misidentification of BB squeeze and RSI uptrend, which may lead to false breakout. Besides, adaptive stop loss may fail to close positions timely during high volatility. Improving stop loss methods like curve stop loss can mitigate this risk.

Optimization Guidelines

This strategy can be further optimized in the following aspects:

Improve BB parameters to identify squeeze more accurately
Test different values for RSI periods
Examine other stop loss techniques like curve SL or back-looking SL
Adjust parameters based on symbol characteristics

Conclusion

This strategy leverages the complementarity of BB and RSI to achieve good risk-adjusted returns. Further optimizations on aspects like stop loss and parameter tuning can make it fit better for different trading instruments.

Parameters

Name	Default	What it controls
v_input_1	timestamp(01 Apr 2016 13:30 +0000)	Backtest Start Time
v_input_2	false	Define backtest end-time (If false, will test up to most recent candle)
v_input_3	timestamp(01 May 2021 19:30 +0000)	Backtest End Time (if checked above)
v_input_4	true	No. of candles to lookback when determining ATR is decreasing
v_input_5	70	[Exit] RSI(14) value considered as overbought

Source Pine Script

/*backtest
start: 2023-12-01 00:00:00
end: 2023-12-31 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/
// © DojiEmoji
// 

//@version=4
strategy("[KL] BOLL + RSI Strategy",overlay=true,pyramiding=1)

// Timeframe {
backtest_timeframe_start = input(defval = timestamp("01 Apr 2016 13:30 +0000"), title = "Backtest Start Time", type = input.time)
USE_ENDTIME = input(false,title="Define backtest end-time (If false, will test up to most recent candle)")
backtest_timeframe_end = input(defval = timestamp("01 May 2021 19:30 +0000"), title = "Backtest End Time (if checked above)", type = input.time)
within_timeframe = true
// }

// Bollinger bands (sdv=2, len=20) {
BOLL_length = 20, BOLL_src = close, SMA20 = sma(BOLL_src, BOLL_length), BOLL_sDEV_x2 = 2 * stdev(BOLL_src, BOLL_length)
BOLL_upper = SMA20 + BOLL_sDEV_x2, BOLL_lower = SMA20 - BOLL_sDEV_x2
plot(SMA20, "Basis", color=#872323, offset = 0)
BOLL_p1 = plot(BOLL_upper, "BOLL Upper", color=color.navy, offset = 0, transp=50)
BOLL_p2 = plot(BOLL_lower, "BOLL Lower", color=color.navy, offset = 0, transp=50)
fill(BOLL_p1, BOLL_p2, title = "Background", color=#198787, transp=85)
// }

// Volatility Indicators {
ATR_x2 = atr(BOLL_length) * 2 // multiplier aligns with BOLL
avg_atr = sma(ATR_x2, input(1,title="No. of candles to lookback when determining ATR is decreasing"))
plot(SMA20+ATR_x2, "SMA20 + ATR_x2", color=color.gray, offset = 0, transp=50)
plot(SMA20-ATR_x2, "SMA20 - ATR_x2", color=color.gray, offset = 0, transp=50)
plotchar(ATR_x2, "ATR_x2", "", location = location.bottom)
//}

// Trailing stop loss {
TSL_source = low
var entry_price = float(0), var stop_loss_price = float(0)

trail_profit_line_color = color.green
if strategy.position_size == 0 or not within_timeframe
    trail_profit_line_color := color.black
    stop_loss_price := TSL_source - ATR_x2
else if strategy.position_size > 0
    stop_loss_price := max(stop_loss_price, TSL_source - ATR_x2)
plot(stop_loss_price, color=trail_profit_line_color)

if strategy.position_size > 0 and stop_loss_price > stop_loss_price[1]
	alert("Stop loss limit raised", alert.freq_once_per_bar)

// } end of Trailing stop loss

//Buy setup - Long positions {
is_squeezing = ATR_x2 > BOLL_sDEV_x2
if is_squeezing and within_timeframe and not is_squeezing[1]
	alert("BOLL bands are squeezing", alert.freq_once_per_bar)
else if not is_squeezing and within_timeframe and is_squeezing[1]
	alert("BOLL bands stopped squeezing", alert.freq_once_per_bar)

ema_trend = ema(close, 20)

concat(a, b) =>
	concat = a
	if a != ""
		concat := concat + ", "
	concat := concat + b
	concat
// }

// Sell setup - Long position {
rsi_10 = rsi(close, 10), rsi_14 = rsi(close, 14)
overbought = rsi_14 > input(70,title="[Exit] RSI(14) value considered as overbought") and rsi_10 > rsi_14
// } end of Sell setup - Long position

// MAIN: {
if within_timeframe
	entry_msg = ""
	exit_msg = ""

    // ENTRY {
	conf_count = 0	
    volat_decr = avg_atr <= avg_atr[1]
	rsi_upslope = rsi_10 > rsi_10[1] and rsi_14 > rsi_14[1]

	if volat_decr and rsi_upslope and is_squeezing and strategy.position_size == 0
		strategy.entry("Long",strategy.long, comment=entry_msg)
		entry_price := close
		stop_loss_price := TSL_source - ATR_x2
	// }

    // EXIT	{
	if strategy.position_size > 0
		bExit = false
		if close <= entry_price and TSL_source <= stop_loss_price
            exit_msg := concat(exit_msg, "stop loss [TSL]")
			bExit := true
        else if close > entry_price and TSL_source <= stop_loss_price
            exit_msg := concat(exit_msg, "take profit [TSL]")
            bExit := true
		else if overbought
			exit_msg := concat(exit_msg, "overbought")
			bExit := true

        strategy.close("Long", when=bExit, comment=exit_msg)
	// }
// }

// CLEAN UP:
if strategy.position_size == 0 and not is_squeezing
	entry_price := 0
	stop_loss_price := float(0)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-30. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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