Trading Strategy of Short Selling When Bollinger Band Crosses Below Price with RSI Callback

This strategy utilizes Bollinger Bands to determine if price has entered the overbought area and combines RSI indicator to identify callback opportunities. It goes short when a death cross is formed in the overbought…

Pine ScriptScalping Breakout Mean reversion RSI SMA Bollinger Bands

Author: ChaoZhang
Complexity: Intermediate · 82 lines
Parameters: 7
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Trading Principles

The strategy is based on the following principles:

When close price crosses above Bollinger Upper Band, it indicates the asset has entered overbought territory and a callback is likely
RSI indicator effectively determines overbought/oversold levels. RSI > 70 is considered overbought
Go short when close price crosses below Upper Band
Close position when RSI pulls back from overbought zone or stop loss is triggered

Advantage Analysis

Advantages of this strategy:

Bollinger Bands determine overbought/oversold levels accurately, improving trade success rate
RSI filters out false breakout signals, avoiding unnecessary losses
High risk to reward ratio obtained by effectively controlling risk

Risk Analysis

Risks in this strategy:

Price may continue going up after breaking above Upper Band, leading to further losses
Failure of timely RSI pullback results in loss amplification
Unidirectional short position leaves no room for trading in consolidation

Risks can be minimized by:

Adjusting stop loss properly for timely stop out
Adding indicators to confirm RSI callback
Using moving averages to determine consolidation

Optimization Directions

This strategy can be improved on:

Optimizing Bollinger parameters for more assets
Fine tuning RSI parameters for better signals
Adding more indicators to pinpoint trend reversal points
Incorporating long trade logic
Implement dynamic stop loss based on volatility

Conclusion

In summary, this is a typical overbought quick short scalping strategy. It capitalizes on Bollinger Bands for trade entries and RSI to filter signals. Risk is managed through prudent stop loss placement. Further enhancements can come from parameter tuning, adding indicators, expanding trade logic etc.

Parameters

Name	Default	What it controls
v_input_1	true	Show Date Range
v_input_int_1	20	length
v_input_2_close	0	Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_float_1	2	StdDev
v_input_int_2	false	Offset
v_input_float_2	3	Trail Long Loss (%)
v_input_float_3	3	Trail Short Loss (%)

Source Pine Script

/*backtest
start: 2023-11-01 00:00:00
end: 2023-11-30 23:59:59
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © Coinrule


strategy("Bollinger Band Below Price with RSI",
         overlay=true,
         initial_capital=1000,
         process_orders_on_close=true,
         default_qty_type=strategy.percent_of_equity,
         default_qty_value=70,
         commission_type=strategy.commission.percent,
         commission_value=0.1)

showDate = input(defval=true, title='Show Date Range')
timePeriod = time >= timestamp(syminfo.timezone, 2022, 1, 1, 0, 0)
notInTrade = strategy.position_size <= 0

//Bollinger Bands Indicator
length = input.int(20, minval=1)
src = input(close, title="Source")
mult = input.float(2.0, minval=0.001, maxval=50, title="StdDev")
basis = ta.sma(src, length)
dev = mult * ta.stdev(src, length)
upper = basis + dev
lower = basis - dev
offset = input.int(0, "Offset", minval = -500, maxval = 500)
plot(basis, "Basis", color=#FF6D00, offset = offset)
p1 = plot(upper, "Upper", color=#2962FF, offset = offset)
p2 = plot(lower, "Lower", color=#2962FF, offset = offset)
fill(p1, p2, title = "Background", color=color.rgb(33, 150, 243, 95))

// RSI inputs and calculations
lengthRSI = 14
RSI = ta.rsi(close, lengthRSI)



// Configure trail stop level with input options
longTrailPerc = input.float(title='Trail Long Loss (%)', minval=0.0, step=0.1, defval=3) * 0.01
shortTrailPerc = input.float(title='Trail Short Loss (%)', minval=0.0, step=0.1, defval=3) * 0.01

// Determine trail stop loss prices
//longStopPrice = 0.0
shortStopPrice = 0.0

//longStopPrice := if strategy.position_size > 0
    //stopValue = close * (1 - longTrailPerc)
    //math.max(stopValue, longStopPrice[1])
//else
    //0

shortStopPrice := if strategy.position_size < 0
    stopValue = close * (1 + shortTrailPerc)
    math.min(stopValue, shortStopPrice[1])
else
    999999


//Entry and Exit
strategy.entry(id="short", direction=strategy.short, when=ta.crossover(close, upper) and RSI < 70 and timePeriod and notInTrade)

if (ta.crossover(upper, close) and RSI > 70 and timePeriod)
    strategy.exit(id='close', limit = shortStopPrice)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-12-26. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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