Two-stage Stop Loss Strategy

Author: ChaoZhang, Date: 2023-10-25 18:11:30
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Overview

The main idea of this strategy is to set two take profit targets and move the stop loss to entry price after the first target is reached to avoid stop loss hunting.

Strategy Logic

This strategy enters trades based on Bollinger Bands and Stochastic indicators. It goes short when price exceeds the Bollinger upper band and goes long when Stochastic shows oversold.

Specifically, the entry logic is:

  1. Enter long when close is below Bollinger lower band and Stochastic K crosses below D.

  2. Enter short when close is above Bollinger upper band and Stochastic K crosses above D.

The strategy sets two take profit targets, TP1 fixed at 200 points and TP2 fixed at 500 points.

When price moves and TP1 is triggered, the strategy will move stop loss to entry price. This locks in profit from first stage and prevents stop loss hunting.

The strategy closes all positions when TP2 or stop loss is triggered.

Advantage Analysis

The biggest advantage of this two-stage stop loss approach is it allows locking in profits while preventing stop loss hunting. By moving stop loss to entry price, it reduces the chance of stop loss hunting and protects profits.

Another advantage is the combination of Bollinger Bands to gauge volatility range and Stochastic for overbought/oversold makes for more accurate entries.

Risk Analysis

Main risks stem from potential false signals from Bollinger Bands and Stochastic indicators. Incorrect Bollinger range can lead to missing entries or bad signals. Stochastic false breakouts also cause wrong entries.

There is also risk of stop loss being hunted again after moving to entry price. V-shaped reversals can trigger stop loss a second time.

These risks can be reduced by optimizing parameters for both indicators and increasing distance between stop losses.

Optimization Directions

Further optimizations for this strategy:

  1. Test different parameter combinations to find optimal Bollinger and Stochastic parameters.

  2. Test different profit/loss targets to find ideal configurations.

  3. Add other indicators like moving averages to create multi-indicator systems for higher accuracy.

  4. Research alternate stop loss positioning logic, like fixed distance from entry instead of entry price itself.

  5. Increase stop loss movement occurrences to 3 or more stages.

Conclusion

This strategy uses Bollinger Bands and Stochastic for entries, sets two take profit targets, and moves stop loss to entry after first target reached to form a two-stage stop loss. This effectively locks in profits and prevents stop loss hunting. Strategy has clear advantages but also room for improvements via parameter optimization, multi-indicator systems, and stop loss logic adjustments.


/*backtest
start: 2022-10-18 00:00:00
end: 2023-10-24 00:00:00
period: 1d
basePeriod: 1h
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/
// © fpsd4ve

//@version=5

// Add Bollinger Bands indicator (close, 20, 2) manually to visualise trading conditions
strategy("2xTP, SL to entry", 
     overlay=false,
     pyramiding=0,
     calc_on_every_tick=false,
     default_qty_type=strategy.percent_of_equity,
     default_qty_value=25,
     initial_capital=1000,
     commission_type=strategy.commission.percent,
     commission_value=0.01
     )

// PARAMETERS
// Assumes quote currency is FIAT as with BTC/USDT pair
tp1=input.float(200, title="Take Profit 1")
tp2=input.float(500, title="Take Profit 2")
sl=input.float(200, title="Stop Loss")
stOBOS = input.bool(true, title="Use Stochastic overbought/oversold threshold")

// Colors
colorRed = #FF2052
colorGreen = #66FF00


// FUNCTIONS
// Stochastic
f_stochastic() =>
    stoch = ta.stoch(close, high, low, 14)
    stoch_K = ta.sma(stoch, 3)
    stoch_D = ta.sma(stoch_K, 3)
    stRD = ta.crossunder(stoch_K, stoch_D)
    stGD = ta.crossover(stoch_K, stoch_D)
    [stoch_K, stoch_D, stRD, stGD]


// VARIABLES
[bbMiddle, bbUpper, bbLower] = ta.bb(close, 20, 2)
[stoch_K, stoch_D, stRD, stGD] = f_stochastic()


// ORDERS
// Active Orders
// Check if strategy has open positions
inLong = strategy.position_size > 0
inShort = strategy.position_size < 0
// Check if strategy reduced position size in last bar
longClose = strategy.position_size < strategy.position_size[1]
shortClose = strategy.position_size > strategy.position_size[1]

// Entry Conditions
// Enter long when during last candle these conditions are true:
// Candle high is greater than upper Bollinger Band
// Stochastic K line crosses under D line and is oversold
longCondition = stOBOS ?
     low[1] < bbLower[1] and stGD[1] and stoch_K[1] < 25 :
     low[1] < bbLower[1] and stGD[1]

// Enter short when during last candle these conditions are true:
// Candle low is lower than lower Bollinger Band
// Stochastic K line crosses over D line and is overbought
shortCondition = stOBOS ?
     high[1] > bbUpper[1] and stRD[1] and stoch_K[1] > 75 :
     high[1] > bbUpper[1] and stRD[1]

// Exit Conditions
// Calculate Take Profit 
longTP1 = strategy.position_avg_price + tp1
longTP2 = strategy.position_avg_price + tp2
shortTP1 = strategy.position_avg_price - tp1
shortTP2 = strategy.position_avg_price - tp2

// Calculate Stop Loss
// Initialise variables
var float longSL = 0.0
var float shortSL = 0.0

// When not in position, set stop loss using close price which is the price used during backtesting
// When in a position, check to see if the position was reduced on the last bar
// If it was, set stop loss to position entry price. Otherwise, maintain last stop loss value
longSL := if inLong and ta.barssince(longClose) < ta.barssince(longCondition)
    strategy.position_avg_price
else if inLong
    longSL[1]
else
    close - sl

shortSL := if inShort and ta.barssince(shortClose) < ta.barssince(shortCondition)
    strategy.position_avg_price
else if inShort
    shortSL[1]
else
    close + sl

// Manage positions
strategy.entry("Long", strategy.long, when=longCondition)
strategy.exit("TP1/SL", from_entry="Long", qty_percent=50, limit=longTP1, stop=longSL)
strategy.exit("TP2/SL", from_entry="Long", limit=longTP2, stop=longSL)

strategy.entry("Short", strategy.short, when=shortCondition)
strategy.exit("TP1/SL", from_entry="Short", qty_percent=50, limit=shortTP1, stop=shortSL)
strategy.exit("TP2/SL", from_entry="Short", limit=shortTP2, stop=shortSL)


// DRAW
// Stochastic Chart
plot(stoch_K, color=color.blue)
plot(stoch_D, color=color.orange)

// Circles
plot(stOBOS ? stRD and stoch_K >= 75 ? stoch_D : na : stRD ? stoch_D : na, color=colorRed, style=plot.style_circles, linewidth=3)
plot(stOBOS ? stGD and stoch_K <= 25 ? stoch_D : na : stGD ? stoch_K : na, color=colorGreen, style=plot.style_circles, linewidth=3)

// Levels
hline(75, linestyle=hline.style_dotted)
hline(25, linestyle=hline.style_dotted)

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