Volatility Stop Tracking Strategy

Pine ScriptVolatility Breakout Mean reversion ATR

Author: ChaoZhang
Complexity: Intermediate · 69 lines
Parameters: 12
Backtest bar: 1d · swing
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

This is a trend tracking stop loss strategy based on price volatility. It uses Average True Range (ATR) to set stop loss lines for price fluctuations. ATR reflects the volatility and risk level of prices. When the price exceeds the stop loss line, the strategy judges the trend reversal and takes corresponding actions to open positions or stop losses.

Strategy Principle

The strategy first calculates the Average True Range (ATR) over a certain period. Then based on the current price trend direction, if it is an uptrend, the stop loss line is set to the current highest price minus n times the ATR; if it is a downtrend, the stop loss line is set to the current lowest price plus n times the ATR. The n value can be adjusted through parameters to control the distance between the stop loss line and the price.

When the price breaks through the stop loss line of the uptrend or the downtrend, the trend is judged to have changed. At this point, the strategy clears positions for stop loss and sets a new stop loss line based on the direction of the new trend.

In summary, the strategy uses price volatility to set stop loss lines to achieve accurate judgment of trend changes. Timely stop loss when the trend changes helps the strategy grasp the direction of the new trend.

Advantages of the Strategy

Use price volatility characteristics to judge trends and accurately grasp price turning points
Timely stop losses and switch positions to reduce risks of market reversals
Flexible parameter adjustment to control distance between stop loss line and price fluctuations
Parameters can be optimized for specific products for better adaptability

Risks of the Strategy

Risks of misjudgment due to invalid breakouts. Prices may have unsustainable invalid breakouts, causing misjudgments of trend changes
Overly aggressive parameter settings may increase losses. For example, when the n value is too large, the stop loss line is too close and small fluctuations may trigger it
The stop loss effect may be poor for low volatility products like currencies. Smaller ATR values mean stop loss lines are closer to prices

Optimization Directions

Auxiliary indicators like trading volume or volatility acceleration can be introduced to avoid misjudgment of invalid breakouts
Adjust n value based on characteristics of different products to make stop loss distance more appropriate
ATR period can also be optimized to choose the most suitable period parameter to judge price gap volatility

Summary

Overall this is a good algorithm implementation for setting stop loss lines based on price volatility. Its accuracy in judging price trends is high and it can capture key turning points of trends. It also provides some room for parameter tuning for better adaptability. As a stop loss strategy, it can effectively avoid risks of market reversals and is worth applying in live trading.

Parameters

Name	Default	What it controls
v_input_1	20	length
v_input_2	2	mult
v_input_3	false	Use take profit?
v_input_4	100	Take profit pips
v_input_5	false	Use stop loss?
v_input_6	100	Stop loss pips
v_input_7	true	From Day
v_input_8	true	From Month
v_input_9	2000	From Year
v_input_10	31	To Day
v_input_11	12	To Month
v_input_12	2039	To Year

Source Pine Script

/*backtest
start: 2022-11-30 00:00:00
end: 2023-11-30 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/
// © laptevmaxim92

//@version=4
strategy("Volatility stop strategy", overlay=true)

length = input(20)
mult = input(2, step = 0.1)
utp = input(false, "Use take profit?")
pr = input(100, "Take profit pips")
usl = input(false, "Use stop loss?")
sl = input(100, "Stop loss pips")
fromday = input(01, defval=01, minval=01, maxval=31, title="From Day")
frommonth = input(01, defval=01, minval= 01, maxval=12, title="From Month")
fromyear = input(2000, minval=1900, maxval=2100, title="From Year")
today = input(31, defval=01, minval=01, maxval=31, title="To Day")
tomonth = input(12, defval=12, minval=01, maxval=12, title="To Month")
toyear = input(2039, minval=1900, maxval=2100, title="To Year")

use_date = (time > timestamp(fromyear, frommonth, fromday, 00, 00) and time < timestamp(toyear, tomonth, today, 00, 00))

atr_ = atr(length)
max_ = 0.0
min_ = 0.0
max1 = 0.0
max1 := max(nz(max_[1]), close)
min1 = 0.0
min1 := min(nz(min_[1]), close)
vstop = 0.0
is_uptrend = false
is_uptrend_prev = false
is_uptrend_prev := nz(is_uptrend[1], true)
stop = is_uptrend_prev ? max1 - mult * atr_ : min1 + mult * atr_
vstop_prev = nz(vstop[1])
vstop1 = is_uptrend_prev ? max(vstop_prev, stop) : min(vstop_prev, stop)
is_uptrend := close - vstop1 >= 0
is_trend_changed = is_uptrend != is_uptrend_prev
max_ := is_trend_changed ? close : max1
min_ := is_trend_changed ? close : min1
vstop := is_trend_changed ? is_uptrend ? max_ - mult * atr_ : min_ + mult * atr_ : vstop1
plot(vstop, color = is_uptrend ? color.green : color.red, linewidth=2)

longCondition = is_uptrend
if (longCondition and use_date)
    strategy.entry("BUY", strategy.long)

shortCondition = not is_uptrend
if (shortCondition and use_date)
    strategy.entry("SELL", strategy.short)
    
if (utp and not usl)
    strategy.exit("TP", "BUY", profit = pr)
    strategy.exit("TP", "SELL", profit = pr)
    
if (usl and not utp)
    strategy.exit("SL", "BUY", loss = sl)
    strategy.exit("SL", "SELL", loss = sl)
    
if (usl and utp)
    strategy.exit("TP/SL", "BUY", loss = sl, profit = pr)
    strategy.exit("TP/SL", "SELL", loss = sl, profit = pr)

Published by ChaoZhang on the FMZ strategy square · last modified 2023-12-01. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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