Double Donchian Channel Breakout Strategy

Pine ScriptBreakout Mean reversion Trend following Donchian

Author: ChaoZhang
Complexity: Starter · 58 lines
Parameters: 6
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

The Double Donchian Channel Breakout strategy is a quantitative trading strategy based on the Donchian Channel. This strategy uses a combination of fast and slow Donchian Channels to achieve low-risk high-return breakout trading. It goes long/short when price breaks out of the slow channel and exits at a stop loss or take profit when price breaks back through the fast channel.

Strategy Logic

This strategy mainly utilizes two Donchian Channels, including a slower channel with longer period and a faster channel with shorter period.

The slow Donchian Channel has a longer period which can effectively filter out market noise, making its breakout signals more reliable. The strategy goes long when price breaks above the upper band of the slow channel and goes short when price breaks below the lower band.

The fast Donchian Channel has a shorter period which can quickly respond to short-term price fluctuations. When price breaks back through this channel, it signals a trend reversal and prompts an exit for stop loss or take profit.

In addition, a volatility condition is set as a filter for entry signals. The strategy will only trigger entry when price movement exceeds a predetermined percentage threshold. This avoids frequent whipsaws during range-bound consolidations.

Advantage Analysis

Dual-channel mechanism sets two lines of defense and effectively controls risk
Combination of fast and slow channels efficiently captures trends
Volatility filter reduces ineffective trades
Simultaneously tracks trends and prevents overfitting
Simple and clear logic, easy to understand and master

Risk Analysis

Violent price swings may penetrate stop loss and cause heavy losses
Improper parameter settings (e.g. channel periods) may compromise strategy efficiency
Trading costs also erode profits to some extent
Gap risks around significant events need attention

These risks can be reduced by parameter optimization, reasonable stop loss placement, event awareness etc.

Optimization Directions

Test different combinations of Donchian channel periods
Optimize volatility parameter for best entry timing
Add trend-checking indicator to avoid counter-trend trades
Fundamentals-based stock picking
Adjust stop loss mechanism to limit losses

Conclusion

The Double Donchian Channel Breakout strategy is overall a relatively stable and reliable trend-following strategy. It combines the strengths of both trend capture and risk control, making it suitable as a basic module in various stock trading strategies. Further improvements in performance can be expected through parameter tuning and logic refinement.

Parameters

Name	Default	What it controls
v_input_int_1	50	Slow Donchian
v_input_int_2	30	Fast Donchian
v_input_int_3	3	Volatility (%)
v_input_float_1	2	Long TP1 (%)
v_input_float_2	2	Short TP1 (%)
v_input_int_4	50	TP1 Position Amount (%)

Source Pine Script

/*backtest
start: 2024-01-04 00:00:00
end: 2024-02-03 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This Pine Script™ code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © omererkan

//@version=5
strategy(title="Double Donchian Channel Breakout", overlay=true, initial_capital = 1000, commission_value = 0.05, default_qty_value = 100, default_qty_type = strategy.percent_of_equity)


slowLen = input.int(50, title="Slow Donchian")
fastLen = input.int(30, title="Fast Donchian")
volatility = input.int(3, title="Volatility (%)")
longProfitPerc = input.float(2, title="Long TP1 (%)", minval=0.0, step=0.1) * 0.01
shortProfitPerc = input.float(2, title="Short TP1 (%)", minval=0.0, step=0.1) * 0.01
TP1Yuzde =input.int(50, title = "TP1 Position Amount (%)")

ubSlow = ta.highest(close, slowLen)[1]
lbSlow = ta.lowest(close, slowLen)[1]

ubFast = ta.highest(close, fastLen)[1]
lbFast = ta.lowest(close, fastLen)[1]

plot(ubSlow, color=color.green, linewidth=2, title="Slow DoCh - Upperband")
plot(lbSlow, color=color.green, linewidth=2, title="Slow DoCh - Lowerband")
plot(ubFast, color=color.blue, linewidth=2, title="Fast DoCh - Upperband")
plot(lbFast, color=color.blue, linewidth=2, title="Fast DoCh - Lowerband")

fark = (ubSlow - lbSlow) / lbSlow * 100

longExitPrice  = strategy.position_avg_price * (1 + longProfitPerc)
shortExitPrice = strategy.position_avg_price * (1 - shortProfitPerc)

longCondition = ta.crossover(close, ubSlow) and fark > volatility
if (longCondition)
    strategy.entry("Long", strategy.long)

shortCondition = ta.crossunder(close, lbSlow) and fark > volatility
if (shortCondition)
    strategy.entry("Short", strategy.short)

if strategy.position_size > 0 and ta.crossunder(close, lbFast) 
    strategy.close("Long", "Close All")

if strategy.position_size < 0 and ta.crossover(close, ubFast)
    strategy.close("Short", "Close All")

// Take Profit
if strategy.position_size > 0
    strategy.exit("TP1", "Long", qty_percent = TP1Yuzde, limit = longExitPrice)

if strategy.position_size < 0
    strategy.exit("TP1", "Short", qty_percent = TP1Yuzde, limit = shortExitPrice)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-02-04. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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