Dynamic Channel Breakthrough Strategy

This strategy uses the Keltner Channel indicator, combined with moving average lines, to set dynamic breakout buy and sell prices to achieve low-buy-high-sell breakthrough operations. The strategy can automatically…

Pine ScriptBreakout Trend following Volatility EMA SMA ATR Keltner

Author: ChaoZhang
Complexity: Starter · 46 lines
Parameters: 6
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Principle

Calculate channel median: Use exponential moving average to calculate the price median of the channel
Calculate channel bandwidth: Use the moving average of true volatility, average true volatility or price amplitude to calculate channel bandwidth
Channel upper and lower rail: Median ± N times channel bandwidth
Entry order: When the price touches the upper rail, set the breakthrough buy price and wait for the breakthrough; when the price touches the lower rail, set the breakthrough sell price and wait for the breakthrough
Exit order: Stop loss when price falls back to median after buying, or when highest price exceeds entry price; Stop loss when price bounces back to median after selling, or when lowest price is lower than entry price

Advantage Analysis

Using dynamic channels can quickly capture changes in market trends
Using median is conducive to judging the direction of price trends
N times bandwidth setting makes the channel range reasonable to avoid frequent position adjustments
Using breakthrough mechanisms conforms to trend theory and follows the trend
Setting stop loss conditions strictly controls risks

Risk Analysis

The selection of the method for calculating the median line will affect the matching effect of the channel range and prices
Excessive large or small N multiples will affect the strategy's rate of return
Breakthrough buys and sells tend to form false signals and should be strictly stopped out

Optimization Directions

Try different median line calculation methods to find the optimal parameters
Test different N values to find the optimal multiplier
Increase the breakthrough amplitude to avoid false signals
Optimize stop loss logic to strictly control single loss

Summary

The overall strategy uses scientific and reasonable methods to judge price trends and directions through dynamic channel indicators, sets reasonable parameters to capture breakthrough signals, achieves low-buy-high-sell, and gains excess returns. At the same time, continuously optimize the risks of the strategy so that it can run stably in various markets.

Parameters

Name	Default	What it controls
v_input_int_1	20	length
v_input_float_1	2	Multiplier
v_input_1_close	0	Source: close \| high \| low \| open \| hl2 \| hlc3 \| hlcc4 \| ohlc4
v_input_2	true	Use Exponential MA
v_input_string_1	0	Bands Style: Average True Range \| True Range \| Range
v_input_3	10	ATR Length

Source Pine Script

/*backtest
start: 2024-01-27 00:00:00
end: 2024-02-26 00:00:00
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy(title="Keltner Strategy", overlay=true)
length = input.int(20, minval=1)
mult = input.float(2.0, "Multiplier")
src = input(close, title="Source")
exp = input(true, "Use Exponential MA")
BandsStyle = input.string("Average True Range", options = ["Average True Range", "True Range", "Range"], title="Bands Style")
atrlength = input(10, "ATR Length")
esma(source, length)=>
	s = ta.sma(source, length)
	e = ta.ema(source, length)
	exp ? e : s
ma = esma(src, length)
rangema = BandsStyle == "True Range" ? ta.tr(true) : BandsStyle == "Average True Range" ? ta.atr(atrlength) : ta.rma(high - low, length)
upper = ma + rangema * mult
lower = ma - rangema * mult
crossUpper = ta.crossover(src, upper)
crossLower = ta.crossunder(src, lower)
bprice = 0.0
bprice := crossUpper ? high+syminfo.mintick : nz(bprice[1])
sprice = 0.0
sprice := crossLower ? low -syminfo.mintick : nz(sprice[1])
crossBcond = false
crossBcond := crossUpper ? true
     : na(crossBcond[1]) ? false : crossBcond[1]
crossScond = false
crossScond := crossLower ? true
     : na(crossScond[1]) ? false : crossScond[1]
cancelBcond = crossBcond and (src < ma or high >= bprice )
cancelScond = crossScond and (src > ma or low <= sprice )
if (cancelBcond)
	strategy.cancel("KltChLE")
if (crossUpper)
	strategy.entry("KltChLE", strategy.long, stop=bprice, comment="KltChLE")
if (cancelScond)
	strategy.cancel("KltChSE")
if (crossLower)
	strategy.entry("KltChSE", strategy.short, stop=sprice, comment="KltChSE")

Published by ChaoZhang on the FMZ strategy square · last modified 2024-02-27. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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