Dual Breakout Volatility Channel Strategy

The dual breakout volatility channel strategy calculates the middle, upper and lower bands of the channel and uses trend and volume indicators to determine market direction and momentum. It sets breakout signals on…

Pine ScriptBreakout Volatility Mean reversion MACD EMA SMA ATR ADX / DMI Keltner

Author: ChaoZhang
Complexity: Intermediate · 137 lines
Parameters: 17
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

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Overview

Strategy Logic

The core indicator of this strategy is the statistically-based volatility channel of candlestick lines. The middle band adopts the moving average algorithm and the upper and lower bands adopt the average true range method to dynamically capture the boundaries of price fluctuations. At the same time, the strategy incorporates DMI and volume criteria to avoid false breakouts.

Specifically, when the price breaks out of the lower rail into the channel, the +DI line of the DMI exceeds the -DI line and the set ADX benchmark, and the trading volume increases, a buy signal is generated. Conversely, when the price breaks through the channel downward from the upper rail, the judgment rules are opposite to the above, generating a sell signal.

Advantage Analysis

The biggest advantage of this strategy is capturing the major breakthrough direction of prices. The dual breakout judgment can effectively avoid sideways and shock markets and reduce the number of stop losses. Compared with simple moving average strategies, the volatility channel breakout judgment is more adaptive to price fluctuations.

In addition, the introduction of auxiliary indicators DMI and volume also plays a good filtering role, avoiding false signals. So from the win rate and profit-loss ratio point of view, the strategy has some advantages.

Risk Analysis

The biggest risk of the dual breakout strategy is that it cannot judge market reversals. If a V-shaped reversal occurs in the market, the stop loss point may be easily triggered. In addition, improper parameter settings can also negatively impact the trading system.

To address the risks, we can further optimize parameter settings and narrow down stop losses to reduce risks. Of course, trading systems can never completely avoid losses, the key is to control risks.

Optimization Directions

The strategy also has great potential for optimization, which can be improved in the following aspects:

Parameter optimization, such as fine tuning of DMI's DI and ADX lengths, period and multiplier settings of volatility channels, etc.
Increase filtering conditions, such as combining MACD and other indicators to avoid false breakouts
Implement automatic tracking of take profit and stop loss to further control risks
Optimize parameter settings and filtering rules for different products

Summary

In general, the dual breakout volatility channel strategy is an effective breakout system. It can effectively determine the main trend direction and momentum, and has great potential in optimization and risk control. If improved and optimized systematically, the strategy can profit steadily in the long run.

Parameters

Name	Default	What it controls
v_input_int_1	46	Period
v_input_1	true	useTrueRange
v_input_int_2	81	length
v_input_float_1	2.5	mult
v_input_2	19	DI Length
v_input_int_3	27	DMI Benchmark
v_input_3	2019	Backtest Start Year
v_input_4	true	Backtest Start Month
v_input_5	true	Backtest Start Day
v_input_6	9999	Backtest Stop Year
v_input_7	12	Backtest Stop Month
v_input_8	31	Backtest Stop Day
v_input_float_2	4.5	Long Take Profit 1 %
v_input_int_4	15	Long Take Profit 1 Qty
v_input_float_3	20	Long Take Profit 2%
v_input_int_5	100	Long Take Profit 2 Qty
v_input_float_4	4	Long Stop Loss %

Source Pine Script

/*backtest
start: 2023-12-01 00:00:00
end: 2023-12-31 23:59:59
period: 1h
basePeriod: 15m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//Original Idea by: Wunderbit Trading

//@version=5
strategy('Keltner Channel ETH/USDT 1H', overlay=true, initial_capital=1000, pyramiding=0, currency='USD', default_qty_type=strategy.percent_of_equity, default_qty_value=100, commission_type=strategy.commission.percent, commission_value=0.07)


/// TREND
ribbon_period = input.int(46, 'Period', step=1)

leadLine1 = ta.ema(close, ribbon_period)
leadLine2 = ta.sma(close, ribbon_period)

// p3 = plot(leadLine1, color= #53b987, title="EMA", transp = 50, linewidth = 1)
// p4 = plot(leadLine2, color= #eb4d5c, title="SMA", transp = 50, linewidth = 1)
// fill(p3, p4, transp = 60, color = leadLine1 > leadLine2 ? #53b987 : #eb4d5c)

//Upward Trend
UT = leadLine2 < leadLine1
DT = leadLine2 > leadLine1

///////////////////////////////////////INDICATORS

// KELTNER //
source = close
useTrueRange = input(true)
length = input.int(81, step=1, minval=1)
mult = input.float(2.5, step=0.1)

// Calculate Keltner Channel
ma = ta.sma(source, length)
range_1 = useTrueRange ? ta.tr : high - low
rangema = ta.sma(range_1, length)
upper = ma + rangema * mult
lower = ma - rangema * mult

plot(ma, title='Middle', color=color.new(color.orange, 0))
p1 = plot(upper, title='Upper', color=color.new(color.orange, 0))
p2 = plot(lower, title='Lower', color=color.new(color.orange, 0))
fill(p1, p2, transp=90)


// DMI INDICATOR //
adxlen = 10  // input(10, title="ADX Smoothing")
dilen = input(19, title='DI Length')
keyLevel = 23  // input(23, title="key level for ADX")
dirmov(len) =>
    up = ta.change(high)
    down = -ta.change(low)
    truerange = ta.rma(ta.tr, len)
    plus = fixnan(100 * ta.rma(up > down and up > 0 ? up : 0, len) / truerange)
    minus = fixnan(100 * ta.rma(down > up and down > 0 ? down : 0, len) / truerange)
    [plus, minus]

adx(dilen, adxlen) =>
    [plus, minus] = dirmov(dilen)
    sum = plus + minus
    adx = 100 * ta.rma(math.abs(plus - minus) / (sum == 0 ? 1 : sum), adxlen)
    [adx, plus, minus]

[sig, up, down] = adx(dilen, adxlen)

benchmark = input.int(title='DMI Benchmark', defval=27, minval=1, step=1)

// plot(sig, color=color.red, title="ADX")
// plot(up, style=plot.style_histogram, color=color.green, title="+DI")
// plot(down, style=plot.style_histogram, color=color.red, title="-DI")
// plot(keyLevel, color=color.white, title="Key Level")

///////////////////////////////////////////////////////////


////////////////////////////////////////////////////Component Code Start

testStartYear = input(2019, 'Backtest Start Year')
testStartMonth = input(1, 'Backtest Start Month')
testStartDay = input(1, 'Backtest Start Day')
testPeriodStart = timestamp(testStartYear, testStartMonth, testStartDay, 0, 0)

testStopYear = input(9999, 'Backtest Stop Year')
testStopMonth = input(12, 'Backtest Stop Month')
testStopDay = input(31, 'Backtest Stop Day')
testPeriodStop = timestamp(testStopYear, testStopMonth, testStopDay, 0, 0)

testPeriod() => true
///// Component Code Stop //////////////////////////////////////////

//////////////// STRATEGY EXECUTION //////////////////////////

//LONG SET UP
// Take Profit / Stop Loss
long_tp1_inp = input.float(4.5, title='Long Take Profit 1 %', step=0.1) / 100
long_tp1_qty = input.int(15, title='Long Take Profit 1 Qty', step=1)

long_tp2_inp = input.float(20, title='Long Take Profit 2%', step=0.1) / 100
long_tp2_qty = input.int(100, title='Long Take Profit 2 Qty', step=1)

long_take_level_1 = strategy.position_avg_price * (1 + long_tp1_inp)
long_take_level_2 = strategy.position_avg_price * (1 + long_tp2_inp)

long_sl_inp = input.float(4, title='Long Stop Loss %', step=0.1) / 100
long_stop_level = strategy.position_avg_price * (1 - long_sl_inp)


// STRATEGY CONDITION
// LONG
entry_long = open > lower and open < upper and close > upper and up > down and up > benchmark  //  and volume[0] > volume[1]
entry_price_long = ta.valuewhen(entry_long, close, 0)
SL_long = entry_price_long * (1 - long_sl_inp)
exit_long = close < lower or low < SL_long


// STRATEGY EXECUTION
if testPeriod()

    // LONG
    if UT
        strategy.entry(id='Long', direction=strategy.long, when=entry_long, comment='INSERT ENTER LONG COMMAND')
    strategy.exit('TP1', 'Long', qty_percent=long_tp1_qty, limit=long_take_level_1)  // PLACE TAKE PROFIT IN WBT BOT SETTINGS 
    strategy.exit('TP2', 'Long', qty_percent=long_tp2_qty, limit=long_take_level_2)  // PLACE TAKE PROFIT IN WBT BOT SETTINGS
    strategy.close(id='Long', when=exit_long, comment='INSERT EXIT LONG COMMAND')


//PLOT FIXED SLTP LINE
// LONG POSITION
plot(strategy.position_size > 0 ? long_take_level_1 : na, style=plot.style_linebr, color=color.new(color.green, 0), linewidth=1, title='1st Long Take Profit')
plot(strategy.position_size > 0 ? long_take_level_2 : na, style=plot.style_linebr, color=color.new(color.green, 0), linewidth=1, title='2nd Long Take Profit')
plot(strategy.position_size > 0 ? long_stop_level : na, style=plot.style_linebr, color=color.new(color.red, 0), linewidth=1, title='Long Stop Loss')

Published by ChaoZhang on the FMZ strategy square · last modified 2024-01-31. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

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