Dynamic Trailing Stop Long Only Trend Following Strategy with Seasonality Filter

This strategy designs a long-only trend following strategy based on the Dynamic Movement Index (DMI), with an Average True Range (ATR) trailing stop loss to control downside risks. It also incorporates trading hours…

Pine ScriptTrend following Machine learning Volatility MACD Bollinger Bands ATR ADX / DMI

Author: ChaoZhang
Complexity: Intermediate · 121 lines
Parameters: 16
Backtest bar: 1h · intraday
Tested on: BTC/USDT · futures

Jump to code View in vault Original on FMZ

Overview

Strategy Logic

The strategy only enters trades on specified trading days (Mon-Fri) and trading hours (default 9:30am - 8:30pm local time).
When ADX is above 27, it signals that the market is in a trend. If the +DI crosses above -DI, a long signal is generated.
After opening a position, the stop loss is set at 5.5 x ATR from the entry price, and it trails upwards as price rises to lock in profits.
Optionally, S&P500 seasonal patterns are enabled, so that trades happen only during historically bullish periods.

Advantage Analysis

Combining trend metrics and stop loss helps effectively ride trends and control loss per trade.
Trading hours and seasonality filters help avoid abnormal volatility and reduce false signals.
DMI and ATR are mature technical indicators with flexibility in parameter tuning suitable for quant optimization.

Risk Analysis

Improper DMI and ATR parameters may lead to too many or too few signals. Parameter tuning is needed.
Stop loss set too wide may cause unnecessary stops. Set too tight may fail to control losses.
Trading hours and seasonality rules may filter some profitable opportunities. Filter effect needs evaluation.

Optimization Directions

Consider combining other indicators like MACD, Bollinger Bands for entry and exit rules.
Test different ATR multiples for stop loss, or dynamic adjustment of stop loss scale.
Test adjusting trading hours, or optimizing seasonal entry and exit dates.
Try applying machine learning methods to auto-tune parameters.

Conclusion

This strategy integrates trend following and risk control techniques to overcome high volatility issues with trend systems. Adding trading hours and seasonal filters further reduces false signals. With parameter tuning and feature expansion, this strategy can achieve more steady profits.

Parameters

Name	Default	What it controls
v_input_int_1	14	DI Length
v_input_int_2	14	ADX Smoothing
v_input_float_1	27	ADX Threshold for Long
v_input_int_3	14	ATR Length
v_input_float_2	5.5	ATR Multiplier for Trailing SL (Long)
v_input_int_4	9	startTime hh
v_input_int_5	30	startTime mm
v_input_int_6	20	endTime hh
v_input_int_7	30	endTime mm
v_input_int_8	true	Timezone Offset (Hours from UTC)
v_input_bool_1	false	Enable SP500 Seasonality
v_input_bool_2	true	Trade on Monday
v_input_bool_3	true	Trade on Tuesday
v_input_bool_4	true	Trade on Wednesday
v_input_bool_5	true	Trade on Thursday
v_input_bool_6	true	Trade on Friday

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="DMI Strategy with ADX and ATR-based Trailing SL (Long Only) and Seasonality", shorttitle="MBV-SP500-CLIMBER", overlay=true)

// Eingabeparameter für Long-Positionen
len = input.int(14, minval=1, title="DI Length")
lensig = input.int(14, title="ADX Smoothing", minval=1, maxval=50)
adxLongThreshold = input.float(27.0, title="ADX Threshold for Long", minval=0)
atrLength = input.int(14, title="ATR Length")
atrLongMultiplier = input.float(5.5, title="ATR Multiplier for Trailing SL (Long)")

startTimeHH = input.int(09, title="startTime hh")
startTimeMM = input.int(30, title="startTime mm")

endTimeHH = input.int(20, title="endTime hh")
endTimeMM = input.int(30, title="endTime mm")

// Zeitzone des Nutzers als Eingabeparameter
timezoneOffset = input.int(1, title="Timezone Offset (Hours from UTC)", minval=-12, maxval=14)


// Zusätzliche Einstellung für SP500-Saisonalität
enableSeasonality = input.bool(false, title="Enable SP500 Seasonality")
seasonColor = color.new(color.blue, 90)
activeTimeColor = color.new(color.yellow, 90) // Farbe für aktive Handelszeiten

// Handelstage und -zeiten
tradeMonday = input.bool(true, title="Trade on Monday")
tradeTuesday = input.bool(true, title="Trade on Tuesday")
tradeWednesday = input.bool(true, title="Trade on Wednesday")
tradeThursday = input.bool(true, title="Trade on Thursday")
tradeFriday = input.bool(true, title="Trade on Friday")

// Konvertierung der Uhrzeit in Unix-Zeitstempel
getUnixTime(hour, minute) =>
    adjustedHour = hour - timezoneOffset
    sessionDate = timestamp(year, month, dayofmonth, 0, 0)
    sessionDate + adjustedHour * 60 * 60000 + minute * 60000

// Start- und Endzeit als Unix-Zeitstempel
// + 1 Stunde wegen UTC
startTime = getUnixTime(startTimeHH, startTimeMM)
endTime = getUnixTime(endTimeHH, endTimeMM)


// Überprüfen, ob der aktuelle Zeitpunkt innerhalb der Handelszeit liegt
isTradingTime() => true

// Saisonale Zeiträume definieren
isSeason(time) =>
    m = month(time)
    d = dayofmonth(time)
    (m == 1 and d >= 1) or (m == 2 and d <= 15) or (m == 3 and d >= 23) or (m == 4 and d <= 17) or (m == 5 and d >= 12) or (m == 6 and d >= 27 and d <= 8) or (m == 7 and d <= 29) or (m == 10 and d >= 15) or (m == 11 and d >= 1) or (m == 12 and d <= 2) or (m == 12 and d >= 20 and d <= 27)

// Hintergrundfarbe für saisonale Bereiche und aktive Handelszeiten
bgcolor(enableSeasonality and isSeason(time) ? seasonColor : na)
bgcolor(isTradingTime() ? color.new(activeTimeColor, 90) : na)

// Berechnung von +DM, -DM, ATR
up = ta.change(high)
down = -ta.change(low)
plusDM = na(up) ? na : (up > down and up > 0 ? up : 0)
minusDM = na(down) ? na : (down > up and down > 0 ? down : 0)
trur = ta.rma(ta.tr, len)
atr = ta.atr(atrLength)

// Berechnung von +DI, -DI und ADX
plus = fixnan(100 * ta.rma(plusDM, len) / trur)
minus = fixnan(100 * ta.rma(minusDM, len) / trur)
sum = plus + minus
adx = 100 * ta.rma(math.abs(plus - minus) / (sum == 0 ? 1 : sum), lensig)

// Logik für LONG Signale unter Berücksichtigung der Saisonalität und Zeitfilter
longSignal = ta.crossover(adx, adxLongThreshold) and plus > minus and isTradingTime()
longSignal := longSignal and (not enableSeasonality or (enableSeasonality and isSeason(time)))


// Variable für Trailing Stop-Loss
var float longTrailingSL = na

// Variablen für die Eröffnungszeit und den Eröffnungspreis der Position
var int openBarIndex = na
var float openPrice = na

// Handelslogik für Long-Positionen
// ohne strategy.position_size == 0 gilt die Kondition für ALLE Signale und nicht nur für das erste
if (longSignal and strategy.position_size == 0)
    strategy.entry("Long", strategy.long)
    openBarIndex := bar_index
    openPrice := close
    longTrailingSL := close - atr * atrLongMultiplier

//if (longSignal)
   //longTrailingSL := close - atr * atrLongMultiplier

// Aktualisierung des Trailing Stop-Loss
if strategy.position_size > 0
    longTrailingSL := math.max(longTrailingSL, close - atr * atrLongMultiplier)

// Ausstieg aus Long-Positionen
strategy.exit("Close Long", "Long", stop=longTrailingSL)

// Anzeige des ATR-basierten Trailing Stops für Long-Positionen
//plot(strategy.position_size > 0 ? longTrailingSL : na, color=color.red, title="ATR Trailing Stop Long")

// Anzeige des ATR-basierten Trailing Stops für Long-Positionen
plot(strategy.position_size > 0 ? longTrailingSL : na, color=color.new(color.red, 75), style=plot.style_circles, linewidth=1, title="Trailing Stop-Loss")


// Wenn eine Position geschlossen wird, zeichnen Sie die Linie
// if strategy.position_size[1] > 0 and strategy.position_size == 0
//     lineColor = longTrailingSL > openPrice ? color.new(color.green, 50) : color.new(color.red, 50) // Hellgrün für Gewinne, Hellrot für Verluste
//     line.new(openBarIndex, openPrice, bar_index, longTrailingSL, width=3, color=lineColor)

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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