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Multitimeframe Trend Hunter Strategy

Author: ChaoZhang, Date: 2024-02-18 10:17:06
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Overview

The Multitimeframe Trend Hunter Strategy is a strategy that utilizes multiple indicators to generate automated trading signals. This strategy incorporates moving averages, Supertrend indicator, Ichimoku Cloud and more across multiple timeframes to determine trend direction and discover potential trading opportunities.

Strategy Logic

The core logic of this strategy is to judge trend direction simultaneously on higher and lower timeframes. The strategy first calculates key moving average, Supertrend lines, Ichimoku conversion and base lines etc. on the higher timeframe. It then calculates the Supertrend lines on the lower timeframe. When Supertrend directions on both timeframes align, the overall trend direction is confirmed. In addition, the strategy also checks if price breaks through moving average or ichimoku cloud to further validate trend reliability.

Once certain criteria are met, the strategy will generate buy or sell signals. Users can choose to only trade longs, shorts or both based on their needs. Users can also optimize parameters like moving average, Supertrend, Ichimoku etc. to improve strategy performance.

Advantage Analysis

The biggest advantage of this strategy is the combination of multiple timeframes and indicators, which greatly improves trend accuracy and timely detects reversal opportunities. Specific advantages are:

  1. Confirm trend with high/low timeframes, avoid market noise
  2. Moving average as mid/long-term indicator judges major trend
  3. Supertrend as short-term indicator timely catches trend reversal
  4. Ichimoku cloud identifies potential support/resistance levels

Risk Analysis

The main risks are improper parameter settings leading to over-trading or missing opportunities. Incorrect signal by indicators can also cause losses. Specific risks and solutions:

  1. Parameter risk: Backtest and optimize to find optimal parameters
  2. Signal error risk: Add more indicators to verify and avoid wrong signals
  3. Drawdown risk: Adjust position sizing to limit single trade loss

Optimization Directions

There is further room to optimize this strategy:

  1. Add more indicators like Bollinger Bands, RSI to improve accuracy
  2. Integrate machine learning models for more intelligent strategies
  3. Incorporate quant techniques like HFT, early bird to further enhance performance
  4. Optimize position sizing strategy to lower drawdown risk

Conclusion

In conclusion, the Multitimeframe Trend Hunter Strategy leverages multiple indicators across timeframes to determine trend and capture reversals timely. It is an effective quant trading strategy with wide applications and much room for future optimizations, worthwhile for quant traders to continually research and apply.

/*backtest
start: 2024-01-01 00:00:00
end: 2024-01-31 23:59:59
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/
// © godzcopilot / blockybears

// Thanks to anthonyf50 for his MTF Ichimoku https://www.tradingview.com/script/Pw9cBFma/
// Thanks to KivancOzbilgic for his SuperTrend https://www.tradingview.com/script/r6dAP7yi/
// Thanks to ZenAndTheArtOfTrading / PineScriptMastery for their Higher Timeframe EMA https://www.tradingview.com/script/Vh3XG9sD-Higher-Timeframe-EMA/


//@version=5
strategy("TrendHunter [Blocky]", overlay=true, default_qty_type=strategy.percent_of_equity, default_qty_value=80, initial_capital=1000, pyramiding=0)

// ================
// Strategy Inputs
// ================

// Defines user inputs for configuring the strategy.

// Higher Time Frame Selection
HTF_TimeFrame = input.timeframe(title='Higher Time Frame', defval='60', group = '== Timeframe ==', tooltip = "Select Chart for standard functionality")

// Inputs for EMA
len     = input.int(title="EMA Length", defval=200, group ='== EMA ==')
col     = input.bool(title="Colour EMA", defval=true, group ='== EMA ==')

// SuperTrend
Periods = input(title='ATR Period', defval=10, group = '== Supertrend ==')
Multiplier = input.float(title='ATR Multiplier', step=0.1, defval=3.0, group = '== Supertrend ==')
Src = input.source(title='Source', defval=hl2, group = '== Supertrend ==')

// Ichimoku
conversionPeriods = input.int(9, minval=1, title='Conversion Line Periods', group = '== Ichimoku ==')
basePeriods = input.int(26, minval=1, title='Base Line Periods', group = '== Ichimoku ==')
laggingSpan2Periods = input.int(52, minval=1, title='Lagging Span 2 Periods', group = '== Ichimoku ==')
displacement = input.int(26, minval=1, title='Displacement', group = '== Ichimoku ==')

// Ichimoku Display Options
isActiveConversion = input(false, 'Conversion Line', group = '== Ichimoku ==', inline = 'lines1')
isActiveBase = input(false, 'Base Line', group = '== Ichimoku ==', inline = 'lines1')
isActiveLagging = input(false, 'Lagging Span', group = '== Ichimoku ==', inline = 'lines2')
isActiveCloud = input(true, 'Cloud', group = '== Ichimoku ==', inline = 'lines2')


// ================
// Strategy Options
// ================

bTable = input.bool(true, title='Trade Table', group='== Strategy Options ==', tooltip = "Show table that shows current selected options and trade trade entry parameters")

bLong = input.bool(true, title='Enter Longs', group='== Strategy Options ==', inline = 'LongShort')
bShort = input.bool(true, title='Enter Shorts', group='== Strategy Options ==', inline = 'LongShort', tooltip = "Filter long / short trade signals")

bPriceCloud = input.bool(true, title='Price outside cloud', group='== Strategy Options ==', inline='PriceCloud')
bPriceCloudBody = input.bool(false, title='Full Body', group='== Strategy Options ==', inline='PriceCloud', tooltip = 'Only trade when price action outside the cloud.\nLongs when price action above the cloud.\nShort when price action below the cloud')

bPriceEMA = input.bool(false, title='Price above/below EMA', group='== Strategy Options ==', inline='PriceEMA')
bPriceEMABody = input.bool(false, title='Full Body', group='== Strategy Options ==', inline='PriceEMA', tooltip = 'Longs when price action above the EMA.\nShort when price action below the EMA')

bSuper = input.bool(true, title='Supertrend transistions', group='== Strategy Options ==', tooltip = "Trade in direction of the supertrend transitions")
bLTF = input.bool(false, title='LTF/HTF Supertrend alignment', group='== Strategy Options ==', tooltip = "Utilise a dual supertrends, chart and defined higher time frame")

bEMACloud1 = input.bool(true, title='EMA Outside Cloud', group='== Strategy Options ==', tooltip = "EMA must be outside the ichimoku cloud")
bEMACloud2 = input.bool(false, title='EMA above/below Cloud', group='== Strategy Options ==', tooltip = "Longs when EMA above the cloud.\nShort when EMA below the cloud")

bExitHTFTrail = input.bool(true, title='Super Trend Exits:  HTF', group='== Strategy Options ==', inline = 'Exits')
bExitLTFTrail = input.bool(true, title='LTF', group='== Strategy Options ==', inline = 'Exits', tooltip = 'Exit trades when price crosses the supertrend line\nIf neither selected trade closes when opposite trade opens\nIf using LTF closes turn on HTF/LTF alignment')

// ===========================
// EMA Functions and Plotting
// ===========================

// Calculate EMA
ema = ta.ema(close, len)
emaSmooth = request.security(syminfo.tickerid, HTF_TimeFrame, ema[barstate.isrealtime ? 1 : 0], gaps=barmerge.gaps_on)[barstate.isrealtime ? 0 : 1]


// Draw EMA
plot(emaSmooth, color=col ? (close > emaSmooth ? color.rgb(76, 163, 175) : color.rgb(6, 23, 173)) : color.black, linewidth=2, title="HTF EMA")


// ==================================
// Supertrend Functions and Plotting
// ==================================

// Function to calculate SuperTrend
calcSuperTrend(src, atrPeriods, multiplier) =>
    atr = ta.atr(atrPeriods)
    up = src - multiplier * atr
    up1 = nz(up[1], up)
    up := close[1] > up1 ? math.max(up, up1) : up
    dn = src + multiplier * atr
    dn1 = nz(dn[1], dn)
    dn := close[1] < dn1 ? math.min(dn, dn1) : dn
    trend = 1
    trend := nz(trend[1], trend)
    trend := trend == -1 and close > dn1 ? 1 : trend == 1 and close < up1 ? -1 : trend
    [up, dn, trend]

// Calculate SuperTrend for the current time frame
[up, dn, trend] = calcSuperTrend(Src, Periods, Multiplier)

// Plotting for the current time frame
plot(trend == 1 ? up : dn, title='LTF Supertrend', color=trend == 1 ?color.green : color.red, linewidth=1, style = plot.style_stepline)

// Fetching the higher time frame data
[HTF_up, HTF_dn, HTF_trend] = request.security(syminfo.tickerid, HTF_TimeFrame, calcSuperTrend(hl2, Periods, Multiplier), lookahead=barmerge.lookahead_on)

// Plotting for the higher time frame
plot(HTF_trend == 1 ? HTF_up : HTF_dn, title='HTF Up Trend', color= HTF_trend == 1 ? color.green : color.red, linewidth=4)


// ===============================
// Ichimoku Functions and Plotting
// ===============================

// Function to convert timeframe to hours
f_convertTimeframeToHours(tf) =>
    val = 0.0
    if tf == "1S" or tf == "S"
        val := 1.0 / 3600.0
    else if str.contains(tf, "S")
        val := str.tonumber(str.replace(tf, "S", "")) / 3600.0
    else if tf == "1D" or tf == "D"
        val := 24.0
    else if str.contains(tf, "D")
        val := str.tonumber(str.replace(tf, "D", "")) * 24.0
    else if tf == "1W" or tf == "W"
        val := 24.0 * 7.0
    else if str.contains(tf, "W")
        val := str.tonumber(str.replace(tf, "W", "")) * 24.0 * 7.0
    else if tf == "1M" or tf == "M"
        val := 24.0 * 30.0  // Approximation for a month
    else if str.contains(tf, "M")
        val := str.tonumber(str.replace(tf, "M", "")) * 24.0 * 30.0  // Approximation for months
    else
        // Default to minutes
        val := str.tonumber(tf) / 60.0
    val

// Time
timeOffset = time - time[1]


// Returns the displacement based on the chart / HTF resolution
f_getDisplacement(_res) =>
    _res == '' ? displacement : math.round(f_convertTimeframeToHours(_res) / f_convertTimeframeToHours(timeframe.period) * displacement)
    //f_avgDilationOf(_res) * displacement

// Returns average value between lowest and highest
f_avgLH(_len) =>
    math.avg(ta.lowest(_len), ta.highest(_len))

// Returns f_donchian data 
f_donchian(_tf, _src) =>
    request.security(syminfo.tickerid, _tf, _src, barmerge.gaps_off, barmerge.lookahead_on)

// Returns ichimoku data
f_ichimokuData(_tf) =>
    _isShow = _tf == '' or f_convertTimeframeToHours(_tf) >= f_convertTimeframeToHours(timeframe.period)
    _displacement = _isShow ? f_getDisplacement(_tf) : na
    _Conversion = _isShow ? f_donchian(_tf, f_avgLH(conversionPeriods)) : na
    _Base = _isShow ? f_donchian(_tf, f_avgLH(basePeriods)) : na
    _Lagging = _isShow ? f_donchian(_tf, close) : na
    _SSA = _isShow ? math.avg(_Conversion, _Base) : na
    _SSB = _isShow ? f_donchian(_tf, f_avgLH(laggingSpan2Periods)) : na
    _middleCloud = _isShow ? _SSA[0] > _SSB[0] ? _SSA[0] - math.abs(_SSA[0] - _SSB[0]) / 2 : _SSA[0] + math.abs(_SSA[0] - _SSB[0]) / 2 : na
    [_displacement, _Conversion, _Base, _Lagging, _SSA, _SSB, _middleCloud]

// Plotting ichimoku data

[Displacement, Conversion, Base, Lagging, SSA, SSB, fisrtMiddleCloud] = f_ichimokuData(HTF_TimeFrame)

// ————— Conversion
plot(isActiveConversion ? Conversion : na, color=color.new(color.blue, 0), title=' Conversion', linewidth=1)
// ————— Base
plot(isActiveBase ? Base : na, color=color.new(color.fuchsia, 0), title=' Base', linewidth=2)
// ————— Lagging
plot(isActiveLagging ? Lagging : na, offset=-Displacement, color=color.new(color.green, 0), title=' Lagging')

// ————— SSA + SSB
ssa = plot(isActiveCloud ? SSA : na, offset=Displacement, color=color.new(color.green, 0), title=' SSA', linewidth=1)
ssb = plot(isActiveCloud ? SSB : na, offset=Displacement, color=color.new(color.red, 0), title=' SSB', linewidth=1)
fill(ssa, ssb, color=color.new(SSA > SSB ? color.green : color.red , 80), title=' Cloud')


// ===============================
// Strategy Entries
// ===============================

// Checks whether price is inside the Ichimoku cloud
f_PriceCloud(dir) =>
    _enter = false
    if bPriceCloud
        if bLong and dir == 1
            if bPriceCloudBody
                _enter := close > math.max(SSA[Displacement], SSB[Displacement]) and open > math.max(SSA[Displacement], SSB[Displacement])
            else
                _enter := close > math.max(SSA[Displacement], SSB[Displacement])
        if bShort and dir == 2
            if bPriceCloudBody
                _enter := close < math.min(SSA[Displacement], SSB[Displacement]) and open < math.min(SSA[Displacement], SSB[Displacement])
            else
                _enter := close < math.min(SSA[Displacement], SSB[Displacement])
    else
        _enter := na
    _enter

// Checks whether price is above / below the ema
f_PriceEMA(dir) =>
    _enter = false
    if bPriceEMA
        if bLong and dir == 1
            if bPriceEMABody
                _enter := close > emaSmooth and open > emaSmooth
            else
                _enter := close > emaSmooth
        if bShort and dir == 2
            if bPriceEMABody
                _enter := close < emaSmooth and open < emaSmooth
            else
                _enter := close < emaSmooth
    else
        _enter := na
    _enter

// Checks HTF supertrend direction
f_Super(dir) =>
    _enter = false
    if bSuper
        if bLong and dir == 1
            _enter := HTF_trend == 1
        if bShort and dir == 2
            _enter := HTF_trend == -1
    else
        _enter := na

    _enter

// Checks LTF supertrend direction
f_LTF(dir) =>
    _enter = false
    if bLTF
        if bLong and dir == 1
            _enter := trend == 1 and HTF_trend == 1
        if bShort and dir == 2
            _enter := trend == -1 and HTF_trend == -1
    else
        _enter := na
    _enter

// Checks whether ema is inside the Ichimoku cloud
f_EMACloud1(dir) =>
    _enter = false
    if bEMACloud1
        if bLong and dir == 1
            _enter := (emaSmooth > math.max(SSA[Displacement], SSB[Displacement])) or (emaSmooth < math.min(SSA[Displacement], SSB[Displacement]))
        if bShort and dir == 2
            _enter := (emaSmooth > math.max(SSA[Displacement], SSB[Displacement])) or (emaSmooth < math.min(SSA[Displacement], SSB[Displacement]))
    else
        _enter := na
    _enter

// Checks whether ema is above/below Ichimoku cloud
f_EMACloud2(dir) =>
    _enter = false
    if bEMACloud2
        if bLong and dir == 1
            _enter := emaSmooth > math.max(SSA[Displacement], SSB[Displacement])
        if bShort and dir == 2
            _enter := emaSmooth < math.min(SSA[Displacement], SSB[Displacement])
    else
        _enter := na
    _enter

// Check if a value is 'na' or true.
f_NATrue(val) =>
    _enter = false
    if na(val)
        _enter := true
    if val
        _enter := true
    _enter   
    

// Consolidates entry conditions.
f_checkCondition(dir) =>
    _enter = false
    if na(f_PriceCloud(dir)) and na(f_PriceEMA(dir)) and na(f_Super(dir)) and na(f_LTF(dir)) and na(f_EMACloud1(dir)) and na(f_EMACloud2(dir))
        _enter := false
    else if f_NATrue(f_PriceCloud(dir)) and f_NATrue(f_PriceEMA(dir)) and f_NATrue(f_Super(dir)) and f_NATrue(f_LTF(dir)) and f_NATrue(f_EMACloud1(dir)) and f_NATrue(f_EMACloud2(dir))
        _enter := true
    _enter

        
// Execute long trade entries
longCondition = bLong and f_checkCondition(1)
if (longCondition)
    strategy.entry("Long", strategy.long)

// Execute short trade entries
shortCondition = bShort and f_checkCondition(2)
if (shortCondition)
    strategy.entry("Short", strategy.short)

// Excute trade exits
exitLong = (bExitHTFTrail and (close < HTF_up or HTF_trend == -1)) or (bExitLTFTrail and (close < up or trend == -1)) 
exitShort = (bExitHTFTrail and (close > HTF_dn or HTF_trend == 1)) or (bExitLTFTrail and (close > dn or trend == 1)) 

if exitLong
    strategy.close("Long")

if exitShort
    strategy.close("Short")

// Creates a table shoing all the user options and their current status for entering a trade
if bTable
    // Create a table
    tbl = table.new(position = position.bottom_right, columns = 4, rows = 9, bgcolor=color.new(color.white, 50), border_width = 1)

    table.cell(tbl, 1, 0, "Selected")
    table.cell(tbl, 2, 0, "Long", bgcolor=na(bLong) ? color.gray : bShort ? color.rgb(4, 112, 8) : color.rgb(100, 7, 7))
    table.cell(tbl, 3, 0, "Short", bgcolor=na(bShort) ? color.gray : bShort ? color.rgb(4, 112, 8) : color.rgb(100, 7, 7))

    table.cell(tbl, 0, 1, "Entry")
    table.cell(tbl, 2, 1, str.tostring(longCondition), bgcolor=longCondition ? color.green : color.red)
    table.cell(tbl, 3, 1, str.tostring(shortCondition), bgcolor=shortCondition ? color.green : color.red)


    table.cell(tbl, 0, 3, "Price Cloud")
    table.cell(tbl, 1, 3, str.tostring(bPriceCloud), bgcolor=na(bPriceCloud) ? color.gray : bPriceCloud ? color.green : color.red)
    table.cell(tbl, 2, 3, str.tostring(f_PriceCloud(1)), bgcolor=na(f_PriceCloud(1)) ? color.gray : f_PriceCloud(1) ? color.green : color.red)
    table.cell(tbl, 3, 3, str.tostring(f_PriceCloud(2)), bgcolor=na(f_PriceCloud(2)) ? color.gray : f_PriceCloud(2) ? color.green : color.red)

    table.cell(tbl, 0, 4, "Price EMA")
    table.cell(tbl, 1, 4, str.tostring(bPriceEMA), bgcolor=na(bPriceEMA) ? color.gray : bPriceEMA ? color.green : color.red)
    table.cell(tbl, 2, 4, str.tostring(f_PriceEMA(1)), bgcolor=na(f_PriceEMA(1)) ? color.gray : f_PriceEMA(1) ? color.green : color.red)
    table.cell(tbl, 3, 4, str.tostring(f_PriceEMA(2)), bgcolor=na(f_PriceEMA(2)) ? color.gray : f_PriceEMA(2) ? color.green : color.red)

    table.cell(tbl, 0, 5, "SuperTrend")
    table.cell(tbl, 1, 5, str.tostring(bSuper), bgcolor=na(bSuper) ? color.gray : bSuper ? color.green : color.red)
    table.cell(tbl, 2, 5, str.tostring(f_Super(1)), bgcolor=na(f_Super(1)) ? color.gray : f_Super(1) ? color.green : color.red)
    table.cell(tbl, 3, 5, str.tostring(f_Super(2)), bgcolor=na(f_Super(2)) ? color.gray : f_Super(2) ? color.green : color.red)

    table.cell(tbl, 0, 6, "HTF/LTF")
    table.cell(tbl, 1, 6, str.tostring(bLTF), bgcolor=na(bLTF) ? color.gray : bLTF ? color.green : color.red)
    table.cell(tbl, 2, 6, str.tostring(f_LTF(1)), bgcolor=na(f_LTF(1)) ? color.gray : f_LTF(1) ? color.green : color.red)
    table.cell(tbl, 3, 6, str.tostring(f_LTF(2)), bgcolor=na(f_LTF(2)) ? color.gray : f_LTF(2) ? color.green : color.red)

    table.cell(tbl, 0, 7, "EMA Outside Cloud")
    table.cell(tbl, 1, 7, str.tostring(bEMACloud1), bgcolor=na(bEMACloud1) ? color.gray : bEMACloud1 ? color.green : color.red)
    table.cell(tbl, 2, 7, str.tostring(f_EMACloud1(1)), bgcolor=na(f_EMACloud1(1)) ? color.gray : f_EMACloud1(1) ? color.green : color.red)
    table.cell(tbl, 3, 7, str.tostring(f_EMACloud1(2)), bgcolor=na(f_EMACloud1(2)) ? color.gray : f_EMACloud1(2) ? color.green : color.red)

    table.cell(tbl, 0, 8, "EMA Above/Below Cloud")
    table.cell(tbl, 1, 8, str.tostring(bEMACloud2), bgcolor=na(bEMACloud2) ? color.gray : bEMACloud2 ? color.green : color.red)
    table.cell(tbl, 2, 8, str.tostring(f_EMACloud2(1)), bgcolor=na(f_EMACloud2(1)) ? color.gray : f_EMACloud2(1) ? color.green : color.red)
    table.cell(tbl, 3, 8, str.tostring(f_EMACloud2(2)), bgcolor=na(f_EMACloud2(2)) ? color.gray : f_EMACloud2(2) ? color.green : color.red)
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