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Strategy vault / Trend following

Trend Following Quant Strategy Based on Hull and LSMA Indicators

This strategy identifies trend directions and reversal points by combining the Hull and LSMA (Least Squares Moving Average) indicators to track trends. It goes long when the Hull shows an uptrend and the LSMA crosses…

Author
ChaoZhang
Complexity
Advanced · 304 lines
Parameters
34
Backtest bar
3m · intraday
Tested on
BTC/USDT · futures

IMG

Overview

This strategy identifies trend directions and reversal points by combining the Hull and LSMA (Least Squares Moving Average) indicators to track trends. It goes long when the Hull shows an uptrend and the LSMA crosses above the Hull, and goes short when the Hull shows a downtrend and the LSMA crosses below the Hull. The strategy is suitable for medium-low frequency trading and can be used on the 1-minute timeframe.

Strategy Logic

  • The Hull indicator is used to determine the trend direction of the price. When the middle band (MHULL) is above the lower band (LHULL), it indicates an uptrend; otherwise it indicates a downtrend.

  • The LSMA indicator is used to identify reversal points of the trend. When the LSMA crosses above MHULL, it signals the formation or acceleration of an uptrend; when the LSMA crosses below MHULL, it signals the formation or acceleration of a downtrend.

  • By combining the two, the strategy goes long when Hull shows an uptrend (MHULL > LHULL) and LSMA crosses above MHULL, and goes short when Hull shows a downtrend (MHULL < LHULL) and LSMA crosses below MHULL.

  • The stop loss is set to the latest fluctuation point. For long positions it is the most recent swing low, and for short positions it is the most recent swing high.

Advantage Analysis

The main advantages of this strategy are:

  1. The Hull indicator is responsive in capturing trend transitions, while the LSMA is smooth in identifying reversal signals reliably. The combination works effectively.

  2. Using LSMA crossings filters out false signals from the Hull indicator and reduces erroneous trades.

  3. The use of fluctuation points for stop loss protects funds to the maximum extent.

  4. It is suitable for medium-low frequency trading and can be used on timeframes as low as 1-minute, with wide applicability.

Risk Analysis

There are also some risks with this strategy:

  1. In ranging markets, there may be excessive crossovers between Hull and LSMA causing over-trading. Parameters should be tuned appropriately to reduce trading frequency.

  2. Stop loss set to fluctuation points may be triggered by short-term price adjustments. The distance should be widened appropriately.

  3. There may be some risk of misjudgment due to lagging of LSMA. Other indicators like candlestick patterns should be used to confirm signals.

Optimization Directions

The strategy can be optimized in the following aspects:

  1. Optimize parameters of Hull and LSMA to match different products and timeframes.

  2. Add filters based on volatility, volume etc. to avoid erroneous trades in ranging markets.

  3. Incorporate machine learning models to aid in judging trend tendencies.

  4. Identify key support/resistance areas with deep learning techniques for more reasonable stop loss placement.

Conclusion

By combining Hull and LSMA, this strategy effectively judges trend direction changes for trend following trading. It has the advantage of being simple to implement, responsive and widely applicable to medium-low frequency algo trading. Further improvements in filtering conditions, auxiliary judgements and stop loss algorithms can potentially yield better strategy performance.

Parameters

NameDefaultWhat it controls
v_input_2falseOffset
v_input_3_close0Source: close | high | low | open | hl2 | hlc3 | hlcc4 | ohlc4
v_input_string_10Hull Variation: Hma | Thma | Ehma
v_input_555Length(180-200 for floating S/R , 55 for swing entry)
v_input_6trueLength multiplier (Used to view higher timeframes with straight band)
v_input_7falseShow Hull MA from X timeframe? (good for scalping)
v_input_timeframe_1240Higher timeframe
v_input_8trueColor Hull according to trend?
v_input_9falseColor candles based on Hull's Trend?
v_input_10falseShow as a Band?
v_input_11trueLine Thickness
v_input_int_140Band Transparency
v_input_125(?Least Squares Moving Average LSMA)Length
v_input_4_close0(?Hull Suite)Source: close | high | low | open | hl2 | hlc3 | hlcc4 | ohlc4
v_input_bool_1false(?ADX)Average Directional Index (ADX)
v_input_1214ADX Smoothing
v_input_1314DI Length
v_input_1425ADX Threshold
v_input_bool_2true(?Date Range)Start
v_input_15timestamp(1 Jan 2019)startPeriodTime
v_input_bool_3trueEnd
v_input_16timestamp(31 Dec 2030)endPeriodTime
v_input_string_20(?Trade Direction)Trade Direction: Long and Short | Long Only | Short Only
v_input_float_1100(?Take Profit)Take Profit 1 - Target %
v_input_int_2100% Of Position
v_input_float_2100Take Profit 2 - Target %
v_input_int_3100% Of Position
v_input_float_3100Take Profit 3 - Target %
v_input_int_4100% Of Position
v_input_float_4100Take Profit 4 - Target %
v_input_float_5999(?Stop Loss)Stop Loss (%)
v_input_float_6true(?Leverage)Leverage
v_input_string_3CRYPTANEX_99FTX_Strategy-Name-Here(?ProfitView Alert Syntax)Alert Syntax Prefix
v_input_bool_4false(?Dashboard)Show Dashboard

Source Pine Script

/*backtest
start: 2024-01-28 00:00:00
end: 2024-02-04 00:00:00
period: 3m
basePeriod: 1m
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © myn

//@version=5
strategy('Strategy Myth-Busting #9 - HullSuite+LSMA - [MYN]', max_bars_back=5000, overlay=true, pyramiding=0, initial_capital=1000, currency='USD', default_qty_type=strategy.percent_of_equity, default_qty_value=1.0, commission_value=0.075, use_bar_magnifier = false)

// Hull Suite by InSilico
// Least Squares Moving Average

// Long 
// Hull Suite is red and LSMA crosses above HUll Suite while red
// Stop loss latest swing low

//Short
// Hull Suite is green and LSMA crosses under HUll Suite while green
// Stop loss latest swing high

//1:4 Risk ratio
// 1 minute timeframe


/////////////////////////////////////
//* Put your strategy logic below *//
/////////////////////////////////////
//72iE0gCVjvM


// LSMA
//░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░

//@version=5
//indicator(title = "Least Squares Moving Average", shorttitle="LSMA", overlay=true, timeframe="", timeframe_gaps=true)
length1 = input(title="Length", defval=25, group="Least Squares Moving Average (LSMA)")
offset1 = input(title="Offset", defval=0)
src1 = input(close, title="Source")
lsma = ta.linreg(src1, length1, offset1)
plot(lsma, color=color.white)



// Hull Suite by InSilico
//░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░

//@version=5
//Basic Hull Ma Pack tinkered by InSilico 
//indicator('Hull Suite by InSilico', overlay=true)

//INPUT
src = input(close, title='Source', group="Hull Suite")
modeSwitch = input.string('Hma', title='Hull Variation', options=['Hma', 'Thma', 'Ehma'])
length = input(55, title='Length(180-200 for floating S/R , 55 for swing entry)')
lengthMult = input(1.0, title='Length multiplier (Used to view higher timeframes with straight band)')

useHtf = input(false, title='Show Hull MA from X timeframe? (good for scalping)')
htf = input.timeframe('240', title='Higher timeframe')

switchColor = input(true, 'Color Hull according to trend?')
candleCol = input(false, title='Color candles based on Hull\'s Trend?')
visualSwitch = input(false, title='Show as a Band?')
thicknesSwitch = input(1, title='Line Thickness')
transpSwitch = input.int(40, title='Band Transparency', step=5)

//FUNCTIONS
//HMA
HMA(_src, _length) =>
    ta.wma(2 * ta.wma(_src, _length / 2) - ta.wma(_src, _length), math.round(math.sqrt(_length)))
//EHMA    
EHMA(_src, _length) =>
    ta.ema(2 * ta.ema(_src, _length / 2) - ta.ema(_src, _length), math.round(math.sqrt(_length)))
//THMA    
THMA(_src, _length) =>
    ta.wma(ta.wma(_src, _length / 3) * 3 - ta.wma(_src, _length / 2) - ta.wma(_src, _length), _length)

//SWITCH
Mode(modeSwitch, src, len) =>
    modeSwitch == 'Hma' ? HMA(src, len) : modeSwitch == 'Ehma' ? EHMA(src, len) : modeSwitch == 'Thma' ? THMA(src, len / 2) : na

//OUT
_hull = Mode(modeSwitch, src, int(length * lengthMult))
HULL = useHtf ? request.security(syminfo.ticker, htf, _hull) : _hull
MHULL = HULL[0]
SHULL = HULL[2]

//COLOR
hullColor = switchColor ? HULL > HULL[2] ? #00ff00 : #ff0000 : #ff9800

//PLOT
///< Frame
Fi1 = plot(MHULL, title='MHULL', color=hullColor, linewidth=thicknesSwitch, transp=50)
Fi2 = plot(visualSwitch ? SHULL : na, title='SHULL', color=hullColor, linewidth=thicknesSwitch, transp=50)
alertcondition(ta.crossover(MHULL, SHULL), title='Hull trending up.', message='Hull trending up.')
alertcondition(ta.crossover(SHULL, MHULL), title='Hull trending down.', message='Hull trending down.')
///< Ending Filler
fill(Fi1, Fi2, title='Band Filler', color=hullColor, transp=transpSwitch)
///BARCOLOR
barcolor(color=candleCol ? switchColor ? hullColor : na : na)




// Long 
// Hull Suite is red and LSMA crosses above HUll Suite while red
// Stop loss latest swing low

//Short
// Hull Suite is green and LSMA crosses under HUll Suite while green
// Stop loss latest swing high

//1:4 Risk ratio
longEntry = hullColor == #ff0000 and ta.crossover(lsma, MHULL )
shortEntry = hullColor == #00ff00 and ta.crossunder(lsma, MHULL)

//////////////////////////////////////
//* Put your strategy rules below *//
/////////////////////////////////////

longCondition = longEntry
shortCondition = shortEntry

//define as 0 if do not want to use
closeLongCondition = 0
closeShortCondition = 0


// ADX
//░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░

adxEnabled = input.bool(defval = false , title = "Average Directional Index (ADX)", tooltip = "", group ="ADX" ) 
adxlen = input(14, title="ADX Smoothing", group="ADX")
adxdilen = input(14, title="DI Length", group="ADX")
adxabove = input(25, title="ADX Threshold", group="ADX")

adxdirmov(len) =>
	adxup = ta.change(high)
	adxdown = -ta.change(low)
	adxplusDM = na(adxup) ? na : (adxup > adxdown and adxup > 0 ? adxup : 0)
	adxminusDM = na(adxdown) ? na : (adxdown > adxup and adxdown > 0 ? adxdown : 0)
	adxtruerange = ta.rma(ta.tr, len)
	adxplus = fixnan(100 * ta.rma(adxplusDM, len) / adxtruerange)
	adxminus = fixnan(100 * ta.rma(adxminusDM, len) / adxtruerange)
	[adxplus, adxminus]
adx(adxdilen, adxlen) =>
	[adxplus, adxminus] = adxdirmov(adxdilen)
	adxsum = adxplus + adxminus
	adx = 100 * ta.rma(math.abs(adxplus - adxminus) / (adxsum == 0 ? 1 : adxsum), adxlen)

adxsig = adxEnabled ? adx(adxdilen, adxlen) : na
isADXEnabledAndAboveThreshold = adxEnabled ? (adxsig > adxabove) : true

//Backtesting Time Period (Input.time not working as expected as of 03/30/2021.  Giving odd start/end dates
//░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
useStartPeriodTime = input.bool(true, 'Start', group='Date Range', inline='Start Period')
startPeriodTime = input(timestamp('1 Jan 2019'), '', group='Date Range', inline='Start Period')
useEndPeriodTime = input.bool(true, 'End', group='Date Range', inline='End Period')
endPeriodTime = input(timestamp('31 Dec 2030'), '', group='Date Range', inline='End Period')

start = useStartPeriodTime ? startPeriodTime >= time : false
end = useEndPeriodTime ? endPeriodTime <= time : false
calcPeriod = true

// Trade Direction 
// ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
tradeDirection = input.string('Long and Short', title='Trade Direction', options=['Long and Short', 'Long Only', 'Short Only'], group='Trade Direction')

// Percent as Points
// ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
per(pcnt) =>
    strategy.position_size != 0 ? math.round(pcnt / 100 * strategy.position_avg_price / syminfo.mintick) : float(na)

// Take profit 1
// ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
tp1 = input.float(title='Take Profit 1 - Target %', defval=100, minval=0.0, step=0.5, group='Take Profit', inline='Take Profit 1')
q1 = input.int(title='% Of Position', defval=100, minval=0, group='Take Profit', inline='Take Profit 1')

// Take profit 2
// ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
tp2 = input.float(title='Take Profit 2 - Target %', defval=100, minval=0.0, step=0.5, group='Take Profit', inline='Take Profit 2')
q2 = input.int(title='% Of Position', defval=100, minval=0, group='Take Profit', inline='Take Profit 2')

// Take profit 3
// ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
tp3 = input.float(title='Take Profit 3 - Target %', defval=100, minval=0.0, step=0.5, group='Take Profit', inline='Take Profit 3')
q3 = input.int(title='% Of Position', defval=100, minval=0, group='Take Profit', inline='Take Profit 3')

// Take profit 4
// ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
tp4 = input.float(title='Take Profit 4 - Target %', defval=100, minval=0.0, step=0.5, group='Take Profit')

/// Stop Loss
// ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
stoplossPercent = input.float(title='Stop Loss (%)', defval=999, minval=0.01, group='Stop Loss') * 0.01
slLongClose = close < strategy.position_avg_price * (1 - stoplossPercent)
slShortClose = close > strategy.position_avg_price * (1 + stoplossPercent)

/// Leverage
// ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
leverage = input.float(1, 'Leverage', step=.5, group='Leverage')
contracts = math.min(math.max(.000001, strategy.equity / close * leverage), 1000000000)


/// Trade State Management
// ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░

isInLongPosition = strategy.position_size > 0
isInShortPosition = strategy.position_size < 0

/// ProfitView Alert Syntax String Generation
// ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░

alertSyntaxPrefix = input.string(defval='CRYPTANEX_99FTX_Strategy-Name-Here', title='Alert Syntax Prefix', group='ProfitView Alert Syntax')
alertSyntaxBase = alertSyntaxPrefix + '\n#' + str.tostring(open) + ',' + str.tostring(high) + ',' + str.tostring(low) + ',' + str.tostring(close) + ',' + str.tostring(volume) + ','


/// Trade Execution
// ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░

longConditionCalc = (longCondition and isADXEnabledAndAboveThreshold)
shortConditionCalc = (shortCondition and isADXEnabledAndAboveThreshold)

if calcPeriod
    if longConditionCalc and tradeDirection != 'Short Only' and isInLongPosition == false
        strategy.entry('Long', strategy.long, qty=contracts)

        alert(message=alertSyntaxBase + 'side:long', freq=alert.freq_once_per_bar_close)

    if shortConditionCalc and tradeDirection != 'Long Only' and isInShortPosition == false
        strategy.entry('Short', strategy.short, qty=contracts)

        alert(message=alertSyntaxBase + 'side:short', freq=alert.freq_once_per_bar_close)
    
    //Inspired from Multiple %% profit exits example by adolgo https://www.tradingview.com/script/kHhCik9f-Multiple-profit-exits-example/
    strategy.exit('TP1', qty_percent=q1, profit=per(tp1))
    strategy.exit('TP2', qty_percent=q2, profit=per(tp2))
    strategy.exit('TP3', qty_percent=q3, profit=per(tp3))
    strategy.exit('TP4', profit=per(tp4))

    strategy.close('Long', qty_percent=100, comment='SL Long', when=slLongClose)
    strategy.close('Short', qty_percent=100, comment='SL Short', when=slShortClose)

    strategy.close_all(when=closeLongCondition or closeShortCondition, comment='Close Postion')

/// Dashboard
// ░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░░
// Inspired by https://www.tradingview.com/script/uWqKX6A2/ - Thanks VertMT

showDashboard = input.bool(group="Dashboard", title="Show Dashboard", defval=false)

f_fillCell(_table, _column, _row, _title, _value, _bgcolor, _txtcolor) =>
    _cellText = _title + "\n" + _value
    table.cell(_table, _column, _row, _cellText, bgcolor=_bgcolor, text_color=_txtcolor, text_size=size.auto)

// Draw dashboard table
if showDashboard
    var bgcolor = color.new(color.black,0)
    
    // Keep track of Wins/Losses streaks
    newWin  = (strategy.wintrades  > strategy.wintrades[1]) and (strategy.losstrades == strategy.losstrades[1]) and (strategy.eventrades == strategy.eventrades[1])
    newLoss = (strategy.wintrades == strategy.wintrades[1]) and (strategy.losstrades  > strategy.losstrades[1]) and (strategy.eventrades == strategy.eventrades[1])

    varip int winRow     = 0
    varip int lossRow    = 0
    varip int maxWinRow  = 0
    varip int maxLossRow = 0

    if newWin
        lossRow := 0
        winRow := winRow + 1
    if winRow > maxWinRow
        maxWinRow := winRow
        
    if newLoss
        winRow := 0
        lossRow := lossRow + 1
    if lossRow > maxLossRow
        maxLossRow := lossRow


    // Prepare stats table
    var table dashTable = table.new(position.bottom_right, 1, 15, border_width=1)
    
   
    if barstate.islastconfirmedhistory
        // Update table
        dollarReturn = strategy.netprofit
        f_fillCell(dashTable, 0, 0, "Start:", str.format("{0,date,long}", strategy.closedtrades.entry_time(0)) , bgcolor, color.white) // + str.format(" {0,time,HH:mm}", strategy.closedtrades.entry_time(0)) 
        f_fillCell(dashTable, 0, 1, "End:", str.format("{0,date,long}", strategy.opentrades.entry_time(0)) , bgcolor, color.white) // + str.format(" {0,time,HH:mm}", strategy.opentrades.entry_time(0))
        _profit = (strategy.netprofit / strategy.initial_capital) * 100
        f_fillCell(dashTable, 0, 2, "Net Profit:", str.tostring(_profit, '##.##') + "%", _profit > 0 ? color.green : color.red, color.white)
        _numOfDaysInStrategy = (strategy.opentrades.entry_time(0) - strategy.closedtrades.entry_time(0)) / (1000 * 3600 * 24)
        f_fillCell(dashTable, 0, 3, "Percent Per Day", str.tostring(_profit / _numOfDaysInStrategy, '#########################.#####')+"%", _profit > 0 ? color.green : color.red, color.white)
        _winRate = ( strategy.wintrades / strategy.closedtrades ) * 100
        f_fillCell(dashTable, 0, 4, "Percent Profitable:", str.tostring(_winRate, '##.##') + "%", _winRate < 50 ? color.red : _winRate < 75 ? #999900 : color.green, color.white)
        f_fillCell(dashTable, 0, 5, "Profit Factor:", str.tostring(strategy.grossprofit / strategy.grossloss,  '##.###'), strategy.grossprofit > strategy.grossloss ? color.green : color.red, color.white)
        f_fillCell(dashTable, 0, 6, "Total Trades:", str.tostring(strategy.closedtrades), bgcolor, color.white)
        f_fillCell(dashTable, 0, 8, "Max Wins In A Row:", str.tostring(maxWinRow, '######') , bgcolor, color.white)
        f_fillCell(dashTable, 0, 9, "Max Losses In A Row:", str.tostring(maxLossRow, '######') , bgcolor, color.white)

Published by ChaoZhang on the FMZ strategy square · last modified 2024-02-05. Collected in the Quant Trading Vault. Unvalidated research: re-test with your own data and costs before trusting it.

Build this with AgenKit

A spec is not a trading system. Paste this into your coding agent and AgenKit runs a specialist team — architecture, test-first build, risk gates, review — with paper trading on by default.

in Claude Code, Cursor, Codex & 4 more
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  1. npx agenkit install engineering-kit in your project
  2. Paste the command into your agent and approve each phase
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