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…

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:
The Hull indicator is responsive in capturing trend transitions, while the LSMA is smooth in identifying reversal signals reliably. The combination works effectively.
Using LSMA crossings filters out false signals from the Hull indicator and reduces erroneous trades.
The use of fluctuation points for stop loss protects funds to the maximum extent.
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:
In ranging markets, there may be excessive crossovers between Hull and LSMA causing over-trading. Parameters should be tuned appropriately to reduce trading frequency.
Stop loss set to fluctuation points may be triggered by short-term price adjustments. The distance should be widened appropriately.
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:
Optimize parameters of Hull and LSMA to match different products and timeframes.
Add filters based on volatility, volume etc. to avoid erroneous trades in ranging markets.
Incorporate machine learning models to aid in judging trend tendencies.
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
| Name | Default | What it controls |
|---|---|---|
| v_input_2 | false | Offset |
| v_input_3_close | 0 | Source: close | high | low | open | hl2 | hlc3 | hlcc4 | ohlc4 |
| v_input_string_1 | 0 | Hull Variation: Hma | Thma | Ehma |
| v_input_5 | 55 | Length(180-200 for floating S/R , 55 for swing entry) |
| v_input_6 | true | Length multiplier (Used to view higher timeframes with straight band) |
| v_input_7 | false | Show Hull MA from X timeframe? (good for scalping) |
| v_input_timeframe_1 | 240 | Higher timeframe |
| v_input_8 | true | Color Hull according to trend? |
| v_input_9 | false | Color candles based on Hull's Trend? |
| v_input_10 | false | Show as a Band? |
| v_input_11 | true | Line Thickness |
| v_input_int_1 | 40 | Band Transparency |
| v_input_1 | 25 | (?Least Squares Moving Average LSMA)Length |
| v_input_4_close | 0 | (?Hull Suite)Source: close | high | low | open | hl2 | hlc3 | hlcc4 | ohlc4 |
| v_input_bool_1 | false | (?ADX)Average Directional Index (ADX) |
| v_input_12 | 14 | ADX Smoothing |
| v_input_13 | 14 | DI Length |
| v_input_14 | 25 | ADX Threshold |
| v_input_bool_2 | true | (?Date Range)Start |
| v_input_15 | timestamp(1 Jan 2019) | startPeriodTime |
| v_input_bool_3 | true | End |
| v_input_16 | timestamp(31 Dec 2030) | endPeriodTime |
| v_input_string_2 | 0 | (?Trade Direction)Trade Direction: Long and Short | Long Only | Short Only |
| v_input_float_1 | 100 | (?Take Profit)Take Profit 1 - Target % |
| v_input_int_2 | 100 | % Of Position |
| v_input_float_2 | 100 | Take Profit 2 - Target % |
| v_input_int_3 | 100 | % Of Position |
| v_input_float_3 | 100 | Take Profit 3 - Target % |
| v_input_int_4 | 100 | % Of Position |
| v_input_float_4 | 100 | Take Profit 4 - Target % |
| v_input_float_5 | 999 | (?Stop Loss)Stop Loss (%) |
| v_input_float_6 | true | (?Leverage)Leverage |
| v_input_string_3 | CRYPTANEX_99FTX_Strategy-Name-Here | (?ProfitView Alert Syntax)Alert Syntax Prefix |
| v_input_bool_4 | false | (?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.
/agenkit build a production-grade trading bot with a backtest engine, risk controls and paper trading by default from strategies/Trend-Following-Quant-Strategy-Based-on-Hull-and-LSMA-Indicators.md- npx agenkit install engineering-kit in your project
- Paste the command into your agent and approve each phase
- Get tests, backtest, risk controls and a paper-trading switch
Understand it first
Before you run this, read the lesson behind the idea and how to backtest it honestly. Specs like this one are the survivors of an unknown number of trials; deflate their results accordingly.
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