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.
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.
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.
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.
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.
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.
/*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)template: strategy.tpl:40:21: executing "strategy.tpl" at <.api.GetStrategyListByName>: wrong number of args for GetStrategyListByName: want 7 got 6