Estrategia de seguimiento de tendencia de media móvil basada en SSL
Fecha de creación:
2024-01-15 14:36:39
Última modificación:
2024-01-15 14:36:39
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Descripción general
La estrategia es una estrategia que utiliza el indicador del canal SSL para determinar la tendencia del mercado y el seguimiento de la tendencia en la línea media como referencia. Se aplica a la línea de 4 horas y la línea de sol en la línea media y larga.
Principio de estrategia
El canal SSL se compone de la línea media de Kelt y el real de la amplitud. Puede determinar la dirección de la tendencia del mercado.
La estrategia utiliza un indicador de línea media como la EMA para calcular una línea media de referencia. Esta línea media puede filtrar algunas brechas falsas.
La estrategia se hace más cuando el precio se rompe la línea de la vía superior de SSL, y se hace vacío cuando el precio se rompe la línea de la vía inferior de SSL.
El método de parada de pérdidas tiene un porcentaje de parada, una parada de ATR y una revisión de la parada mínima / máxima. La parada es N veces la parada de pérdidas. Los parámetros específicos son determinados por el usuario.
Análisis de las ventajas
El canal SSL determina la dirección de la tendencia con precisión, reduciendo las falsas señales. La colaboración con la unión de la línea de paridad es la base de entrada en el mercado, evitando la búsqueda de la parte inferior.
Se puede elegir con flexibilidad entre diferentes tipos de líneas medias para adaptarse a un contexto más amplio de mercado.
El método de stop loss es flexible y el riesgo se puede controlar. El multiplicador de stop loss también se puede configurar de manera flexible para satisfacer diferentes preferencias.
El objetivo de la iniciativa es crear un mercado de trabajo abierto, que permita a los empresarios y a las empresas explotar las oportunidades que ofrece el mercado.
Análisis de riesgos
Los indicadores de la línea media están rezagados y es posible que haya pérdidas acumuladas.
En el caso de una sacudida, la primera vez que se sube y baja de la vía hay una reversión, por lo que es fácil de atrapar.
El ATR y el Stop Loss de Revisión pueden ser demasiado flexibles en caso de una ruptura anormal, ampliando las pérdidas.
Las medidas de respuesta al riesgo:
- Ajuste adecuadamente los parámetros de la línea media, o elija otro tipo de línea media.
- El objetivo es aumentar la cantidad de pérdidas y detenerlas en el momento oportuno.
- Añadir un factor multiplicador en el ATR, o ajustar el ciclo de revisión.
Dirección de optimización
- Prueba más tipos de medias para encontrar los mejores parámetros.
- Parámetros de ciclo ATR para la optimización de la pérdida.
- Prueba de los diferentes parámetros de los multiplicadores de la pérdida.
- Prueba de los diferentes coeficientes de riesgo de parálisis.
Resumir
Esta estrategia combina el uso de SSL para juzgar las tendencias y los indicadores de línea media para confirmar la entrada en el mercado, lo que permite un seguimiento eficaz de las tendencias. Ofrece una forma flexible de detener y detener los pérdidas, obteniendo mayores ganancias al mismo tiempo que controla el riesgo. Mediante la prueba y optimización continua de los parámetros, se puede obtener un mejor rendimiento comercial.
Código Fuente de la Estrategia
/*backtest
start: 2023-12-01 00:00:00
end: 2023-12-31 23:59:59
period: 1h
basePeriod: 15m
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/
// Thanks to @kevinmck100 for opensource strategy template and @Mihkel00 for SSL Hybrid
// @fpemehd
// @version=5
strategy(title = '[fpemehd] SSL Baseline Strategy',
shorttitle = '[f] SSL',
overlay = true)
// # ========================================================================= #
// # Inputs
// # ========================================================================= #
// 1. Time
i_start = input (defval = timestamp("20 Jan 1990 00:00 +0900"), title = "Start Date", tooltip = "Choose Backtest Start Date", inline = "Start Date", group = "Time" )
i_end = input (defval = timestamp("20 Dec 2030 00:00 +0900"), title = "End Date", tooltip = "Choose Backtest End Date", inline = "End Date", group = "Time" )
inDateRange = true
// 2. Inputs for direction: Long? Short? Both?
// i_longEnabled = input.bool(defval = true , title = "Long?", tooltip = "Enable Long Position Trade?", inline = "1", group = "Long / Short" )
// i_shortEnabled = input.bool(defval = true , title = "Short?", tooltip = "Enable Short Position Trade?", inline = "1", group = "Long / Short" )
// 3. Shared inputs for Long and Short
//// 3-1. Inputs for Stop Loss Type: ATR or Percent?
i_slType = input.string (defval = "ATR", title = "SL Type ", group = "Strategy: Stop Loss Conditions", options = ["Percent", "ATR", "Previous LL / HH"], tooltip = "Stop Loss based on %? ATR?", inline = "1")
i_slPercent = input.float (defval = 3, title = "SL % ", group = "Strategy: Stop Loss Conditions", inline = "2")
i_slAtrLength = input.int (14, "SL ATR Length ", group = "Strategy: Stop Loss Conditions", inline = "3", minval = 0, maxval = 10000)
i_slAtrMultiplier = input.float (4, "SL ATR Multiplier", group = "Strategy: Stop Loss Conditions", inline = "3", minval = 0, step = 0.1, tooltip = "Length of ATR used to calculate Stop Loss. \nSize of StopLoss is determined by multiplication of ATR value. Take Profit is derived from this also by multiplying the StopLoss value by the Risk:Reward multiplier.")
i_slLookBack = input.int(30, "Lowest Price Before Entry", group = "Strategy: Stop Loss Conditions", inline = "4", minval = 30, step = 1, tooltip = "Lookback to find the Lowest Price. \nStopLoss is determined by the Lowest price of the look back period. Take Profit is derived from this also by multiplying the StopLoss value by the Risk:Reward multiplier.")
//// 3-2. Inputs for Quantity & Risk Manangement: Take Profit
i_riskReward = input.float(2, "Risk : Reward Ratio ", group = "Strategy: Risk Management", inline = "1", minval = 0, step = 0.1, tooltip = "Previous high or low (long/short dependant) is used to determine TP level. 'Risk : Reward' ratio is then used to calculate SL based of previous high/low level.\n\nIn short, the higher the R:R ratio, the smaller the SL since TP target is fixed by previous high/low price data.")
i_accountRiskPercent = input.float(1, "Portfolio Risk %", group = "Strategy: Risk Management", inline = "1", minval = 0, step = 0.1, tooltip = "Percentage of portfolio you lose if trade hits SL.\n\nYou then stand to gain\n Portfolio Risk % * Risk : Reward\nif trade hits TP.")
// 4. Inputs for Drawings
i_showTpSlBoxes = input.bool(false, "Show TP / SL Boxes", group = "Strategy: Drawings", inline = "1", tooltip = "Show or hide TP and SL position boxes.\n\nNote: TradingView limits the maximum number of boxes that can be displayed to 500 so they may not appear for all price data under test.")
i_showLabels = input.bool(false, "Show Trade Exit Labels", group = "Strategy: Drawings", inline = "1", tooltip = "Useful labels to identify Profit/Loss and cumulative portfolio capital after each trade closes.\n\nAlso note that TradingView limits the max number of 'boxes' that can be displayed on a chart (max 500). This means when you lookback far enough on the chart you will not see the TP/SL boxes. However you can check this option to identify where trades exited.")
i_showDashboard = input.bool(false, "Show Dashboard", group = "Strategy: Drawings", inline = "1", tooltip = "Show Backtest Results")
i_show_color_bar = input.bool(false , "Color Bars", group = "Strategy: Drawings", inline = "1")
// 5. Inputs for Indicators
//// 5-1. Inputs for Indicator - 1: SSL Hybrid
i_useTrueRange = input.bool(defval = true , title = "use true range for Keltner Channel?", tooltip = "", inline = " ", group = "1: SSL Hybrid")
i_maType = input.string(defval='EMA', title='Baseline Type', options=['SMA', 'EMA', 'DEMA', 'TEMA', 'LSMA', 'WMA', 'MF', 'VAMA', 'TMA', 'HMA', 'JMA', 'Kijun v2', 'EDSMA', 'McGinley'],group = "1: SSL Hybrid")
i_len = input.int(defval=30,title='Baseline Length', group = "1: SSL Hybrid")
i_multy = input.float(0.2, step=0.05, title='Base Channel Multiplier', group = "1: SSL Hybrid")
// Input for Baseline
i_kidiv = input.int(defval=1, maxval=4, minval=0, title='Kijun MOD Divider',inline="Kijun v2", group="1: SSL Hybrid")
i_jurik_phase = input.int(defval=3, title='Baseline Type = JMA -> Jurik Phase', inline='JMA',group="1: SSL Hybrid")
i_jurik_power = input.int(defval=1, title='Baseline Type = JMA -> Jurik Power', inline='JMA',group="1: SSL Hybrid")
i_volatility_lookback = input.int(defval=10, title='Baseline Type = VAMA -> Volatility lookback length', inline='VAMA',group="1: SSL Hybrid")
// MF
i_beta = input.float(0.8, minval=0, maxval=1, step=0.1, title='Baseline Type = MF (Modular Filter, General Filter) ->Beta', inline='MF',group="1: SSL Hybrid")
i_feedback = input.bool(defval=false, title='Baseline Type = MF (Modular Filter) -> Use Feedback?', inline='MF',group="1: SSL Hybrid")
i_z = input.float(0.5, title='Baseline Type = MF (Modular Filter) -> Feedback Weighting', step=0.1, minval=0, maxval=1, inline='MF',group="1: SSL Hybrid")
// EDSMA
i_ssfLength = input.int(title='EDSMA - Super Smoother Filter Length', minval=1, defval=20, inline='EDSMA',group="1: SSL Hybrid")
i_ssfPoles = input.int(title='EDSMA - Super Smoother Filter Poles', defval=2, options=[2, 3], inline='EDSMA',group="1: SSL Hybrid")
// # ========================================================================= #
// # Functions for Stop Loss & Take Profit & Plots
// # ========================================================================= #
percentAsPoints(pcnt) =>
math.round(pcnt / 100 * close / syminfo.mintick)
calcStopLossPrice(pointsOffset, isLong) =>
priceOffset = pointsOffset * syminfo.mintick
if isLong
close - priceOffset
else
close + priceOffset
calcProfitTrgtPrice(pointsOffset, isLong) =>
calcStopLossPrice(-pointsOffset, isLong)
printLabel(barIndex, msg) => label.new(barIndex, close, msg)
printTpSlHitBox(left, right, slHit, tpHit, entryPrice, slPrice, tpPrice) =>
if i_showTpSlBoxes
box.new (left = left, top = entryPrice, right = right, bottom = slPrice, bgcolor = slHit ? color.new(color.red, 60) : color.new(color.gray, 90), border_width = 0)
box.new (left = left, top = entryPrice, right = right, bottom = tpPrice, bgcolor = tpHit ? color.new(color.green, 60) : color.new(color.gray, 90), border_width = 0)
line.new(x1 = left, y1 = entryPrice, x2 = right, y2 = entryPrice, color = color.new(color.yellow, 20))
line.new(x1 = left, y1 = slPrice, x2 = right, y2 = slPrice, color = color.new(color.red, 20))
line.new(x1 = left, y1 = tpPrice, x2 = right, y2 = tpPrice, color = color.new(color.green, 20))
printTpSlNotHitBox(left, right, entryPrice, slPrice, tpPrice) =>
if i_showTpSlBoxes
box.new (left = left, top = entryPrice, right = right, bottom = slPrice, bgcolor = color.new(color.gray, 90), border_width = 0)
box.new (left = left, top = entryPrice, right = right, bottom = tpPrice, bgcolor = color.new(color.gray, 90), border_width = 0)
line.new(x1 = left, y1 = entryPrice, x2 = right, y2 = entryPrice, color = color.new(color.yellow, 20))
line.new(x1 = left, y1 = slPrice, x2 = right, y2 = slPrice, color = color.new(color.red, 20))
line.new(x1 = left, y1 = tpPrice, x2 = right, y2 = tpPrice, color = color.new(color.green, 20))
printTradeExitLabel(x, y, posSize, entryPrice, pnl) =>
if i_showLabels
labelStr = "Position Size: " + str.tostring(math.abs(posSize), "#.##") + "\nPNL: " + str.tostring(pnl, "#.##") + "\nCapital: " + str.tostring(strategy.equity, "#.##") + "\nEntry Price: " + str.tostring(entryPrice, "#.##") + "\nExit Price: " + str.tostring(close,"#.##")
label.new(x = x, y = y, text = labelStr, color = pnl > 0 ? color.new(color.green, 60) : color.new(color.red, 60), textcolor = color.white, style = label.style_label_down)
f_fillCell(_table, _column, _row, _title, _value, _bgcolor, _txtcolor) =>
_cellText = _title + " " + _value
table.cell(_table, _column, _row, _cellText, bgcolor=_bgcolor, text_color=_txtcolor, text_size=size.auto)
// # ========================================================================= #
// # Entry, Close Logic
// # ========================================================================= #
// 1. Calculate Indicators
//// 1-1. Calculate Indicators for SSL Hybrid Baseline
////// TEMA
tema(src, len) =>
ema1 = ta.ema(src, len)
ema2 = ta.ema(ema1, len)
ema3 = ta.ema(ema2, len)
3 * ema1 - 3 * ema2 + ema3
////// EDSMA
get2PoleSSF(src, length) =>
PI = 2 * math.asin(1)
arg = math.sqrt(2) * PI / length
a1 = math.exp(-arg)
b1 = 2 * a1 * math.cos(arg)
c2 = b1
c3 = -math.pow(a1, 2)
c1 = 1 - c2 - c3
ssf = 0.0
ssf := c1 * src + c2 * nz(ssf[1]) + c3 * nz(ssf[2])
ssf
get3PoleSSF(src, length) =>
PI = 2 * math.asin(1)
arg = PI / length
a1 = math.exp(-arg)
b1 = 2 * a1 * math.cos(1.738 * arg)
c1 = math.pow(a1, 2)
coef2 = b1 + c1
coef3 = -(c1 + b1 * c1)
coef4 = math.pow(c1, 2)
coef1 = 1 - coef2 - coef3 - coef4
ssf = 0.0
ssf := coef1 * src + coef2 * nz(ssf[1]) + coef3 * nz(ssf[2]) + coef4 * nz(ssf[3])
ssf
ma(type, src, len) =>
float result = 0
if type == 'TMA'
result := ta.sma(ta.sma(src, math.ceil(len / 2)), math.floor(len / 2) + 1)
result
if type == 'MF'
ts = 0.
b = 0.
c = 0.
os = 0.
//----
alpha = 2 / (len + 1)
a = i_feedback ? i_z * src + (1 - i_z) * nz(ts[1], src) : src
//----
b := a > alpha * a + (1 - alpha) * nz(b[1], a) ? a : alpha * a + (1 - alpha) * nz(b[1], a)
c := a < alpha * a + (1 - alpha) * nz(c[1], a) ? a : alpha * a + (1 - alpha) * nz(c[1], a)
os := a == b ? 1 : a == c ? 0 : os[1]
//----
upper = i_beta * b + (1 - i_beta) * c
lower = i_beta * c + (1 - i_beta) * b
ts := os * upper + (1 - os) * lower
result := ts
result
if type == 'LSMA'
result := ta.linreg(src, len, 0)
result
if type == 'SMA' // Simple
result := ta.sma(src, len)
result
if type == 'EMA' // Exponential
result := ta.ema(src, len)
result
if type == 'DEMA' // Double Exponential
e = ta.ema(src, len)
result := 2 * e - ta.ema(e, len)
result
if type == 'TEMA' // Triple Exponential
e = ta.ema(src, len)
result := 3 * (e - ta.ema(e, len)) + ta.ema(ta.ema(e, len), len)
result
if type == 'WMA' // Weighted
result := ta.wma(src, len)
result
if type == 'VAMA' // Volatility Adjusted
/// Copyright © 2019 to present, Joris Duyck (JD)
mid = ta.ema(src, len)
dev = src - mid
vol_up = ta.highest(dev, i_volatility_lookback)
vol_down = ta.lowest(dev, i_volatility_lookback)
result := mid + math.avg(vol_up, vol_down)
result
if type == 'HMA' // Hull
result := ta.wma(2 * ta.wma(src, len / 2) - ta.wma(src, len), math.round(math.sqrt(len)))
result
if type == 'JMA' // Jurik
/// Copyright © 2018 Alex Orekhov (everget)
/// Copyright © 2017 Jurik Research and Consulting.
phaseRatio = i_jurik_phase < -100 ? 0.5 : i_jurik_phase > 100 ? 2.5 : i_jurik_phase / 100 + 1.5
beta = 0.45 * (len - 1) / (0.45 * (len - 1) + 2)
alpha = math.pow(beta, i_jurik_power)
jma = 0.0
e0 = 0.0
e0 := (1 - alpha) * src + alpha * nz(e0[1])
e1 = 0.0
e1 := (src - e0) * (1 - beta) + beta * nz(e1[1])
e2 = 0.0
e2 := (e0 + phaseRatio * e1 - nz(jma[1])) * math.pow(1 - alpha, 2) + math.pow(alpha, 2) * nz(e2[1])
jma := e2 + nz(jma[1])
result := jma
result
if type == 'Kijun v2'
kijun = math.avg(ta.lowest(len), ta.highest(len)) //, (open + close)/2)
conversionLine = math.avg(ta.lowest(len / i_kidiv), ta.highest(len / i_kidiv))
delta = (kijun + conversionLine) / 2
result := delta
result
if type == 'McGinley'
mg = 0.0
mg := na(mg[1]) ? ta.ema(src, len) : mg[1] + (src - mg[1]) / (len * math.pow(src / mg[1], 4))
result := mg
result
if type == 'EDSMA'
zeros = src - nz(src[2])
avgZeros = (zeros + zeros[1]) / 2
// Ehlers Super Smoother Filter
ssf = i_ssfPoles == 2 ? get2PoleSSF(avgZeros, i_ssfLength) : get3PoleSSF(avgZeros, i_ssfLength)
// Rescale filter in terms of Standard Deviations
stdev = ta.stdev(ssf, len)
scaledFilter = stdev != 0 ? ssf / stdev : 0
alpha = 5 * math.abs(scaledFilter) / len
edsma = 0.0
edsma := alpha * src + (1 - alpha) * nz(edsma[1])
result := edsma
result
result
////// Keltner Baseline Channel (Baseline)
BBMC = ma(i_maType, close, i_len)
Keltma = ma(i_maType, close, i_len)
range_1 = i_useTrueRange ? ta.tr : high - low
rangema = ta.ema(range_1, i_len)
upperk = Keltma + rangema * i_multy
lowerk = Keltma - rangema * i_multy
// 2. Entry Condition for Long and Short
// Condition 1
bullSSL = close > upperk
bearSSL = close < lowerk
// Enter Position based on Condition 1
goLong = inDateRange and bullSSL
goShort = inDateRange and bearSSL
// # ========================================================================= #
// # Position Control Logic (Entry & Exit)
// # ========================================================================= #
// 1. Trade entry and exit variables
var tradeEntryBar = bar_index
var profitPoints = 0.
var lossPoints = 0.
var slPrice = 0.
var tpPrice = 0.
var inLong = false
var inShort = false
// 2. Entry decisions
openLong = (goLong and not inLong) // Long entry condition & not in long position
openShort = (goShort and not inShort) // Short entry condition & not in short position
flippingSides = (goLong and inShort) or (goShort and inLong) // (Long entry condition & in short position) and the opposite
enteringTrade = openLong or openShort // Entering Long or Short Condition
inTrade = inLong or inShort
// 3. Stop Loss & Take Profit Percent
lowestLow = ta.lowest(source = low, length = i_slLookBack)
highestHigh = ta.highest(source = high, length = i_slLookBack)
llhhSLPercent = openLong ? math.abs((close - lowestLow) / close) * 100 : openShort ? math.abs((highestHigh - close) / close) * 100 : na
atr = ta.atr(i_slAtrLength)
slAmount = atr * i_slAtrMultiplier
slPercent = i_slType == 'ATR' ? math.abs((1 - (close - slAmount) / close) * 100) : i_slType == 'Percent' ? i_slPercent : llhhSLPercent
tpPercent = slPercent * i_riskReward
// 4. Risk calculations & Quantity Management
riskAmt = strategy.equity * i_accountRiskPercent / 100
entryQty = math.abs(riskAmt / slPercent * 100) / close
// 5. Open Position
if openLong
if strategy.position_size < 0
printTpSlNotHitBox(tradeEntryBar + 1, bar_index + 1, strategy.position_avg_price, slPrice, tpPrice)
printTradeExitLabel(bar_index + 1, math.max(tpPrice, slPrice), strategy.position_size, strategy.position_avg_price, strategy.openprofit)
strategy.entry("Long", strategy.long, qty = entryQty, alert_message = "Long Entry")
enteringTrade := true
inLong := true
inShort := false
if openShort
if strategy.position_size > 0
printTpSlNotHitBox(tradeEntryBar + 1, bar_index + 1, strategy.position_avg_price, slPrice, tpPrice)
printTradeExitLabel(bar_index + 1, math.max(tpPrice, slPrice), strategy.position_size, strategy.position_avg_price, strategy.openprofit)
strategy.entry("Short", strategy.short, qty = entryQty, alert_message = "Short Entry")
enteringTrade := true
inShort := true
inLong := false
if enteringTrade
profitPoints := percentAsPoints(tpPercent)
lossPoints := percentAsPoints(slPercent)
slPrice := calcStopLossPrice(lossPoints, openLong)
tpPrice := calcProfitTrgtPrice(profitPoints, openLong)
tradeEntryBar := bar_index
// Can add more take profit Actions
strategy.exit("TP/SL", profit = profitPoints, loss = lossPoints, comment_profit = "TP Hit", comment_loss = "SL Hit", alert_profit = "TP Hit Alert", alert_loss = "SL Hit Alert")
// # ========================================================================= #
// # Plots (Bar Color, Plot, Label, Boxes)
// # ========================================================================= #
// 1. SSL Hybrid Baseline
longColor = #00c3ff
shortColor = #ff0062
color_bar = close > upperk ? longColor : close < lowerk ? shortColor : color.gray
p1 = plot(BBMC, color=color.new(color=color_bar, transp=0), linewidth=4, title='MA Baseline')
// 2. Bar color Based On SSL Hybrid Baseline
barcolor(i_show_color_bar ? color_bar : na)
up_channel = plot(upperk, color=color_bar, title='Baseline Upper Channel')
low_channel = plot(lowerk, color=color_bar, title='Basiline Lower Channel')
fill(up_channel, low_channel, color.new(color=color_bar, transp=90))
// 3. Stoploss Boxes
slHit = (inShort and high >= slPrice) or (inLong and low <= slPrice)
tpHit = (inLong and high >= tpPrice) or (inShort and low <= tpPrice)
exitTriggered = slHit or tpHit
entryPrice = strategy.closedtrades.entry_price (strategy.closedtrades - 1)
pnl = strategy.closedtrades.profit (strategy.closedtrades - 1)
posSize = strategy.closedtrades.size (strategy.closedtrades - 1)
if (inTrade and exitTriggered)
inShort := false
inLong := false
printTpSlHitBox(tradeEntryBar + 1, bar_index, slHit, tpHit, entryPrice, slPrice, tpPrice)
printTradeExitLabel(bar_index, math.max(tpPrice, slPrice), posSize, entryPrice, pnl)
if barstate.islastconfirmedhistory and strategy.position_size != 0
printTpSlNotHitBox(tradeEntryBar + 1, bar_index + 1, strategy.position_avg_price, slPrice, tpPrice)
// 4. Data Windows
plotchar(slPrice, "Stop Loss Price", "")
plotchar(tpPrice, "Take Profit Price", "")
// 5. Showing Labels
plotDebugLabels = false
if plotDebugLabels
if bar_index == tradeEntryBar
printLabel(bar_index, "Position size: " + str.tostring(entryQty * close, "#.##"))
// 6. Showing Dashboard
if i_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)