OPEN-SOURCE SCRIPT
RSI OB/OS THEDU 999

//version=6
indicator("RSI OB/OS THEDU 999", overlay=false)
//#region Inputs Section
// ================================
// Inputs Section
// ================================
// Time Settings Inputs
startTime = input.time(timestamp("1 Jan 1900"), "Start Time", group="Time Settings")
endTime = input.time(timestamp("1 Jan 2099"), "End Time", group="Time Settings")
isTimeWindow = time >= startTime and time <= endTime
// Table Settings Inputs
showTable = input.bool(true, "Show Table", group="Table Settings")
fontSize = input.string("Auto", "Font Size", options=["Auto", "Small", "Normal", "Large"], group="Table Settings")
// Strategy Settings Inputs
tradeDirection = input.string("Long", "Trade Direction", options=["Long", "Short"], group="Strategy Settings")
entryStrategy = input.string("Revert Cross", "Entry Strategy", options=["Cross Threshold", "Revert Cross"], group="Strategy Settings")
barLookback = input.int(10, "Bar Lookback", minval=1, maxval=20, group="Strategy Settings")
// RSI Settings Inputs
rsiPeriod = input.int(14, "RSI Period", minval=1, group="RSI Settings")
overboughtLevel = input.int(70, "Overbought Level", group="RSI Settings")
oversoldLevel = input.int(30, "Oversold Level", group="RSI Settings")
//#endregion
//#region Font Size Mapping
// ================================
// Font Size Mapping
// ================================
fontSizeMap = fontSize == "Auto" ? size.auto : fontSize == "Small" ? size.small : fontSize == "Normal" ? size.normal : fontSize == "Large" ? size.large : na
//#endregion
//#region RSI Calculation
// ================================
// RSI Calculation
// ================================
rsiValue = ta.rsi(close, rsiPeriod)
plot(rsiValue, "RSI", color=color.yellow)
hline(overboughtLevel, "OB Level", color=color.gray)
hline(oversoldLevel, "OS Level", color=color.gray)
//#endregion
//#region Entry Conditions
// ================================
// Entry Conditions
// ================================
buyCondition = entryStrategy == "Revert Cross" ? ta.crossover(rsiValue, oversoldLevel) : ta.crossunder(rsiValue, oversoldLevel)
sellCondition = entryStrategy == "Revert Cross" ? ta.crossunder(rsiValue, overboughtLevel) : ta.crossover(rsiValue, overboughtLevel)
// Plotting buy/sell signals
plotshape(buyCondition ? oversoldLevel : na, title="Buy", location=location.absolute, color=color.green, style=shape.labelup, text="BUY", textcolor=color.white, size=size.small)
plotshape(sellCondition ? overboughtLevel : na, title="Sell", location=location.absolute, color=color.red, style=shape.labeldown, text="SELL", textcolor=color.white, size=size.small)
// Plotting buy/sell signals on the chart
plotshape(buyCondition, title="Buy", location=location.belowbar, color=color.green, style=shape.triangleup, text="BUY", textcolor=color.white, size=size.small , force_overlay = true)
plotshape(sellCondition, title="Sell", location=location.abovebar, color=color.red, style=shape.triangledown, text="SELL", textcolor=color.white, size=size.small, force_overlay = true)
//#endregion
//#region Returns Matrix Calculation
// ================================
// Returns Matrix Calculation
// ================================
var returnsMatrix = matrix.new<float>(0, barLookback, 0.0)
if (tradeDirection == "Long" ? buyCondition[barLookback] : sellCondition[barLookback]) and isTimeWindow
newRow = array.new_float(barLookback)
for i = 0 to barLookback - 1
entryPrice = close[barLookback]
futurePrice = close[barLookback - 1 - i]
ret = (futurePrice - entryPrice) / entryPrice * 100
array.set(newRow, i, math.round(ret, 4))
matrix.add_row(returnsMatrix, matrix.rows(returnsMatrix), newRow)
//#endregion
//#region Display Table
// ================================
// Display Table
// ================================
var table statsTable = na
if barstate.islastconfirmedhistory and showTable
statsTable := table.new(position.top_right, barLookback + 1, 4, border_width=1, force_overlay=true)
// Table Headers
table.cell(statsTable, 0, 1, "Win Rate %", bgcolor=color.rgb(45, 45, 48), text_color=color.white, text_size=fontSizeMap)
table.cell(statsTable, 0, 2, "Mean Return %", bgcolor=color.rgb(45, 45, 48), text_color=color.white, text_size=fontSizeMap)
table.cell(statsTable, 0, 3, "Median Return %", bgcolor=color.rgb(45, 45, 48), text_color=color.white, text_size=fontSizeMap)
// Row Headers
for i = 1 to barLookback
table.cell(statsTable, i, 0, str.format("{0} Bar Return", i), bgcolor=color.rgb(45, 45, 48), text_color=color.white, text_size=fontSizeMap)
// Calculate Statistics
meanReturns = array.new_float()
medianReturns = array.new_float()
for col = 0 to matrix.columns(returnsMatrix) - 1
colData = matrix.col(returnsMatrix, col)
array.push(meanReturns, array.avg(colData))
array.push(medianReturns, array.median(colData))
// Populate Table
for col = 0 to matrix.columns(returnsMatrix) - 1
colData = matrix.col(returnsMatrix, col)
positiveCount = 0
for val in colData
if val > 0
positiveCount += 1
winRate = positiveCount / array.size(colData)
meanRet = array.avg(colData)
medianRet = array.median(colData)
// Color Logic
winRateColor = winRate == 0.5 ? color.rgb(58, 58, 60) : (winRate > 0.5 ? color.rgb(76, 175, 80) : color.rgb(244, 67, 54))
meanBullCol = color.from_gradient(meanRet, 0, array.max(meanReturns), color.rgb(76, 175, 80), color.rgb(0, 128, 0))
meanBearCol = color.from_gradient(meanRet, array.min(meanReturns), 0, color.rgb(255, 0, 0), color.rgb(255, 99, 71))
medianBullCol = color.from_gradient(medianRet, 0, array.max(medianReturns), color.rgb(76, 175, 80), color.rgb(0, 128, 0))
medianBearCol = color.from_gradient(medianRet, array.min(medianReturns), 0, color.rgb(255, 0, 0), color.rgb(255, 99, 71))
table.cell(statsTable, col + 1, 1, str.format("{0,number,#.##%}", winRate), text_color=color.white, bgcolor=winRateColor, text_size=fontSizeMap)
table.cell(statsTable, col + 1, 2, str.format("{0,number,#.###}%", meanRet), text_color=color.white, bgcolor=meanRet > 0 ? meanBullCol : meanBearCol, text_size=fontSizeMap)
table.cell(statsTable, col + 1, 3, str.format("{0,number,#.###}%", medianRet), text_color=color.white, bgcolor=medianRet > 0 ? medianBullCol : medianBearCol, text_size=fontSizeMap)
//#endregion
// Background color for OB/OS regions
bgcolor(rsiValue >= overboughtLevel ? color.new(color.red, 90) : rsiValue <= oversoldLevel ? color.new(color.green, 90) : na)
indicator("RSI OB/OS THEDU 999", overlay=false)
//#region Inputs Section
// ================================
// Inputs Section
// ================================
// Time Settings Inputs
startTime = input.time(timestamp("1 Jan 1900"), "Start Time", group="Time Settings")
endTime = input.time(timestamp("1 Jan 2099"), "End Time", group="Time Settings")
isTimeWindow = time >= startTime and time <= endTime
// Table Settings Inputs
showTable = input.bool(true, "Show Table", group="Table Settings")
fontSize = input.string("Auto", "Font Size", options=["Auto", "Small", "Normal", "Large"], group="Table Settings")
// Strategy Settings Inputs
tradeDirection = input.string("Long", "Trade Direction", options=["Long", "Short"], group="Strategy Settings")
entryStrategy = input.string("Revert Cross", "Entry Strategy", options=["Cross Threshold", "Revert Cross"], group="Strategy Settings")
barLookback = input.int(10, "Bar Lookback", minval=1, maxval=20, group="Strategy Settings")
// RSI Settings Inputs
rsiPeriod = input.int(14, "RSI Period", minval=1, group="RSI Settings")
overboughtLevel = input.int(70, "Overbought Level", group="RSI Settings")
oversoldLevel = input.int(30, "Oversold Level", group="RSI Settings")
//#endregion
//#region Font Size Mapping
// ================================
// Font Size Mapping
// ================================
fontSizeMap = fontSize == "Auto" ? size.auto : fontSize == "Small" ? size.small : fontSize == "Normal" ? size.normal : fontSize == "Large" ? size.large : na
//#endregion
//#region RSI Calculation
// ================================
// RSI Calculation
// ================================
rsiValue = ta.rsi(close, rsiPeriod)
plot(rsiValue, "RSI", color=color.yellow)
hline(overboughtLevel, "OB Level", color=color.gray)
hline(oversoldLevel, "OS Level", color=color.gray)
//#endregion
//#region Entry Conditions
// ================================
// Entry Conditions
// ================================
buyCondition = entryStrategy == "Revert Cross" ? ta.crossover(rsiValue, oversoldLevel) : ta.crossunder(rsiValue, oversoldLevel)
sellCondition = entryStrategy == "Revert Cross" ? ta.crossunder(rsiValue, overboughtLevel) : ta.crossover(rsiValue, overboughtLevel)
// Plotting buy/sell signals
plotshape(buyCondition ? oversoldLevel : na, title="Buy", location=location.absolute, color=color.green, style=shape.labelup, text="BUY", textcolor=color.white, size=size.small)
plotshape(sellCondition ? overboughtLevel : na, title="Sell", location=location.absolute, color=color.red, style=shape.labeldown, text="SELL", textcolor=color.white, size=size.small)
// Plotting buy/sell signals on the chart
plotshape(buyCondition, title="Buy", location=location.belowbar, color=color.green, style=shape.triangleup, text="BUY", textcolor=color.white, size=size.small , force_overlay = true)
plotshape(sellCondition, title="Sell", location=location.abovebar, color=color.red, style=shape.triangledown, text="SELL", textcolor=color.white, size=size.small, force_overlay = true)
//#endregion
//#region Returns Matrix Calculation
// ================================
// Returns Matrix Calculation
// ================================
var returnsMatrix = matrix.new<float>(0, barLookback, 0.0)
if (tradeDirection == "Long" ? buyCondition[barLookback] : sellCondition[barLookback]) and isTimeWindow
newRow = array.new_float(barLookback)
for i = 0 to barLookback - 1
entryPrice = close[barLookback]
futurePrice = close[barLookback - 1 - i]
ret = (futurePrice - entryPrice) / entryPrice * 100
array.set(newRow, i, math.round(ret, 4))
matrix.add_row(returnsMatrix, matrix.rows(returnsMatrix), newRow)
//#endregion
//#region Display Table
// ================================
// Display Table
// ================================
var table statsTable = na
if barstate.islastconfirmedhistory and showTable
statsTable := table.new(position.top_right, barLookback + 1, 4, border_width=1, force_overlay=true)
// Table Headers
table.cell(statsTable, 0, 1, "Win Rate %", bgcolor=color.rgb(45, 45, 48), text_color=color.white, text_size=fontSizeMap)
table.cell(statsTable, 0, 2, "Mean Return %", bgcolor=color.rgb(45, 45, 48), text_color=color.white, text_size=fontSizeMap)
table.cell(statsTable, 0, 3, "Median Return %", bgcolor=color.rgb(45, 45, 48), text_color=color.white, text_size=fontSizeMap)
// Row Headers
for i = 1 to barLookback
table.cell(statsTable, i, 0, str.format("{0} Bar Return", i), bgcolor=color.rgb(45, 45, 48), text_color=color.white, text_size=fontSizeMap)
// Calculate Statistics
meanReturns = array.new_float()
medianReturns = array.new_float()
for col = 0 to matrix.columns(returnsMatrix) - 1
colData = matrix.col(returnsMatrix, col)
array.push(meanReturns, array.avg(colData))
array.push(medianReturns, array.median(colData))
// Populate Table
for col = 0 to matrix.columns(returnsMatrix) - 1
colData = matrix.col(returnsMatrix, col)
positiveCount = 0
for val in colData
if val > 0
positiveCount += 1
winRate = positiveCount / array.size(colData)
meanRet = array.avg(colData)
medianRet = array.median(colData)
// Color Logic
winRateColor = winRate == 0.5 ? color.rgb(58, 58, 60) : (winRate > 0.5 ? color.rgb(76, 175, 80) : color.rgb(244, 67, 54))
meanBullCol = color.from_gradient(meanRet, 0, array.max(meanReturns), color.rgb(76, 175, 80), color.rgb(0, 128, 0))
meanBearCol = color.from_gradient(meanRet, array.min(meanReturns), 0, color.rgb(255, 0, 0), color.rgb(255, 99, 71))
medianBullCol = color.from_gradient(medianRet, 0, array.max(medianReturns), color.rgb(76, 175, 80), color.rgb(0, 128, 0))
medianBearCol = color.from_gradient(medianRet, array.min(medianReturns), 0, color.rgb(255, 0, 0), color.rgb(255, 99, 71))
table.cell(statsTable, col + 1, 1, str.format("{0,number,#.##%}", winRate), text_color=color.white, bgcolor=winRateColor, text_size=fontSizeMap)
table.cell(statsTable, col + 1, 2, str.format("{0,number,#.###}%", meanRet), text_color=color.white, bgcolor=meanRet > 0 ? meanBullCol : meanBearCol, text_size=fontSizeMap)
table.cell(statsTable, col + 1, 3, str.format("{0,number,#.###}%", medianRet), text_color=color.white, bgcolor=medianRet > 0 ? medianBullCol : medianBearCol, text_size=fontSizeMap)
//#endregion
// Background color for OB/OS regions
bgcolor(rsiValue >= overboughtLevel ? color.new(color.red, 90) : rsiValue <= oversoldLevel ? color.new(color.green, 90) : na)
Skrip sumber terbuka
Dalam semangat sebenar TradingView, pencipta skrip ini telah menjadikannya sumber terbuka supaya pedagang dapat menilai dan mengesahkan kefungsiannya. Terima kasih kepada penulis! Walaupun anda boleh menggunakannya secara percuma, ingat bahawa menerbitkan semula kod ini adalah tertakluk kepada Peraturan Dalaman kami.
Penafian
Maklumat dan penerbitan adalah tidak dimaksudkan untuk menjadi, dan tidak membentuk, nasihat untuk kewangan, pelaburan, perdagangan dan jenis-jenis lain atau cadangan yang dibekalkan atau disahkan oleh TradingView. Baca dengan lebih lanjut di Terma Penggunaan.
Skrip sumber terbuka
Dalam semangat sebenar TradingView, pencipta skrip ini telah menjadikannya sumber terbuka supaya pedagang dapat menilai dan mengesahkan kefungsiannya. Terima kasih kepada penulis! Walaupun anda boleh menggunakannya secara percuma, ingat bahawa menerbitkan semula kod ini adalah tertakluk kepada Peraturan Dalaman kami.
Penafian
Maklumat dan penerbitan adalah tidak dimaksudkan untuk menjadi, dan tidak membentuk, nasihat untuk kewangan, pelaburan, perdagangan dan jenis-jenis lain atau cadangan yang dibekalkan atau disahkan oleh TradingView. Baca dengan lebih lanjut di Terma Penggunaan.