动态网格交易策略

/*backtest
start: 2023-02-19 00:00:00
end: 2024-02-01 05:20:00
period: 1d
basePeriod: 1h
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/
// © AssassinsGrid

// Embark on an automated grid-based trading journey with this Pine script tailored for backtesting in TradingView using strategy.orders().
// Whether you're a seasoned trader or new to the world of financial markets, this script is designed to enhance your trading experience across various assets.
// It's essential to note that while powerful, this script may have a slightly delayed execution compared to the original Assassin's Grid due to the nature of strategy.orders() and strategy.close() functions,
// which execute on the following bar after the price crosses the grid.
//
// Key Features:
//
// 📊 Dynamic Grid Configuration: Define the grid type, width, and pivot point resolution to adapt to market dynamics.
//
// 📈 Smart Buy Strategies: Choose from various buy types, set quantities, and control the number of buy positions based on market trends.
//
// 💹 Strategic Selling: Optimize sell strategies with flexible options, including setting quantities, controlling sell positions, and defining loss thresholds.
//
// 🌐 Versatile Trading: Select between spot and margin trading modes, offering flexibility for diverse trading preferences.
//
// ⚙️ Detailed Configuration: Fine-tune your strategy with parameters like initial capital, commission values, margin rates, and more.
//
// 📊 Informative Chart Elements: Visualize critical information with adjustable labels, table size, grid visibility, and an insightful information panel.
//
// Conclusion:
//
// Whether you're a seasoned trader or a trading enthusiast exploring markets beyond cryptocurrencies, this Pine script provides a robust framework for testing and refining your strategies.
// While powerful, be aware that the execution may have a slight delay compared to the original Assassin's Grid.
// Dive into the dynamic world of grid-based trading, explore various configurations, and refine your approach across a spectrum of financial assets. Happy trading! 🚀💰

//@version=5
strategy("Assassin's Grid B",  shorttitle = "AAGG📈", overlay = true, max_labels_count = 500, initial_capital = 10000, default_qty_value = 0, process_orders_on_close = true)

// INPUTS

// Grid parameters
WOption                     = input.string('Geometric (% Fall)',    'Width Type', ['Arithmetic (Price)', 'Geometric (% Sell)', 'Geometric (% Fall)'],  group = "GRID", tooltip = "Select the type of width for the grid:\n\n- Arithmetic (Price): Fixed width in price units, maintaining constant separation on the chart.\n\n- Geometric (% Sell): Width based on a percentage of the sell price, dynamically adjusting grid lines. (Typically between 5-15%)\n\n- Geometric (% Fall): Width based on a percentage of potential market decline from the last sale, helping visualize potential drops. (Usually between 40-80%)")
Width                       = input.float(75,                       'Width Parameter', minval = 0, step = 0.5, group = "GRID", tooltip = "Set the width parameter for the grid. Larger values result in wider grid lines.")
ppPeriod                    = input.string('4W',                    'Pivot Point Resolution', group = "GRID", tooltip = "Set the resolution for the Pivot Point. Type a timeframe that suits your trading style: 'H, D, W, M'")
MARes                       = input.timeframe('D',                  'EMA Resolution', group = "GRID", tooltip = "Set the resolution for the Exponential Moving Average (EMA). Choose a timeframe that suits your analysis.")
MALength                    = input.int(100,                        'MA Length', minval = 1, group = "GRID", tooltip = "Set the length for the Moving Average (MA). This affects the responsiveness of the MA to price changes.")

// Buy
BuyType                     = input.string('Cash / n Buys',         'Buy Type', ['Contracts', 'Cash', '% Cash', 'Cash / n Buys', 'Cash / n Buys +'], group = "BUY", tooltip = "Select the type of buy: \n- Contracts: Specify the number of contracts to buy. \n- Cash: Specify the amount of cash to invest. \n- % Cash: Specify the percentage of available cash to invest. \n- Cash / n Buys: Distribute available cash equally across n buy positions. \n- Cash / n Buys +: Similar to Cash / n Buys, but the quantity on each buy increases proportionally with the buy number.")
BuyQ                        = input.float(10.0,                     'Contracts / Cash / % Cash', minval = 0, group = "BUY", tooltip = "Set the quantity for buy. For 'Contracts' mode, it represents the number of contracts to buy. For 'Cash' and '% Cash' modes, it represents the amount to invest or the percentage of cash to invest, respectively.")
NBuysUp                     = input.int(4,                          'N Buys over MA', minval = 1, maxval = 30, group = "BUY", tooltip = "Set the maximum number of buy positions allowed above the Moving Average (MA). This helps control the number of buys in an uptrend.")
NBuysDown                   = input.int(5,                          'N Buys under MA (Max.)', minval = 1, maxval = 30, group = "BUY", tooltip = "Set the maximum number of buy positions allowed below the Moving Average (MA). This helps control the number of buys in a downtrend.")
LastXtrades                 = input.int(2,                          'Buy all in last Trades', minval = 0, maxval = 10, group = "BUY", tooltip = "Set the number of the most recent buy trades to consider for making a buy decision. For the '% Cash' option only, this setting enables buying all available cash in the last specified number of trades.")

// Sel
SellType                    = input.string('Position / n Sells +',  'Sell Type', ['Contracts', 'Cash', '% Position', 'Position / n Sells', 'Position / n Sells +'], group = "SELL", tooltip = "Select the type of sell: \n- Contracts: Specify the number of contracts to sell. \n- Cash: Specify the amount of cash to disinvest. \n- % Position: Specify the percentage of the position to sell. \n- Position / n Sells: Distribute the position equally across n sell positions. \n- Position / n Sells +: Similar to Position / n Sells, but the quantity on each sell increases proportionally with the sell number.")
SellQ                       = input.float(5.0,                      'Contracts / Cash / % Position', minval = 0, group = "SELL", tooltip = "Set the quantity for sell. For 'Contracts' mode, it represents the number of contracts to sell. For 'Cash' and '% Position' modes, it represents the amount to disinvest or the percentage of the position to sell, respectively.")
NSellsUp                    = input.int(20,                         'N Sells over MA (Max.)', minval = 1, maxval = 30, group = "SELL", tooltip = "Set the maximum number of sell positions allowed above the Moving Average (MA). This helps control the number of sells in an uptrend.")
NSellsDown                  = input.int(4,                          'N Sells under MA', minval = 1, maxval = 30, group = "SELL", tooltip = "Set the maximum number of sell positions allowed below the Moving Average (MA). This helps control the number of sells in a downtrend.")
LossAllowed                 = input.string('Never',                 'Loss Allowed', ['Never', 'Last buy', 'Always'], group = "SELL", tooltip = "Set the loss allowed criteria: \n- Never: No loss allowed for selling. \n- Last buy: Allow selling if the current price is above the price of the last buy. \n- Always: Allow selling at any price.")

// Trading
TradingType                 = input.string('Spot',                  'Trading Type', ['Spot', 'Margin'], group = "TRADING", tooltip = "Select the type of trading: \n- Spot: Regular trading without margin. \n- Margin: Trading with margin, allowing for leveraged positions.")
InitialContracts            = input.float(10.0,                     '% Initial Capital 1st Trade', minval = 1, maxval = 100, group = "TRADING", tooltip = "Set the percentage of the initial capital to be used for the first trade. This determines the position size for the first trade.") / 100
CommissionValue             = input.float(0.1,                      '% Commission Value', minval = 0, maxval = 100, step = 0.1, group = "TRADING", tooltip = "Set the percentage of the trade value to be considered as a commission. This is deducted from the trading capital.") / 100
MarginRate                  = input.float(1.0,                      '% Margin Rate', minval = 0, maxval = 100, step = 0.5, group = "TRADING", tooltip = "Set the percentage of margin rate to be applied. This is relevant only in margin trading scenarios.") / 100
StartDate                   = timestamp('01 Jan 1970 00:00 +000')
testPeriodStart             = input(StartDate,                 'Start of Trading', group = "TRADING", tooltip = "Set the start date for trading. The strategy will start evaluating trades from this date onwards.")
TableSizeInput              = input.string('Small',                 'Table Size', ['Auto', 'Tiny', 'Small', 'Normal', 'Large', 'Huge'], group = "PLOTTING", tooltip = "Set the size of the information table. Choose a size that suits your preference.")
ShowGrid                    = input(true,                           'Level Grid', group = "PLOTTING", tooltip = "Show or hide the level grid on the chart. The grid represents price levels.")
ShowPanel                   = input(false,                           'Information Panel', group = "PLOTTING", tooltip = "Show or hide the information panel on the chart. The panel displays key information about the strategy and current market conditions.")
ShowLiquidationPrice        = input(false,                          'Liquidation Price', group = "PLOTTING", tooltip = "Show or hide the liquidation price on the chart. The liquidation price is the level at which liquidation may occur, if applicable.")

// VARIABLES

// Grid levels on buys
var float _ldown            = na
bool _pb                    = false
bool _buy                   = false

// Grid levels on sells
var float _lup              = na
bool _ps                    = false
bool _sell                  = false

// First Buy
CloseFirstBar               = ta.valuewhen(bar_index == 0, open, 0)
TimeFirstBar                = ta.valuewhen(bar_index == 0, time, 0)
CloseStart                  = ta.valuewhen(time <= testPeriodStart, open, 0)
FirstClose                  = testPeriodStart > TimeFirstBar ? CloseStart : CloseFirstBar
TimeFirstClose              = testPeriodStart > TimeFirstBar ? testPeriodStart : TimeFirstBar

// Buy and Sell prices 
var float FinalBuyPrice     = na
var float FinalSellPrice    = na
var float FinalOpenPrice    = na
var float BuyLimitPrice     = na
var float SellLimitPrice    = na

// Number of trades
var int nBuys               = na
nBuys                       := nz(nBuys[1])
var int nSells              = na
nSells                      := nz(nSells[1])
var int NBuys               = NBuysDown
var int NSells              = NSellsDown

// Quantities
var float BuyQuantity       = 0
var float BuyAmount         = 0
var float SellQuantity      = 0
var float SellAmount        = 0
var float Commission        = 0
var float Gains             = 0
var float Losses            = 0

// Position calculation
var float PositionCash      = 0
var float PositionSize      = 0
var int BarIndex            = 0

// Average Price Calculation
var float AvgPrice          = 0
var float hl2Bar            = 0

// Backtest information
var float Balance           = 500000
var float Equity            = 0
var float RealizedPnL       = 0
var float PRealizedPnL      = 0
var float Floating          = 0
var float PFloating         = 0
var float URealizedPnL      = 0
var float PURealizedPnL     = 0
var float Cash              = Balance
var float Margin            = 0
var float BuyAndHold        = 0
var float PBuyAndHold       = 0
var float CLeverage         = 0
var float LiquidationPrice  = 0
var bool  Liquidation       = false
var float ProfitFactor      = 0
var int TradingTime         = 0

// Fibonacci Pivots level calculation
var float PP                = open

// Information panel
label labelBalance          = na

// Analyzing when the period changes
bool PeriodChange           = false

// Grid with arrays
aDown                       = array.new_float(30)
aUp                         = array.new_float(30)
aBuy                        = array.new_bool(30)
aSell                       = array.new_bool(30)

// Labels size
fTextSize(_SizeInput)=>
    if _SizeInput == 'Auto'
        size.auto
    else if _SizeInput == 'Tiny'
        size.tiny
    else if _SizeInput == 'Small'
        size.small
    else if _SizeInput == 'Normal'
        size.normal
    else if _SizeInput == 'Normal'
        size.normal
    else if _SizeInput == 'Large'
        size.large
    else if _SizeInput == 'Huge'
        size.huge

// Variable reference
var float MaxFinalOpenPrice = FirstClose

// Value of the MA
var float sMAValue          = na

// GRID

// Function to calculate the Width
fWidth(_Width) =>

    // If price is constant
    if WOption == 'Arithmetic (Price)'
        _Width

    // If price is the Max % of the next Sell
    else if WOption == 'Geometric (% Sell)'
        MaxFinalOpenPrice * (_Width / 100)
    
    // If price is a part of the % of the maximum fall
    else if WOption == 'Geometric (% Fall)'
        MaxFinalOpenPrice / NBuysDown * (_Width / 100)
        
// Origin from Rounded Pivot Points or last Sell
fDownGrid(_GridWidth) =>

    if na(FinalOpenPrice)
        FirstClose
    else
        if FinalSellPrice <= PP
            if PositionSize > 0
                if na(FinalBuyPrice)
                    if WOption == 'Arithmetic (Price)'
                        (math.floor(FinalSellPrice / _GridWidth) * _GridWidth) - _GridWidth
                    else
                        FinalSellPrice - _GridWidth
                else
                    FinalBuyPrice - _GridWidth

            else if PositionSize == 0
                if WOption == 'Arithmetic (Price)'
                    (math.floor(PP / _GridWidth) * _GridWidth) - _GridWidth
                else
                    PP
        else
            if na(FinalBuyPrice)
                if WOption == 'Arithmetic (Price)'
                    (math.floor(PP / _GridWidth) * _GridWidth) - _GridWidth
                else
                    if (FinalSellPrice - _GridWidth) > PP
                        PP
                    else
                        (FinalSellPrice - _GridWidth)
            else
                FinalBuyPrice - _GridWidth
        
// Origin for sells from Rounded Position Price
fUpGrid(_GridWidth) =>
    
    if na(FinalSellPrice)
        if LossAllowed == 'Never'
            if WOption == 'Arithmetic (Price)'
                math.ceil(math.max(AvgPrice, (FinalBuyPrice + _GridWidth)) / _GridWidth) * _GridWidth
            else
                math.max(AvgPrice, (FinalBuyPrice + _GridWidth))
            
        else if LossAllowed == 'Last buy'
            if nBuys == NBuys
                FinalBuyPrice + _GridWidth
            else
                if WOption == 'Arithmetic (Price)'
                    math.ceil(math.max(AvgPrice, (FinalBuyPrice + _GridWidth)) / _GridWidth) * _GridWidth
                else
                    math.max(AvgPrice, (FinalBuyPrice + _GridWidth))
                
        else if LossAllowed == 'Always'
            FinalBuyPrice + _GridWidth
                
    else
        FinalSellPrice + _GridWidth
    
// FUNCTIONS

// Function to sum factorial
fSum(_Num)=>
    (math.pow(_Num, 2) + _Num) / 2

// Function when "Cash / n Buys" or "Position / n Sells"
fCaPo_N(_N, _n) =>
    1 / (_N - nz(_n))

// Function when "Cash / n Buys +" or "Position / n Sells +"
fCaPo_Nplus(_OnSells, _N, _n) =>
    if TradingType == 'Spot' or _OnSells == 1
        (nz(_n)+1) / (fSum(_N) - fSum(nz(_n)))
    else
        (nz(_n)+1) / fSum(_N)
        
// One of the correct ways to use security
f_security(_sym, _res, _src, _rep) => 
    request.security(_sym, _res, _src[not _rep and barstate.isrealtime ? 1 : 0])[_rep or barstate.isrealtime ? 0 : 1]

// Pivot points
PP          := f_security(syminfo.tickerid, ppPeriod, hlc3, false)

// Moving Average
MA          = ta.ema(close, MALength)
sMA         = f_security(syminfo.tickerid, MARes, MA, false)

// Analyzing when the period changes
PeriodChange := ta.change(time(ppPeriod)) != 0

// On Bullish trend, less Number of Buys and more amounts per trade;
// on Bearish more Number of Buys and less amounts per trade
// Max. number of buys
NBuys := if (BuyType == "Cash / n Buys" or BuyType == "Cash / n Buys +")
    if BuyLimitPrice >= sMAValue
        NBuysUp
    else
        NBuysDown
else
    NBuysDown

// On Bullish trend, more Number of Sells and less amounts per trade;
// on Bearish less Number of Sells and more amounts per trade
// Max. number of sells
NSells := if (SellType == "Position / n Sells" or SellType == "Position / n Sells +")
    if SellLimitPrice < sMAValue
        NSellsDown
    else
        NSellsUp
else
    NSellsUp
    
// TRADING

// Start of trading
if time >= TimeFirstClose

    // Final Trade Price, Average Price & Backtest
    for _i = 1 to math.max(NBuys, NSells)
    
        // Grid on Buys
        array.insert(aDown, _i, fDownGrid(fWidth(Width)))
        
        // Crossing between price and levels of grid
        array.insert(aBuy, _i, (low <= array.get(aDown, _i) or open <= array.get(aDown, _i)) and nBuys <= NBuys-1)
        
        // Grid on Sells
        array.insert(aUp, _i, fUpGrid(fWidth(Width)))
    
        // Crossing between price and levels of grid
        array.insert(aSell, _i, (high >= array.get(aUp, _i) or open >= array.get(aUp, _i)) and nSells <= NSells-1)
        strategy.initial_capital = 50000
        // Financial Data
        RealizedPnL         := Balance - strategy.initial_capital
        PRealizedPnL        := (RealizedPnL / strategy.initial_capital) * 100
        Floating            := ((close - AvgPrice) / AvgPrice) * PositionSize * AvgPrice
        PFloating           := (Floating / Balance) * 100
        URealizedPnL        := RealizedPnL + Floating
        PURealizedPnL       := (URealizedPnL / strategy.initial_capital) * 100
        Equity              := Balance + Floating
        Margin              := TradingType == 'Spot' ? 0 : (PositionSize * AvgPrice * MarginRate)
        Cash                := TradingType == 'Spot' ? math.max(0, Balance - (PositionSize * AvgPrice)) : math.max(0, Balance - Margin)
        BuyAndHold          := ((close  - FirstClose) / FirstClose) * strategy.initial_capital
        PBuyAndHold         := (BuyAndHold / strategy.initial_capital) * 100
        CLeverage           := (PositionSize * AvgPrice) / Balance
        LiquidationPrice    := TradingType == 'Spot' ? 0 :  AvgPrice - ((Balance - (Margin * 1)) / PositionSize)
        Liquidation         := (ta.valuewhen(LiquidationPrice >= low, time , 0) <= timenow)
        ProfitFactor        := Gains / Losses
        TradingTime         := timenow - TimeFirstClose
        
        // Quantities to buy according to inputs
        if      BuyType == "Contracts"
            if na(FinalOpenPrice)
                BuyQuantity := ((Cash * InitialContracts) / FirstClose)
            else
                BuyQuantity := math.min((Cash / AvgPrice), BuyQ)
                   
        else if BuyType == "Cash"
            if na(FinalOpenPrice)
                BuyQuantity := (Cash * InitialContracts)
            else
                BuyQuantity := math.min(Cash, BuyQ)
                    
        else if BuyType == "% Cash"
            if na(FinalOpenPrice)
                BuyQuantity := (Cash * InitialContracts)
            else
                if nBuys >= NBuys - LastXtrades
                    BuyQ := (1 / (NBuys - nz(nBuys))) * 100
                
                BuyQuantity := math.min(Cash, (BuyQ / 100) * Cash)
        
        else if BuyType == "Cash / n Buys"
            if na(FinalOpenPrice)
                BuyQuantity := (Cash * InitialContracts)
            else
                BuyQuantity := math.min(Cash, fCaPo_N(NBuys, nBuys) * Cash)
                                           
        else if BuyType == "Cash / n Buys +"
            if na(FinalOpenPrice)
                BuyQuantity := (Cash * InitialContracts)
            else
                BuyQuantity := math.min(Cash, fCaPo_Nplus(0, NBuys, nBuys) * Cash)
            
        // Quantities to sell according to inputs
        if      SellType == "Contracts"
            SellQuantity    := math.min(PositionSize, SellQ)
            
        else if SellType == "Cash"
            SellQuantity    := math.min((PositionSize * AvgPrice), SellQ)
            
        else if SellType == "% Position"
            SellQuantity    := math.min(PositionSize, (SellQ / 100) * PositionSize)
            
        else if SellType == "Position / n Sells"
            SellQuantity    := math.min(PositionSize, fCaPo_N(NSells, nSells) * PositionSize)
        
        else if SellType == "Position / n Sells +"
            SellQuantity    := math.min(PositionSize, fCaPo_Nplus(1, NSells, nSells) * PositionSize)
            
        // First buy limit order from every change of the period
        if (PP != PP[1]) and nz(nBuys) == 0 and not nz(nSells) == 0 and not na(nBuys) and not na(fDownGrid(fWidth(Width)))
            
            // Value of the MA
            sMAValue := sMA
            
            // Buy price of the limit order
            BuyLimitPrice := fDownGrid(fWidth(Width))            
                
        // Buying at better Price
        if array.get(aBuy, _i) and BuyQuantity > 0
            
            // Value of the MA
            sMAValue := sMA
            
            // Price of buy orders and resetting sales
            FinalBuyPrice   := math.min(open, array.get(aDown, _i))
            FinalSellPrice  := na
            FinalOpenPrice  := FinalBuyPrice
            
            // Number of buys and resetting sales
            nBuys           += 1
            nSells          := na
            
            // Redefining buy quantity
            if BuyType == "Contracts"
                BuyAmount   := BuyQuantity
            else
                BuyAmount   := (BuyQuantity / FinalBuyPrice)
            
            // Calculating the priority and secondary price average
            PositionCash    += FinalBuyPrice * BuyAmount
            PositionSize    += BuyAmount
            AvgPrice        := PositionCash / PositionSize
            
            // Calculating net profit
            Balance         -= (BuyAmount * FinalBuyPrice * CommissionValue)
            
            // Comissions losses
            Losses          += (BuyAmount * FinalBuyPrice * CommissionValue)
            
            // Fees paid
            Commission      += (BuyAmount * FinalBuyPrice * CommissionValue)
            
            // Avoiding overlap
            BarIndex        := bar_index            
            
            // Variable reference
            MaxFinalOpenPrice := math.max(FinalBuyPrice, nz(MaxFinalOpenPrice))
            
            // Buy & Sell price of the limit orders
            if nBuys <= NBuys-1
                BuyLimitPrice := FinalBuyPrice - fWidth(Width)
            else
                BuyLimitPrice := na
            
            SellLimitPrice := fUpGrid(fWidth(Width))
            
            // Strategy orders
            strategy.order("Buy", strategy.long, BuyAmount)

            // Buy shapes
            //string BuyText = str.tostring(BuyAmount,'#.####') + "\n" + str.tostring(((BuyAmount * FinalBuyPrice) / Cash) * 100, '#.##') + "%"
            //c_BuyGrad = color.from_gradient(((NBuys - nBuys) / NBuys) * 100, 1, 100, color.lime, color.blue)
            //label.new(bar_index, FinalBuyPrice, BuyText, textcolor = color.new(color.white, 50), color = c_BuyGrad, style = label.style_diamond, size = fTextSize(LabelSizeInput))

        // Selling at better Price    
        else if array.get(aSell, _i) and SellQuantity > 0 and BarIndex != bar_index
            
            // Value of the MA
            sMAValue := sMA
            
            // Price of sale orders and resetting buys
            FinalBuyPrice   := na
            FinalSellPrice  := math.max(open, array.get(aUp, _i))
            FinalOpenPrice  := FinalSellPrice
            
            // Number of sales and resetting buys
            nBuys           := na
            nSells          += 1
            
            // Redefining sell quantity
            if SellType == "Cash"
                SellAmount  := SellQuantity / FinalSellPrice
            else
                SellAmount  := SellQuantity
                
            // Calculating the priority and resetting secondary price average
            PositionCash    -= AvgPrice * SellAmount
            PositionSize    -= SellAmount
            
            // Calculating net profit
            Balance          += (FinalSellPrice - AvgPrice) * SellAmount
            Balance          -= (SellAmount * FinalSellPrice * CommissionValue)
            
            // Gains and Losses
            if FinalSellPrice >= AvgPrice
                Gains       += (FinalSellPrice - AvgPrice) * SellAmount
            else
                Losses      += (AvgPrice - FinalSellPrice) * SellAmount
            
            // Comission losses    
            Losses          += (SellAmount * FinalSellPrice * CommissionValue)
            
            // Fees paid
            Commission      += (SellAmount * FinalSellPrice * CommissionValue)
            
            // Variable reference
            MaxFinalOpenPrice := FinalSellPrice
            
            // Buy & Sell price of the limit orders
            BuyLimitPrice := fDownGrid(fWidth(Width))
            
            if nSells <= NSells-1
                SellLimitPrice := FinalSellPrice + fWidth(Width)
            else
                SellLimitPrice := na

            // Strategy orders
            strategy.close("Buy", comment = 'Sell', qty = SellAmount)

            // Sell shapes
            //string SellText = str.tostring(SellAmount,'#.####') + "\n" + str.tostring((SellAmount / (PositionSize + SellAmount)) * 100, '#.##') + "%"
            //c_SellGrad = color.from_gradient(((NSells - nSells) / NSells) * 100, 1, 100, color.yellow, color.red)
            //label.new(bar_index, FinalSellPrice, SellText, textcolor = color.new(color.white, 50), color = c_SellGrad, style = label.style_diamond, size = fTextSize(LabelSizeInput))
      
// PLOTTING

// Price of the limit orders
bool LastBar = (time >= timenow - (timeframe.multiplier * 1000 * 60))
plotshape(ShowGrid                          ? BuyLimitPrice  : na, "Buy level",  shape.cross, location.absolute, color.new(color.blue, 30), size = size.auto)
plotshape(ShowGrid                          ? SellLimitPrice : na, "Sell level", shape.cross, location.absolute, color.new(color.red,  30), size = size.auto)

// Table
var InfoPanel = table.new(position.middle_left, 2, 12, na, color.new(color.white, 80), 1, color.new(color.white, 80), 1)
ftable(_table_id, _column, _row, _text, _bgcolor) => 
    table.cell(_table_id, _column, _row, _text, 0, 0, _bgcolor, text.align_left, text.align_center, fTextSize(TableSizeInput), na)

tfString(int timeInMs) =>
    // @function  Produces a string corresponding to the input time in days, hours, and minutes.
    // @param     (series int) A time value in milliseconds to be converted to a string variable. 
    // @returns   (string) A string variable reflecting the amount of time from the input time.
    float s  = timeInMs / 1000
    float m  = s / 60
    float h  = m / 60
    float d  = h / 24
    float mo = d / 30.416
    int tm   = math.floor(m % 60)
    int th   = math.floor(h % 24)
    int td   = math.floor(d % 30.416)
    int tmo  = math.floor(mo % 12)
    int ys   = math.floor(d / 365)
    
    string result = 
      switch
        d == 30 and th == 10 and tm == 30 => "1M"
        d == 7  and th == 0  and tm == 0  => "1W"
        =>
            string yStr  = ys  ? str.tostring(ys)  + "Y "  : ""
            string moStr = tmo ? str.tostring(tmo) + "M "  : ""
            string dStr  = td  ? str.tostring(td)  + "D "  : ""
            string hStr  = th  ? str.tostring(th)  + "H "  : ""
            string mStr  = tm  ? str.tostring(tm)  + "min" : ""
            yStr + moStr + dStr + hStr + mStr
            
if ShowPanel
    ftable(InfoPanel, 0, 0,     'Equity: '                                                                              , color.new(color.white, 50))
    ftable(InfoPanel, 0, 1,     'Position: '                                                                            , color.new(color.white, 50))
    ftable(InfoPanel, 0, 2,     'Cash: '                                                                                , color.new(color.white, 50))
    ftable(InfoPanel, 0, 3,     'Margin: '                                                                              , color.new(color.white, 50))
    ftable(InfoPanel, 0, 4,     'Current Leverage: '                                                                    , color.new(color.white, 50))
    ftable(InfoPanel, 0, 5,     'Commission Paid: '                                                                     , color.new(color.white, 50))
    ftable(InfoPanel, 0, 6,     'Floating: '                                                                            , color.new(color.white, 50))
    ftable(InfoPanel, 0, 7,     'Realized PnL: '                                                                        , color.new(color.white, 50))
    ftable(InfoPanel, 0, 8,     'Unrealized PnL: '                                                                      , color.new(color.white, 50))
    ftable(InfoPanel, 0, 9,     'Buy n Hold: '                                                                          , color.new(color.white, 50))
    ftable(InfoPanel, 0, 10,    'Profit Factor: '                                                                       , color.new(color.white, 50))
    ftable(InfoPanel, 0, 11,    'Time of Trading: '                                                                     , color.new(color.white, 50))
    ftable(InfoPanel, 1, 0,     Liquidation ? 'Liquidation' : str.tostring(Equity, '#.####') + ' ' + syminfo.currency   , Liquidation ? color.red : color.green)
    ftable(InfoPanel, 1, 1,     str.tostring(PositionSize, '#.####') + ' ' + syminfo.basecurrency                       , color.green)
    ftable(InfoPanel, 1, 2,     str.tostring(Cash, '#.####') + ' ' + syminfo.currency                                   , color.green)
    ftable(InfoPanel, 1, 3,     str.tostring(Margin, '#.####') + ' ' + syminfo.currency                                 , color.green)
    ftable(InfoPanel, 1, 4,     TradingType == 'Spot' ? 'Spot' : str.tostring(CLeverage, '#.##') + 'x'                  , color.green)
    ftable(InfoPanel, 1, 5,     str.tostring(Commission, '#.####') + ' ' + syminfo.currency                             , Commission    == 0 ? color.green : color.red)
    ftable(InfoPanel, 1, 6,     str.tostring(PFloating, '#.##') + ' %'                                                  , PFloating     >= 0 ? color.green : color.red)
    ftable(InfoPanel, 1, 7,     str.tostring(PRealizedPnL, '#.##') + ' %'                                               , PRealizedPnL  >= 0 ? color.green : color.red)
    ftable(InfoPanel, 1, 8,     str.tostring(PURealizedPnL, '#.##') + ' %'                                              , PURealizedPnL >= 0 ? color.green : color.red)
    ftable(InfoPanel, 1, 9,     str.tostring(PBuyAndHold, '#.##') + ' %'                                                , PBuyAndHold   >= 0 ? color.green : color.red)
    ftable(InfoPanel, 1, 10,    str.tostring(ProfitFactor, '#.##')                                                      , ProfitFactor  >= 1 ? color.green : color.red)
    ftable(InfoPanel, 1, 11,    tfString(TradingTime)                                                                   , color.new(color.white, 50))
    
// Plotting pivot points
plot(PP, title = "PP", style = plot.style_stepline, color = color.silver, linewidth = 1)

// Plotting the average price
plotshape(barstate.isrealtime and ta.change(AvgPrice)     != 0                     ? AvgPrice       : na, "AvgPricepr",   shape.diamond, location.absolute, color.new(color.yellow,  10), size = size.tiny)
plotshape(                        ta.change(AvgPrice[1])  != 0                     ? AvgPrice[1]    : na, "AvgPricep",    shape.diamond, location.absolute, color.new(color.yellow,  40), size = size.tiny)
plotshape(TimeFirstClose == time                                                   ? FirstClose     : na, "FirstClose",   shape.diamond, location.absolute, color.new(color.yellow,  40), size = size.tiny)

// Plotting the moving average
plot((BuyType == "Cash / n Buys" or BuyType == "Cash / n Buys +") and NBuysUp != NBuysDown ? sMA : na, title = "Moving Average Buys", color = color.new(color.blue, 50), linewidth = 2)
plot((SellType == "Position / n Sells" or SellType == "Position / n Sells +") and NSellsUp != NSellsDown ? sMA : na, title = "Moving Average Sells", color = color.new(color.red, 50), linewidth = 2)

// Plotting the liquidation price
plot(ShowLiquidationPrice and LiquidationPrice > 0 ? LiquidationPrice : na, "Liquidation Price", Liquidation ? color.new(color.red, 30) : color.new(color.lime, 30), 2)
barcolor(Liquidation ? color.red : na)

//⚠️ IMPORTANT NOTICE: LIVE ALGORITHMIC TRADING RISKS

//🚨 Engaging in live algorithmic trading poses several inherent risks that you should be aware of:

//📉 Backtesting Limitations: Historical performance (backtesting) may not accurately predict future results. Past success does not guarantee future profits.
//🌐 Market Unpredictability: The market is dynamic and may fail or exhibit unexpected behavior, impacting your trading strategies.
//🛑 Broker Infrastructure Issues: Your broker's infrastructure may experience failures, execution delays, or reject your orders, affecting real-time trading.
//🤖 System Failures: The systems used for order generation, communication with your broker, and result reception might fail, disrupting the trading process.
//⏳ Time Lag Challenges: Time lags during live trading can lead to unexpected behavior and outcomes, requiring careful consideration.
//🤝 Third-Party System Risks: Systems of third parties, including service providers, brokers, and securities markets, may fail or malfunction, impacting overall functionality.
//💡 It's crucial to acknowledge and understand these risks before embarking on live algorithmic trading. Stay informed, be cautious, and adapt your strategies accordingly. 
// Happy and safe trading! 🚀💰