Multi-Timeframe Hurst Exponent and Fibonacci Retracement Dynamic Trend Trading Strategy

/*backtest
start: 2024-02-21 00:00:00
end: 2024-10-01 00:00:00
period: 1h
basePeriod: 1h
exchanges: [{"eid":"Binance","currency":"TRB_USDT"}]
*/

//@version=5
// Advanced Multi-Timeframe Trading System (Risk Managed)
// 
// Description:
// This strategy combines an approximate measure of market trending via a Hurst exponent
// calculation with Fibonacci retracement levels derived from a higher timeframe (default: Daily)
// to identify potential reversal zones and trade opportunities. The Hurst exponent is calculated
// as a rough indicator of market persistence, while the Fibonacci retracement levels provide potential
// support and resistance areas.
// 
// Signal Logic:
// - A long entry is signaled when the price crosses above the 61.8% Fibonacci level (Golden Ratio)
//   and the daily Hurst exponent is above 0.5 (suggesting a trending market).
// - A short entry is signaled when the price crosses below the 38.2% Fibonacci level and the daily Hurst
//   exponent is below 0.5.
// 
// Risk Management:
// Each trade is risk-managed with a stop-loss set at 2% below (or above for shorts) the entry price,
// and a take profit order is set to achieve a 1:2 risk-reward ratio. Position sizing is fixed at 10% of
// equity per trade. Additionally, the strategy limits trading to a maximum of 5 trades per day and 510 trades
// overall (for backtesting since 2019) to ensure a realistic number of orders.
// 
// Backtesting Parameters:
// - Initial Capital: $10,000
// - Commission: 0.1% per trade
// - Slippage: 1 tick per bar
// - Position Sizing: 10% of equity per trade
// 
// Disclaimer:
// Past performance is not indicative of future results. This strategy is experimental and is provided solely
// for educational purposes. Use caution and perform your own testing before any live deployment.
// 
// Author: [Your Name]
// Date: [Date]

strategy("Advanced Multi-Timeframe Trading System (Risk Managed)",
     overlay=true, 
     max_bars_back=500, 
     initial_capital=10000, 
     default_qty_type=strategy.percent_of_equity, 
     default_qty_value=10,          // 10% of equity per trade
     commission_type=strategy.commission.percent, 
     commission_value=0.1,          // 0.1% commission per trade
     slippage=1,                    // 1 tick per bar
     calc_on_order_fills=true, 
     calc_on_every_tick=true)

// ─── INPUTS ─────────────────────────────────────────────────────────────
hurstLen        = input.int(50, title="Hurst Lookback Period", minval=10)
fibTF           = input.timeframe("D", title="Fibonacci Retracement Timeframe")
maxTradesPerDay = input.int(5, title="Max Trades Per Day", minval=1)
maxTotalTrades  = input.int(510, title="Max Total Trades since 2019", minval=1)
riskPerc        = input.float(2.0, title="Risk Percent per Trade (%)", step=0.1) * 0.01  // 2% risk per trade
rrRatio         = input.float(2.0, title="Risk-Reward Ratio", step=0.1)                 // Target profit = 2x risk

// ─── FUNCTION: Approximate Hurst Exponent Calculation ──────────────────────
// This function uses a simple rescaled range method to approximate the Hurst exponent.
// Note: This is an experimental calculation and should be interpreted as a rough gauge of market trending.
calcHurst(src, len) =>
    mean   = ta.sma(src, len)
    dev    = src - mean
    cumDev = 0.0
    for i = 0 to len - 1
        cumDev := cumDev + dev[i]
    R     = ta.highest(cumDev, len) - ta.lowest(cumDev, len)
    S     = ta.stdev(src, len)
    hurst = na(S) or S == 0 ? na : math.log(R / S) / math.log(len)
    hurst

// Calculate the Hurst exponent on the current timeframe and from a higher timeframe (daily)
currHurst  = calcHurst(close, hurstLen)
dailyHurst = request.security(syminfo.tickerid, "D", calcHurst(close, hurstLen))

// ─── FIBONACCI RETRACEMENT LEVELS (WITH GOLDEN RATIO) ──────────────────────────
// Retrieve the daily high/low from the selected timeframe (default: Daily)
dHigh   = request.security(syminfo.tickerid, fibTF, high)
dLow    = request.security(syminfo.tickerid, fibTF, low)

// Define Fibonacci levels between the daily low and high.
fib_0   = dLow
fib_100 = dHigh
fib_236 = dLow + 0.236 * (dHigh - dLow)
fib_382 = dLow + 0.382 * (dHigh - dLow)
fib_500 = dLow + 0.5   * (dHigh - dLow)
fib_618 = dLow + 0.618 * (dHigh - dLow)  // Golden ratio level

// Plot the Fibonacci levels for reference.
pFib0   = plot(fib_0,   color=color.gray,   title="Fib 0%")
pFib236 = plot(fib_236, color=color.blue,   title="Fib 23.6%")
pFib382 = plot(fib_382, color=color.orange, title="Fib 38.2%")
pFib500 = plot(fib_500, color=color.purple, title="Fib 50%")
pFib618 = plot(fib_618, color=color.green,  title="Fib 61.8% (Golden Ratio)")
pFib100 = plot(fib_100, color=color.gray,   title="Fib 100%")
// Fill the area between the 61.8% and 38.2% levels to highlight the key retracement zone.
fill(pFib618, pFib382, color=color.new(color.yellow, 80), title="Fibonacci Retracement Zone")

// ─── TRADE COUNT MANAGEMENT ─────────────────────────────────────────────────
// To simulate realistic trading frequency, the strategy limits trades to a maximum of 5 per day and 510 overall.
var int tradesToday     = 0
var int globalTradeCount = 0

// Reset the daily trade counter at the start of a new day.
newDay = ta.change(time("D"))
if newDay
    tradesToday := 0

// Allow new trades only if within the daily and overall trade limits.
canTrade = (tradesToday < maxTradesPerDay) and (globalTradeCount < maxTotalTrades)

// ─── TRADING SIGNALS ─────────────────────────────────────────────────────────
// Entry conditions based on Fibonacci levels and daily Hurst conditions:
// • Long: Price crosses above the 61.8% (Golden Ratio) level and daily Hurst > 0.5.
// • Short: Price crosses below the 38.2% level and daily Hurst < 0.5.
longCond  = ta.crossover(close, fib_618) and (dailyHurst > 0.5)
shortCond = ta.crossunder(close, fib_382) and (dailyHurst < 0.5)

if longCond and canTrade
    strategy.entry("Long", strategy.long)
    tradesToday      := tradesToday + 1
    globalTradeCount := globalTradeCount + 1

if shortCond and canTrade
    strategy.entry("Short", strategy.short)
    tradesToday      := tradesToday + 1
    globalTradeCount := globalTradeCount + 1

// ─── RISK MANAGEMENT: STOP-LOSS & TAKE-PROFIT ──────────────────────────────
// For active positions, define stop-loss and take profit levels based on the entry price.
// This ensures that each trade risks approximately 2% of the entry price with a target
// of 2x the risk (1:2 risk-reward ratio).
if strategy.position_size > 0
    longStop   = strategy.position_avg_price * (1 - riskPerc)
    longTarget = strategy.position_avg_price * (1 + rrRatio * riskPerc)
    strategy.exit("Long Exit", from_entry="Long", stop=longStop, limit=longTarget)
if strategy.position_size < 0
    shortStop   = strategy.position_avg_price * (1 + riskPerc)
    shortTarget = strategy.position_avg_price * (1 - rrRatio * riskPerc)
    strategy.exit("Short Exit", from_entry="Short", stop=shortStop, limit=shortTarget)

// ─── CHART OVERLAYS & VISUAL AIDS ────────────────────────────────────────────
// Background color indicates the daily market trend:
// Green for trending conditions (dailyHurst > 0.5) and red for less trending conditions.
bgcolor(dailyHurst > 0.5 ? color.new(color.green, 90) : color.new(color.red, 90), title="Daily Trend Background")

// Display an information table in the top-right corner to help interpret key values.
var table infoTable = table.new(position.top_right, 2, 4, border_width=1, frame_color=color.gray)
if barstate.islast
    table.cell(infoTable, 0, 0, "Current Hurst", text_color=color.white, bgcolor=color.black)
    table.cell(infoTable, 1, 0, str.tostring(currHurst, "#.###"), text_color=color.white, bgcolor=color.black)
    table.cell(infoTable, 0, 1, "Daily Hurst", text_color=color.white, bgcolor=color.black)
    table.cell(infoTable, 1, 1, str.tostring(dailyHurst, "#.###"), text_color=color.white, bgcolor=color.black)
    table.cell(infoTable, 0, 2, "Trades Today", text_color=color.white, bgcolor=color.black)
    table.cell(infoTable, 1, 2, str.tostring(tradesToday), text_color=color.white, bgcolor=color.black)
    table.cell(infoTable, 0, 3, "Global Trades", text_color=color.white, bgcolor=color.black)
    table.cell(infoTable, 1, 3, str.tostring(globalTradeCount), text_color=color.white, bgcolor=color.black)

// Optional: Add labels on the final bar to mark the key Fibonacci levels.
if barstate.islast
    label.new(bar_index, fib_618, "61.8% (Golden Ratio)", style=label.style_label_left, color=color.green, textcolor=color.white, size=size.tiny)
    label.new(bar_index, fib_382, "38.2%", style=label.style_label_left, color=color.orange, textcolor=color.white, size=size.tiny)