다중 시간대 적응형 평균 회귀 및 볼륨 분석 전략

/*backtest
start: 2025-01-01 00:00:00
end: 2025-04-01 00:00:00
period: 1h
basePeriod: 1h
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT"}]
*/

//@version=5
strategy("Mean Reversion with Volume Analysis", overlay=true)

// Parameters
length = input.int(20, "MA Period", minval=1)
bb_mult = input.float(2.0, "Bollinger Band Multiplier", minval=0.1, step=0.1)
rsi_length = input.int(14, "RSI Period", minval=1)
rsi_oversold = input.int(30, "RSI Oversold", minval=1, maxval=100)
rsi_overbought = input.int(70, "RSI Overbought", minval=1, maxval=100)
vol_threshold = input.float(1.5, "Volume Threshold", minval=0.1, step=0.1)
atr_period = input.int(14, "ATR Period", minval=1)
use_higher_tf = input.bool(true, "Use Higher Timeframe Confirmation")
higher_tf = input.timeframe("D", "Higher Timeframe")

// Moving Average and Bollinger Bands
sma = ta.sma(close, length)
stdev = ta.stdev(close, length)
upper_band = sma + bb_mult * stdev
lower_band = sma - bb_mult * stdev
bb_width = (upper_band - lower_band) / sma

// RSI
rsi = ta.rsi(close, rsi_length)

// Volume Analysis
vol_sma = ta.sma(volume, length)
vol_ratio = volume / vol_sma

// ATR for volatility filter and position sizing
atr = ta.atr(atr_period)
normalized_atr = atr / close

// Higher Timeframe Confirmation
higher_rsi = request.security(syminfo.tickerid, higher_tf, ta.rsi(close, rsi_length))
higher_sma = request.security(syminfo.tickerid, higher_tf, ta.sma(close, length))
higher_trend = close > higher_sma ? 1 : close < higher_sma ? -1 : 0

// Adaptive Parameters based on market volatility
dynamic_rsi_oversold = 30 + math.floor(10 * normalized_atr)
dynamic_rsi_overbought = 70 - math.floor(10 * normalized_atr)

// Entry Conditions
long_condition = close < lower_band and 
                 rsi < (use_higher_tf ? math.min(rsi_oversold, dynamic_rsi_oversold) : rsi_oversold) and 
                 vol_ratio > vol_threshold and
                 (use_higher_tf ? higher_trend >= 0 : true) and
                 normalized_atr < 0.03  // Volatility filter

short_condition = close > upper_band and 
                  rsi > (use_higher_tf ? math.max(rsi_overbought, dynamic_rsi_overbought) : rsi_overbought) and 
                  vol_ratio > vol_threshold and
                  (use_higher_tf ? higher_trend <= 0 : true) and
                  normalized_atr < 0.03  // Volatility filter

// Exit Conditions
exit_long = close > sma or rsi > 60 or close < lower_band * 0.95  // Stop loss
exit_short = close < sma or rsi < 40 or close > upper_band * 1.05  // Stop loss

// Strategy Execution
if (long_condition)
    strategy.entry("Long", strategy.long)

if (short_condition)
    strategy.entry("Short", strategy.short)

if (strategy.position_size > 0 and exit_long)
    strategy.close("Long")

if (strategy.position_size < 0 and exit_short)
    strategy.close("Short")

// Plotting
plot(sma, "SMA", color=color.blue)
plot(upper_band, "Upper Band", color=color.red)
plot(lower_band, "Lower Band", color=color.green)

// Signals for visualization
plotshape(long_condition, "Buy Signal", shape.triangleup, location.belowbar, color.green, size=size.small)
plotshape(short_condition, "Sell Signal", shape.triangledown, location.abovebar, color.red, size=size.small)

// Info panel
var table info = table.new(position.top_right, 3, 5, color.black, color.white, 1, color.gray, 1)
table.cell(info, 0, 0, "RSI", text_color=color.white)
table.cell(info, 1, 0, str.tostring(rsi, "#.##"), text_color=rsi < rsi_oversold ? color.green : rsi > rsi_overbought ? color.red : color.white)
table.cell(info, 0, 1, "BB Width", text_color=color.white)
table.cell(info, 1, 1, str.tostring(bb_width, "#.###"), text_color=color.white)
table.cell(info, 0, 2, "Vol Ratio", text_color=color.white)
table.cell(info, 1, 2, str.tostring(vol_ratio, "#.##"), text_color=vol_ratio > vol_threshold ? color.green : color.white)
table.cell(info, 0, 3, "ATR %", text_color=color.white)
table.cell(info, 1, 3, str.tostring(normalized_atr * 100, "#.##") + "%", text_color=color.white)