Динамическая стоп-лосс-стратегия количественной торговли с использованием мультииндикаторного пересечения трендовых линий

/*backtest
start: 2024-06-23 00:00:00
end: 2024-09-09 00:00:00
period: 3h
basePeriod: 3h
exchanges: [{"eid":"Futures_Binance","currency":"ETH_USDT"}]
*/

//@version=5
strategy("Advanced Crypto Trend Line Strategy", overlay=true, margin_long=100, margin_short=100)

// ================================
// INPUT PARAMETERS
// ================================

// Crypto Selection
crypto_type = input.string("BTC", "Cryptocurrency", options=["BTC", "SOL", "AUTO"])

// Trend Line Parameters
trendline_length = input.int(20, "Trend Line Calculation Length", minval=10, maxval=50)
min_touches = input.int(2, "Minimum Trend Line Touches", minval=2, maxval=5)
breakout_threshold = input.float(0.5, "Breakout Threshold %", minval=0.1, maxval=2.0) / 100

// Risk Management
risk_percent = input.float(2.0, "Risk Per Trade %", minval=0.5, maxval=5.0) / 100
tp1_ratio = input.float(2.0, "Take Profit 1 Ratio", minval=1.0, maxval=5.0)
tp2_ratio = input.float(3.0, "Take Profit 2 Ratio", minval=2.0, maxval=6.0)
max_leverage = crypto_type == "BTC" ? 5 : crypto_type == "SOL" ? 10 : 7

// Technical Indicators
rsi_length = input.int(14, "RSI Length", minval=5, maxval=30)
rsi_oversold = input.int(35, "RSI Oversold Level", minval=20, maxval=40)
rsi_overbought = input.int(70, "RSI Overbought Level", minval=60, maxval=80)

macd_fast = input.int(12, "MACD Fast Length", minval=5, maxval=20)
macd_slow = input.int(26, "MACD Slow Length", minval=20, maxval=40)
macd_signal = input.int(9, "MACD Signal Length", minval=5, maxval=15)

volume_multiplier = input.float(1.5, "Volume Spike Multiplier", minval=1.1, maxval=3.0)

// ATR for Dynamic Stops
atr_length = input.int(14, "ATR Length for Stops", minval=5, maxval=30)
atr_multiplier = input.float(2.0, "ATR Stop Multiplier", minval=1.0, maxval=4.0)

// ================================
// TECHNICAL INDICATORS
// ================================

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

// MACD
[macd_line, signal_line, macd_histogram] = ta.macd(close, macd_fast, macd_slow, macd_signal)

// Volume
volume_avg = ta.sma(volume, 20)
volume_spike = volume > volume_avg * volume_multiplier

// ATR for dynamic stops
atr = ta.atr(atr_length)

// ================================
// TREND LINE CALCULATION
// ================================

// Function to calculate trend line slope and intercept
get_trend_line(src, len, min_touch) =>
    var float slope = na
    var float intercept = na
    var int touches = 0
    var array<float> highs = array.new<float>()
    var array<float> lows = array.new<float>()
    var array<int> high_bars = array.new<int>()
    var array<int> low_bars = array.new<int>()
    
    // Find pivots
    ph = ta.pivothigh(high, 5, 5)
    pl = ta.pivotlow(low, 5, 5)
    
    // Store pivot points
    if not na(ph)
        array.push(highs, ph)
        array.push(high_bars, bar_index - 5)
        if array.size(highs) > len
            array.shift(highs)
            array.shift(high_bars)
    
    if not na(pl)
        array.push(lows, pl)
        array.push(low_bars, bar_index - 5)
        if array.size(lows) > len
            array.shift(lows)
            array.shift(low_bars)
    
    [slope, intercept, touches]

// Calculate trend lines
[up_slope, up_intercept, up_touches] = get_trend_line(low, trendline_length, min_touches)
[down_slope, down_intercept, down_touches] = get_trend_line(high, trendline_length, min_touches)

// ================================
// TREND LINE VALUES
// ================================

// Simplified trend line calculation using linear regression
uptrend_line = ta.linreg(low, trendline_length, 0)
downtrend_line = ta.linreg(high, trendline_length, 0)

// Dynamic trend line based on recent pivots
recent_low = ta.lowest(low, 10)
recent_high = ta.highest(high, 10)

// Support and Resistance levels
support_level = uptrend_line
resistance_level = downtrend_line

// ================================
// MARKET STRUCTURE
// ================================

// Higher lows and lower highs detection
higher_low = low > ta.lowest(low[1], 5) and low[1] > ta.lowest(low[2], 5)
lower_high = high < ta.highest(high[1], 5) and high[1] < ta.highest(high[2], 5)

// Overall trend determination
uptrend = close > ta.sma(close, 50) and ta.sma(close, 20) > ta.sma(close, 50)
downtrend = close < ta.sma(close, 50) and ta.sma(close, 20) < ta.sma(close, 50)

// ================================
// ENTRY CONDITIONS
// ================================

// Long entry conditions
long_trend_bounce = close > support_level and low <= support_level * 1.01
long_rsi = rsi < rsi_oversold or (rsi > rsi_oversold and rsi[1] < rsi_oversold)
long_macd = macd_histogram > macd_histogram[1]
long_volume = volume_spike
long_structure = higher_low or uptrend

long_condition = long_trend_bounce and long_rsi and long_macd and long_volume and long_structure

// Short entry conditions
short_trend_reject = close < resistance_level and high >= resistance_level * 0.99
short_rsi = rsi > rsi_overbought or (rsi < rsi_overbought and rsi[1] > rsi_overbought)
short_macd = macd_histogram < macd_histogram[1]
short_volume = volume_spike
short_structure = lower_high or downtrend

short_condition = short_trend_reject and short_rsi and short_macd and short_volume and short_structure

// ================================
// BREAKOUT CONDITIONS
// ================================

// Uptrend breakout (bearish)
uptrend_break = close < support_level * (1 - breakout_threshold) and volume_spike
// Downtrend breakout (bullish)
downtrend_break = close > resistance_level * (1 + breakout_threshold) and volume_spike

// ================================
// POSITION SIZING
// ================================

// Calculate position size based on risk
account_size = strategy.equity
risk_amount = account_size * risk_percent

// ================================
// STRATEGY EXECUTION
// ================================

// Long entries
if long_condition and strategy.position_size == 0
    stop_loss = support_level - (atr * atr_multiplier)
    take_profit_1 = close + (close - stop_loss) * tp1_ratio
    take_profit_2 = close + (close - stop_loss) * tp2_ratio
    
    // Position sizing
    risk_per_share = close - stop_loss
    position_size = risk_amount / risk_per_share
    position_size := math.min(position_size, account_size * max_leverage / close)
    
    strategy.entry("Long", strategy.long, qty=position_size)
    strategy.exit("Long TP1", "Long", limit=take_profit_1, stop=stop_loss, qty=position_size * 0.5)
    strategy.exit("Long TP2", "Long", limit=take_profit_2, stop=stop_loss, qty=position_size * 0.5)

// Short entries
if short_condition and strategy.position_size == 0
    stop_loss = resistance_level + (atr * atr_multiplier)
    take_profit_1 = close - (stop_loss - close) * tp1_ratio
    take_profit_2 = close - (stop_loss - close) * tp2_ratio
    
    // Position sizing
    risk_per_share = stop_loss - close
    position_size = risk_amount / risk_per_share
    position_size := math.min(position_size, account_size * max_leverage / close)
    
    strategy.entry("Short", strategy.short, qty=position_size)
    strategy.exit("Short TP1", "Short", limit=take_profit_1, stop=stop_loss, qty=position_size * 0.5)
    strategy.exit("Short TP2", "Short", limit=take_profit_2, stop=stop_loss, qty=position_size * 0.5)

// Breakout entries
if downtrend_break and strategy.position_size == 0
    stop_loss = resistance_level - (atr * atr_multiplier)
    take_profit = close + (close - stop_loss) * 2.0
    
    risk_per_share = close - stop_loss
    position_size = risk_amount / risk_per_share
    position_size := math.min(position_size, account_size * max_leverage / close)
    
    strategy.entry("Breakout Long", strategy.long, qty=position_size)
    strategy.exit("Breakout Long Exit", "Breakout Long", limit=take_profit, stop=stop_loss)

if uptrend_break and strategy.position_size == 0
    stop_loss = support_level + (atr * atr_multiplier)
    take_profit = close - (stop_loss - close) * 2.0
    
    risk_per_share = stop_loss - close
    position_size = risk_amount / risk_per_share
    position_size := math.min(position_size, account_size * max_leverage / close)
    
    strategy.entry("Breakout Short", strategy.short, qty=position_size)
    strategy.exit("Breakout Short Exit", "Breakout Short", limit=take_profit, stop=stop_loss)

// ================================
// VISUALIZATION
// ================================

// Plot trend lines
plot(support_level, "Support Trend Line", color=color.green, linewidth=2)
plot(resistance_level, "Resistance Trend Line", color=color.red, linewidth=2)

// Plot entry signals
plotshape(long_condition, "Long Signal", shape.triangleup, location.belowbar, color.green, size=size.small)
plotshape(short_condition, "Short Signal", shape.triangledown, location.abovebar, color.red, size=size.small)

// Plot breakout signals
plotshape(downtrend_break, "Bullish Breakout", shape.diamond, location.belowbar, color.blue, size=size.small)
plotshape(uptrend_break, "Bearish Breakout", shape.diamond, location.abovebar, color.orange, size=size.small)

// Background color for trend
bgcolor(uptrend ? color.new(color.green, 95) : downtrend ? color.new(color.red, 95) : na)

// ================================
// ALERTS
// ================================

// Entry alerts
alertcondition(long_condition, "Long Entry", "Long entry signal detected")
alertcondition(short_condition, "Short Entry", "Short entry signal detected")
alertcondition(downtrend_break, "Bullish Breakout", "Bullish breakout detected")
alertcondition(uptrend_break, "Bearish Breakout", "Bearish breakout detected")

// ================================
// TABLE FOR INFORMATION
// ================================

// Create info table
var table info_table = table.new(position.top_right, 2, 8, bgcolor=color.white, border_width=1)

if barstate.islast
    table.cell(info_table, 0, 0, "Metric", text_color=color.black, bgcolor=color.gray)
    table.cell(info_table, 1, 0, "Value", text_color=color.black, bgcolor=color.gray)
    table.cell(info_table, 0, 1, "RSI", text_color=color.black)
    table.cell(info_table, 1, 1, str.tostring(math.round(rsi, 2)), text_color=color.black)
    table.cell(info_table, 0, 2, "MACD", text_color=color.black)
    table.cell(info_table, 1, 2, str.tostring(math.round(macd_line, 4)), text_color=color.black)
    table.cell(info_table, 0, 3, "Volume Spike", text_color=color.black)
    table.cell(info_table, 1, 3, volume_spike ? "YES" : "NO", text_color=color.black)
    table.cell(info_table, 0, 4, "Trend", text_color=color.black)
    table.cell(info_table, 1, 4, uptrend ? "UP" : downtrend ? "DOWN" : "SIDEWAYS", text_color=color.black)
    table.cell(info_table, 0, 5, "Support", text_color=color.black)
    table.cell(info_table, 1, 5, str.tostring(math.round(support_level, 2)), text_color=color.black)
    table.cell(info_table, 0, 6, "Resistance", text_color=color.black)
    table.cell(info_table, 1, 6, str.tostring(math.round(resistance_level, 2)), text_color=color.black)
    table.cell(info_table, 0, 7, "ATR", text_color=color.black)
    table.cell(info_table, 1, 7, str.tostring(math.round(atr, 2)), text_color=color.black)