신경과 전문의 트레이딩 로봇

/*backtest
start: 2024-10-20 00:00:00
end: 2025-10-18 08:00:00
period: 1d
basePeriod: 1d
exchanges: [{"eid":"Futures_Binance","currency":"BTC_USDT","balance":500000}]
*/

// This Pine Script™ code is subject to the terms of the MPL 2.0 at https://mozilla.org/MPL/2.0/
// © MTB by Neurodoc
// By Nicolás Astorga

//@version=5
strategy("Master Trading Bot by Neurodoc", 
         shorttitle="MTB Adaptation", 
         overlay=true, 
         initial_capital=10000, 
         pyramiding=100,
         commission_value=0.1, 
         commission_type=strategy.commission.percent,
         default_qty_type = strategy.cash)

// —————— CONFIGURATION (Based on ve.env) ——————
// Purchase and DCA Percentages
var GRP_DCA = "DCA Configuration"
start_percentage = input.float(5.0, "Initial Buy Percentage (%)", group=GRP_DCA)
increment_percentage = input.float(2.5, "Increment per DCA Buy (%)", group=GRP_DCA)
max_percentage = input.float(100.0, "Maximum Buy Percentage (%)", group=GRP_DCA)
min_profit_percent = input.float(2.0, "Minimum Profit for Sell (%)", group=GRP_DCA)

// Stop Loss and Drop Signal
var GRP_RISK = "Risk Management"
stop_loss_percent = input.float(100.0, "Stop Loss (%)", group=GRP_RISK, tooltip="A value of 100 means there’s no real stop loss, as price would have to go to 0.")
drop_percent_signal = input.float(2.0, "Price Drop for Sell Signal (%)", group=GRP_RISK)

// Indicator Parameters
var GRP_INDICATORS = "Indicator Parameters"
ema_fast_period = input.int(3, "Fast EMA", group=GRP_INDICATORS)
ema_mid_period = input.int(7, "Medium EMA", group=GRP_INDICATORS)
ema_slow_period = input.int(18, "Slow EMA", group=GRP_INDICATORS)
bb_length = input.int(20, "Bollinger Bands Length", group=GRP_INDICATORS)
bb_stddev = input.float(2.0, "BB Standard Deviation", group=GRP_INDICATORS)
macd_fast = input.int(52, "MACD Fast", group=GRP_INDICATORS)
macd_slow = input.int(200, "MACD Slow", group=GRP_INDICATORS)
macd_signal = input.int(3, "MACD Signal", group=GRP_INDICATORS)
rsi_length = input.int(14, "RSI Length", group=GRP_INDICATORS)
rsi_oversold_threshold = input.int(25, "RSI Oversold (for divergence)", group=GRP_INDICATORS)

// —————— INDICATOR CALCULATIONS ——————
// EMAs
ema_fast = ta.ema(open, ema_fast_period)
ema_mid = ta.ema(open, ema_mid_period)
ema_slow = ta.ema(open, ema_slow_period)

// Bollinger Bands
[bb_middle, bb_upper, bb_lower] = ta.bb(close, bb_length, bb_stddev)
bb_width = (bb_upper - bb_lower) / bb_middle * 100
is_bb_expanding = bb_width > bb_width[1]

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

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

// Price drop signal from highest price (similar to `cummax` in Python)
highest_price = ta.highest(high, 500) // Using 500-bar lookback to approximate the high
price_drop_percent = ((highest_price - close) / highest_price) * 100
is_price_drop_signal = price_drop_percent >= drop_percent_signal

// —————— TRADING LOGIC ——————
// Trend Conditions
is_bullish = ema_fast > ema_slow and macd_line > signal_line and close > bb_middle
is_bearish = ema_fast < ema_slow and macd_line < signal_line and close < bb_middle
is_weakening = rsi < rsi[1]

// Variables to manage strategy state
var bool just_sold = false
var int dca_step = 0

// Determine next buy percentage of capital
dca_buy_percentage = start_percentage + (dca_step * increment_percentage)
if dca_buy_percentage > max_percentage
    dca_buy_percentage := max_percentage

avg_buy_price = strategy.position_avg_price

// Initial Long Condition
long_signal_initial = strategy.position_size == 0 and is_bullish and macd_line > signal_line and rsi < 65

// DCA Condition
price_drop_from_avg = ((avg_buy_price - close) / avg_buy_price) * 100
dca_required_drop = 2.0 + (dca_step * 4.0) // DCA price drop start and increment logic
long_signal_dca = strategy.position_size > 0 and is_bearish and close < avg_buy_price and price_drop_from_avg >= dca_required_drop

// Manage `just_sold` state
if strategy.position_size > 0
    just_sold := false
if strategy.position_size == 0 and strategy.position_size[1] > 0
    just_sold := true

// Avoid immediate repurchase after sell unless bullish condition is strong
long_signal = (just_sold and is_bullish) ? long_signal_initial : (not just_sold ? (long_signal_initial or long_signal_dca) : false)

// Sell (Close) Condition
current_profit_percent = ((close - avg_buy_price) / avg_buy_price) * 100
has_min_profit = current_profit_percent >= min_profit_percent
stop_loss_price = avg_buy_price * (1 - stop_loss_percent / 100)
is_stoploss_triggered = close <= stop_loss_price

short_signal = strategy.position_size > 0 and has_min_profit and ((is_bearish and is_weakening) or is_price_drop_signal or is_stoploss_triggered or (macd_line < signal_line))

// —————— ORDER EXECUTION ——————
if (long_signal)
    // Calculate how much MONEY (USDT) to invest in this trade
    cash_to_invest = (strategy.equity * dca_buy_percentage / 100) / close
    strategy.entry("Buy", strategy.long, qty=cash_to_invest)
    dca_step := dca_step + 1
        
if (short_signal)
    strategy.close_all(comment="Sell")
    dca_step := 0 // Reset DCA counter after selling

// —————— VISUALIZATION ——————
// Background color by trend
bgcolor(is_bullish ? color.new(color.green, 90) : is_bearish ? color.new(color.red, 90) : na)

// Plot EMAs and Bollinger Bands
plot(ema_fast, "Fast EMA", color.blue)
plot(ema_slow, "Slow EMA", color.orange)
p1 = plot(bb_upper, "Upper BB", color=color.gray)
p2 = plot(bb_lower, "Lower BB", color=color.gray)
fill(p1, p2, color=color.new(color.gray, 90))

// Plot average buy price when in position
plot(strategy.position_size > 0 ? avg_buy_price : na, "Average Buy Price", color.yellow, style=plot.style_linebr, linewidth=2)

// Plot Take Profit target
plot(strategy.position_size > 0 ? avg_buy_price * (1 + min_profit_percent / 100) : na, "Sell Price (TP)", color.aqua, style=plot.style_linebr, linewidth=2)

// Plot Stop Loss level
plot(strategy.position_size > 0 ? stop_loss_price : na, "Stop Loss", color.fuchsia, style=plot.style_linebr, linewidth=2)