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⏱️ Urgent project – looking for an experienced developer to finalize MT4 bot (deadline: Tuesday)

MQL5 Esperti Forex Trading robot/indicator debugging Uploading data to a website

Specifiche

"""
Fast Multi-Pair RSI Trading Bot
Supports:
- BTCUSDT
- XAUUSD
- GBPUSD

Opens fast buy or sell trades based on RSI signals
Closes trades after 5, 10, or 15 minutes
"""

import asyncio
import time
from dataclasses import dataclass, field
from typing import Dict, List, Optional
import pandas as pd
import numpy as np

# ===== RSI calculation ===== #
def compute_rsi(close: pd.Series, period: int = 14) -> pd.Series:
    delta = close.diff()
    gain = delta.clip(lower=0)
    loss = -delta.clip(upper=0)
    avg_gain = gain.ewm(alpha=1 / period, adjust=False).mean()
    avg_loss = loss.ewm(alpha=1 / period, adjust=False).mean()
    rs = avg_gain / avg_loss
    return 100 - (100 / (1 + rs))

# ===== Position structure ===== #
@dataclass
class Position:
    id: str
    symbol: str
    side: str
    entry_price: float
    size: float
    opened_at: float
    duration_min: int

# ===== Config ===== #
@dataclass
class BotConfig:
    symbols: List[str] = field(default_factory=lambda: ["BTCUSDT", "XAUUSD", "GBPUSD"])
    rsi_period: int = 14
    rsi_oversold: int = 30
    rsi_overbought: int = 70
    durations_min: List[int] = field(default_factory=lambda: [5, 10, 15])
    account_equity: float = 2000.0
    risk_pct: float = 0.5
    lot_size: Optional[float] = None
    paper: bool = True

# ===== Trading Bot ===== #
class MultiPairRSIBot:
    def __init__(self, cfg: BotConfig):
        self.cfg = cfg
        self.data: Dict[str, pd.DataFrame] = {sym: pd.DataFrame() for sym in cfg.symbols}
        self.positions: Dict[str, Dict[str, Position]] = {sym: {} for sym in cfg.symbols}
        self._id = 0

    # ========== Fake 1-minute feed for PAPER mode ========== #
    def get_fake_ohlcv(self, symbol):
        now = int(time.time()) * 1000
        df = self.data[symbol]

        last_close = df["close"].iloc[-1] if not df.empty else 1000 + np.random.rand() * 10
        change = np.random.normal(0, 0.0008)
        close = last_close * (1 + change)
        high = max(last_close, close)
        low = min(last_close, close)

        return (now, last_close, high, low, close, 0)

    # ========== Append new candle ========== #
    def append_candle(self, symbol, ohlc):
        ts, o, h, l, c, v = ohlc
        row = {"timestamp": pd.to_datetime(ts, unit="ms"),
               "open": o, "high": h, "low": l, "close": c, "volume": v}
        self.data[symbol] = pd.concat([self.data[symbol], pd.DataFrame([row])], ignore_index=True)
        if len(self.data[symbol]) > 2000:
            self.data[symbol] = self.data[symbol].iloc[-2000:]

    # ========== Timeframe aggregation ========== #
    def to_tf(self, symbol, minutes):
        df = self.data[symbol]
        if df.empty:
            return pd.DataFrame()
        df["bucket"] = df["timestamp"].dt.floor(f"{minutes}T")
        out = df.groupby("bucket").agg({
            "open": "first",
            "high": "max",
            "low": "min",
            "close": "last",
            "volume": "sum"
        }).reset_index().rename(columns={"bucket": "timestamp"})
        return out

    # ========== Position sizing ========== #
    def get_size(self, price):
        if self.cfg.lot_size:
            return self.cfg.lot_size
        risk_amount = self.cfg.account_equity * (self.cfg.risk_pct / 100)
        return round(risk_amount / price, 4)

    # ========== Check RSI signals and enter trades ========== #
    async def process_signals(self, symbol):
        for dur in self.cfg.durations_min:
            df = self.to_tf(symbol, dur)
            if len(df) < self.cfg.rsi_period + 2:
                continue

            df["rsi"] = compute_rsi(df["close"], self.cfg.rsi_period)

            prev = df["rsi"].iloc[-2]
            last = df["rsi"].iloc[-1]
            price = df["close"].iloc[-1]

            # BUY: RSI cross up
            if prev <= self.cfg.rsi_oversold and last > prev:
                size = self.get_size(price)
                await self.open_position(symbol, "buy", price, size, dur)

            # SELL: RSI cross down
            if prev >= self.cfg.rsi_overbought and last < prev:
                size = self.get_size(price)
                await self.open_position(symbol, "sell", price, size, dur)

    # ========== Open position ========== #
    async def open_position(self, symbol, side, price, size, duration):
        self._id += 1
        pid = f"{symbol}_{self._id}"
        print(f"[{symbol}] OPEN {side.upper()} @ {price:.2f} | {duration}m | size {size}")

        pos = Position(
            id=pid,
            symbol=symbol,
            side=side,
            entry_price=price,
            size=size,
            opened_at=time.time(),
            duration_min=duration
        )
        self.positions[symbol][pid] = pos

    # ========== Close expired trades ========== #
    async def close_expired(self, symbol):
        now = time.time()
        to_close = []

        for pid, pos in self.positions[symbol].items():
            if (now - pos.opened_at) / 60 >= pos.duration_min:
                to_close.append(pid)

        for pid in to_close:
            await self.close_position(symbol, pid)

    # ========== Close position ========== #
    async def close_position(self, symbol, pid):
        pos = self.positions[symbol][pid]
        last_price = self.data[symbol]["close"].iloc[-1]
        pnl = (last_price - pos.entry_price) * pos.size if pos.side == "buy" else (pos.entry_price - last_price) * pos.size

        print(f"[{symbol}] CLOSE {pos.side.upper()} @ {last_price:.2f} | PnL = {pnl:.3f}")
        self.cfg.account_equity += pnl
        del self.positions[symbol][pid]

    # ========== Main loop ========== #
    async def start(self):
        print("Starting multi-pair RSI bot...")
        print("Symbols:", self.cfg.symbols)

        while True:
            try:
                for symbol in self.cfg.symbols:

                    # new candle
                    ohlcv = self.get_fake_ohlcv(symbol)
                    self.append_candle(symbol, ohlcv)

                    # signal scan
                    await self.process_signals(symbol)

                    # manage trades
                    await self.close_expired(symbol)

            except Exception as e:
                print("Error:", e)

            await asyncio.sleep(1)

# ========== Launch Example ========== #
async def main():
    cfg = BotConfig(
        symbols=["BTCUSDT", "XAUUSD", "GBPUSD"],
        account_equity=3000.0,
        paper=True,
        lot_size=None
    )
    bot = MultiPairRSIBot(cfg)

    task = asyncio.create_task(bot.start())
    await asyncio.sleep(60 * 5) # run 5 minutes demo
    task.cancel()

if __name__ == "__main__":
    asyncio.run(main())

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Informazioni sul progetto

Budget
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