FreelanceSezioni

⏱️ 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())

Con risposta

1
Sviluppatore 1
Valutazioni
(630)
Progetti
994
47%
Arbitraggio
33
36% / 36%
In ritardo
98
10%
Gratuito
Pubblicati: 6 codici
2
Sviluppatore 2
Valutazioni
(19)
Progetti
23
9%
Arbitraggio
6
33% / 50%
In ritardo
1
4%
Occupato
3
Sviluppatore 3
Valutazioni
(43)
Progetti
50
28%
Arbitraggio
14
21% / 64%
In ritardo
1
2%
In elaborazione
4
Sviluppatore 4
Valutazioni
(6)
Progetti
5
0%
Arbitraggio
3
33% / 67%
In ritardo
2
40%
Gratuito
5
Sviluppatore 5
Valutazioni
(8)
Progetti
11
0%
Arbitraggio
7
29% / 71%
In ritardo
2
18%
In elaborazione
6
Sviluppatore 6
Valutazioni
(16)
Progetti
35
23%
Arbitraggio
4
0% / 50%
In ritardo
2
6%
In elaborazione
7
Sviluppatore 7
Valutazioni
(1)
Progetti
2
0%
Arbitraggio
2
0% / 50%
In ritardo
0
Gratuito
8
Sviluppatore 8
Valutazioni
(2)
Progetti
2
0%
Arbitraggio
0
In ritardo
0
Gratuito
9
Sviluppatore 9
Valutazioni
(16)
Progetti
20
10%
Arbitraggio
8
38% / 38%
In ritardo
3
15%
In elaborazione
10
Sviluppatore 10
Valutazioni
(568)
Progetti
657
32%
Arbitraggio
41
41% / 46%
In ritardo
11
2%
Occupato
11
Sviluppatore 11
Valutazioni
(14)
Progetti
19
11%
Arbitraggio
4
50% / 25%
In ritardo
4
21%
In elaborazione
12
Sviluppatore 12
Valutazioni
(4)
Progetti
3
33%
Arbitraggio
2
0% / 100%
In ritardo
0
Gratuito
13
Sviluppatore 13
Valutazioni
(2660)
Progetti
3379
68%
Arbitraggio
77
48% / 14%
In ritardo
342
10%
Gratuito
Pubblicati: 1 codice
14
Sviluppatore 14
Valutazioni
(2)
Progetti
3
0%
Arbitraggio
0
In ritardo
0
Gratuito
15
Sviluppatore 15
Valutazioni
(1)
Progetti
0
0%
Arbitraggio
1
0% / 100%
In ritardo
0
Gratuito
16
Sviluppatore 16
Valutazioni
(1)
Progetti
1
100%
Arbitraggio
0
In ritardo
0
Gratuito
17
Sviluppatore 17
Valutazioni
(258)
Progetti
264
30%
Arbitraggio
0
In ritardo
3
1%
Gratuito
Pubblicati: 2 codici
18
Sviluppatore 18
Valutazioni
(25)
Progetti
29
21%
Arbitraggio
20
10% / 50%
In ritardo
8
28%
Caricato
19
Sviluppatore 19
Valutazioni
(8)
Progetti
9
0%
Arbitraggio
2
0% / 50%
In ritardo
1
11%
In elaborazione
20
Sviluppatore 20
Valutazioni
(298)
Progetti
477
40%
Arbitraggio
105
40% / 24%
In ritardo
81
17%
Caricato
Pubblicati: 2 codici
21
Sviluppatore 21
Valutazioni
Progetti
0
0%
Arbitraggio
0
In ritardo
0
Gratuito
22
Sviluppatore 22
Valutazioni
Progetti
0
0%
Arbitraggio
0
In ritardo
0
Gratuito
23
Sviluppatore 23
Valutazioni
Progetti
0
0%
Arbitraggio
0
In ritardo
0
Gratuito
Ordini simili
Early Killer EA 30+ USD
It must have automated stop loss. Something that can end poverty and kill the market early.It must take the trades for me whenever I start it it must work on tradeport ea
Design & Construct Scripts for Sharing Screenshots with Clarifai 150+ USD
I want to use a ai subscription service called Clarifai as an image identification tool, and I wish to use it in response to screenshots of my signals being generated and placed in a folder. -I believe there needs to be a script that responds to a new screenshot being added to a specific folder That script then sends the image to Clarifai, and then Clarifai needs to be instructed to scan that image and look for
Some one creates an ea based on this heikein ashi smothed indicator 30 - 200 USD
buy condition when blue color appears sell condition when yellow color appears close all buys when there is a sell order close all sells when there is a buy order
Mk 30+ USD
I need a fully automated trading robot designed to generate consistent profits while strictly controlling risk and minimizing losses. The robot should use a combination of strategies, including trend-following, scalping, and price action, and must be able to adapt to different market conditions such as trending and ranging markets. It should analyze the market using indicators like Moving Averages, RSI, MACD, and
Expert trading robot developer needed 30+ USD
1. IF price forms: - Higher highs + higher lows → TREND = BUY - Lower highs + lower lows → TREND = SELL ELSE → NO TRADE 2. IF: - Trend = BUY - Price retraces to support zone - Bullish engulfing candle forms - TDI green crosses above red (optional) THEN: - Execute BUY 3. IF: - Trend = SELL - Price retraces to resistance - Bearish engulfing forms - TDI confirms THEN: - Execute SELL 4. Risk per trade = 1% of account Lot

Informazioni sul progetto

Budget
50+ USD