FreelanceSections

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

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

Spécifications

"""
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())

Répondu

1
Développeur 1
Évaluation
(633)
Projets
1001
47%
Arbitrage
33
36% / 36%
En retard
98
10%
Travail
Publié : 6 codes
2
Développeur 2
Évaluation
(19)
Projets
24
8%
Arbitrage
9
33% / 33%
En retard
1
4%
Chargé
3
Développeur 3
Évaluation
(48)
Projets
56
34%
Arbitrage
15
27% / 60%
En retard
1
2%
Travail
4
Développeur 4
Évaluation
(6)
Projets
5
0%
Arbitrage
4
25% / 75%
En retard
2
40%
Gratuit
5
Développeur 5
Évaluation
(8)
Projets
11
0%
Arbitrage
8
25% / 63%
En retard
2
18%
Travail
6
Développeur 6
Évaluation
(16)
Projets
35
23%
Arbitrage
4
0% / 50%
En retard
2
6%
Travail
7
Développeur 7
Évaluation
(1)
Projets
2
0%
Arbitrage
2
0% / 50%
En retard
0
Gratuit
8
Développeur 8
Évaluation
(2)
Projets
2
0%
Arbitrage
0
En retard
0
Gratuit
9
Développeur 9
Évaluation
(17)
Projets
21
14%
Arbitrage
8
38% / 38%
En retard
3
14%
Chargé
10
Développeur 10
Évaluation
(593)
Projets
684
32%
Arbitrage
42
45% / 45%
En retard
12
2%
Occupé
11
Développeur 11
Évaluation
(19)
Projets
26
27%
Arbitrage
4
50% / 25%
En retard
4
15%
Chargé
12
Développeur 12
Évaluation
(4)
Projets
3
33%
Arbitrage
2
0% / 100%
En retard
0
Gratuit
13
Développeur 13
Évaluation
(2668)
Projets
3400
68%
Arbitrage
77
48% / 14%
En retard
342
10%
Travail
Publié : 1 code
14
Développeur 14
Évaluation
(2)
Projets
3
0%
Arbitrage
0
En retard
0
Gratuit
15
Développeur 15
Évaluation
(1)
Projets
0
0%
Arbitrage
1
0% / 100%
En retard
0
Gratuit
16
Développeur 16
Évaluation
(1)
Projets
1
100%
Arbitrage
0
En retard
0
Gratuit
17
Développeur 17
Évaluation
(258)
Projets
265
29%
Arbitrage
0
En retard
3
1%
Gratuit
Publié : 2 codes
18
Développeur 18
Évaluation
(28)
Projets
32
25%
Arbitrage
20
10% / 50%
En retard
10
31%
Travail
19
Développeur 19
Évaluation
(10)
Projets
12
0%
Arbitrage
3
33% / 33%
En retard
1
8%
Gratuit
20
Développeur 20
Évaluation
(298)
Projets
477
40%
Arbitrage
105
40% / 24%
En retard
81
17%
Chargé
Publié : 2 codes
21
Développeur 21
Évaluation
Projets
0
0%
Arbitrage
0
En retard
0
Gratuit
22
Développeur 22
Évaluation
Projets
0
0%
Arbitrage
0
En retard
0
Gratuit
23
Développeur 23
Évaluation
Projets
0
0%
Arbitrage
0
En retard
0
Gratuit
Commandes similaires
URGENT — Review & Certify MT5 Risk Firewall + Telegram Module (5 Days) 100+ USD
We have a professionally built MT5 security and monitoring module with pre-written code. We need an experienced MQL5 developer to REVIEW, FIX, and CERTIFY the SENTINEL MODULE. YOU ARE NOT BUILDING FROM SCRATCH. You are reviewing 6 existing .mqh files. WHAT YOU WILL DO: 1. Review 6 pre-written Sentinel module files 2. Verify drawdown calculations (3% daily / 7% total) 3. Fix DD warning spam bug (fires every tick —
URGENT — Review & Certify MT5 Trade Engine Module (5 Days) 100+ USD
We have a professionally built MT5 Expert Advisor with pre-written code ready. We need an experienced MQL5 developer to REVIEW, FIX, and CERTIFY the ENGINE MODULE. YOU ARE NOT BUILDING FROM SCRATCH. You are reviewing 8 existing .mqh files. WHAT YOU WILL DO: 1. Review 8 pre-written .mqh engine files 2. Fix known shutdown bug: "invalid pointer access in AlmudoEngine.mqh (60,10)" 3. Achieve ZERO warnings in MT5 Build
ATR Risk-Managed EA for EURUSD & XAUUSD - Breakeven + Daily DD Stop 30 - 150 USD
### ** Main EA File** - `InstitutionalTrendPullbackScalper.mq5` **Core Features Implemented:** **Multi-Timeframe Analysis** - M15 trend filter (EMA20 > EMA50 for uptrends) - M5 entry signals with 5-condition confirmation - Independent indicator sets for both symbols **Advanced Entry Logic** - RSI reversal detection (crosses thresholds) - Price pullback zone validation - Bullish/bearish candle close confirmation -
Automate my trading 100 - 300 USD
i want a trading bot that take trade auto and make 5% profit daily and stop with in 24 hours not more then that at least the bot give me more then 2% not less then that like a ai agent if it make any loss that agent have to take care of it i need only 5 % profit
Binance Ai Trading Bot $US700 budget negotiable 700 - 3000 USD
I need an Ai trading bot for Binance and BTC on MT5 that also uses order flow data. It should also make use of TSI- Temporal indicator sampling and also it should make use of fundamental analysis in the process of signal generation
MT5 EA with ready indicator 30+ USD
Hi,I am looking for an experienced developer specializing in the creation of Expert Advisors (EAs) for trading platforms. I would like to commission the development of an EA based on the open-source LuxAlgo code. The entry strategy will be based, among other things, on Martingale and Grid trading concepts. A detailed specification covering trade management, position sizing, and risk management rules will be provided
TPO Market profile, volume profile, footprint, delta for Sierra charts 65+ USD
Hi! I’m looking for someone to make TPO Market profile, volume profile, footprint, delta for Sierra charts I need it to be set up to give me these for Nasdaq, ES/NQ and also the minii’s. Is this something you can help me with
Profitable EA for Gold in sideways and trending both market 30+ USD
I have a EA for XAUUSD which works awesome in sideways and trending market as well, capital requirement is only 2000USd and weekly profit is around 1500-2000 USD. I am using this bot from 3 months and getting continuous good result
Complete my multi--timeframe-multi-currency-indicator (easy for a coder) 40 - 150 USD
I’m looking for an experienced MT4 developer to create a custom indicator (or EA) with mobile push notifications based on the following strategy. Trend Filter (Daily Timeframe) Daily Close above 50 EMA = Bullish Bias Daily Close below 50 EMA = Bearish Bias Entry Timeframe (H1) RSI Settings RSI Period: 14 (default) Upper Level: 65 Lower Level: 35 Buy Signal Generate a BUY signal when: Daily bias is Bullish (Daily
Want to automate my strategy in forex gold 30 - 100 USD
Dear All i am working on strategy in forex market specifically in xausud and i just want someone to make it automatic execution mode as per my requirements with propee risk management my broker is exness and i have an account in MT5

Informations sur le projet

Budget
50+ USD