Servizio freelance su MQL5.com: Trading paradise

Descrizione

Specifiche

# Import necessary libraries

import pandas as pd

# Define parameters

stop_loss_percentage = 0.02 # Set stop loss percentage (2% in this example)

take_profit_percentage = 0.05 # Set take profit percentage (5% in this example)

# Read historical price data

df = pd.read_csv("historical_data.csv") # Replace with your historical data file or API integration

# Calculate moving averages

df['SMA_50'] = df['Close'].rolling(window=50).mean()

df['SMA_200'] = df['Close'].rolling(window=200).mean()

# Initialize variables

position = None

entry_price = 0.0

# Start trading loop

for i in range(200, len(df)):

current_price = df['Close'].iloc[i]

# Check for entry conditions

if position is None and df['SMA_50'].iloc[i] > df['SMA_200'].iloc[i]:

position = 'long'

entry_price = current_price

print(f"Enter long position at {entry_price}")

elif position is None and df['SMA_50'].iloc[i] < df['SMA_200'].iloc[i]:

position = 'short'

entry_price = current_price

print(f"Enter short position at {entry_price}")

# Check for exit conditions

if position == 'long' and current_price >= (1 + take_profit_percentage) * entry_price:

position = None

exit_price = current_price

print(f"Exit long position at {exit_price}")

profit = exit_price - entry_price

print(f"Profit: {profit}")

elif position == 'long' and current_price <= (1 - stop_loss_percentage) * entry_price:

position = None

exit_price = current_price

print(f"Exit long position at {exit_price}")

loss = exit_price - entry_price

print(f"Loss: {loss}")

elif position == 'short' and current_price <= (1 - take_profit_percentage) * entry_price:

position = None

exit_price = current_price

print(f"Exit short position at {exit_price}")

profit = entry_price - exit_price

print(f"Profit: {profit}")

elif position == 'short' and current_price >= (1 + stop_loss_percentage) * entry_price:

position = None

exit_price = current_price

print(f"Exit short position at {exit_price}")

loss = entry_price - exit_price

print(f"Loss: {loss}")

Con risposta

Valutazioni

(2)

Progetti

Arbitraggio

0% / 0%

In ritardo

100%

Gratuito

Valutazioni

(43)

Progetti

12%

Arbitraggio

58% / 42%

In ritardo

Gratuito

Valutazioni

(35)

Progetti

42%

Arbitraggio

33% / 33%

In ritardo

Gratuito

Valutazioni

(6)

Progetti

50%

Arbitraggio

17% / 50%

In ritardo

30%

In elaborazione

Valutazioni

(5)

Progetti

50%

Arbitraggio

0% / 75%

In ritardo

Gratuito

Ordini simili

1. Objective Development of a XAUUSD mean-reversion grid Expert Advisor for MT5. Deliverable: full commented .mq5 source code (personal use, no resale). Compiled-only (.ex5) offers will be declined. 2. Framework (fixed) 2.1. Native timeframe M5, signal evaluated on closed bar, trades long & short. 2.2. Entry analysis: Bollinger Bands + Moving Average based conditions. The exact entry/selection logic must match a

1. Use two EMAs: 20 and 50. If EMA 20 is above EMA 50 → uptrend (look for buys) If EMA 20 is below EMA 50 → downtrend (look for sells) 2. Wait for a pullback into the area between the two EMAs. - For buys: price must touch or move between EMA 20 and EMA 50 during the last few candles. - For stils: same idea, but in a downtrend. 3. Entry signal: Buy: a bullish engulfing candle in an uptrend after the pullback

I am looking for an experienced MQL5 developer to create a fully automated Expert Advisor (EA) for MetaTrader 5 based on a Price Action strategy. The bot needs to automatically identify specific candlestick formations and market structure levels, execute trades, and manage risk using a dynamic trailing stop.The EA should monitor the chart for the following price action setup:Market Structure / Trend Filter:The bot

I am looking for an experienced MQL5 developer to build a high-frequency (HFT) latency arbitrage Expert Advisor for Pepperstone MT5 , using LMAX as the leading price feed. The initial focus will be on US30 (Dow Jones) , and if the strategy proves successful, I want the EA to be easily expandable to additional symbols such as NAS100, GER40, XAUUSD, major forex pairs, and other supported instruments. The EA should

Start ↓ Detect Trend (H4) ↓ Confirm Structure (H1) ↓ Wait for Pullback ↓ Check Indicators ↓ Calculate Confidence Score ↓ Score ≥ 80? ├── No → Wait └── Yes ↓ Calculate Lot Size ↓ Place Order ↓ Set Stop Loss ↓ Set Take Profit ↓ Manage Trade ↓ Move to Break-even ↓ Trail Stop ↓ Close Trade. IF Price > EMA200 (H4) AND EMA50 > EMA200 (H4) AND ADX > 25 AND RSI between 55 and 70 AND MACD Main > Signal AND Bullish engulfing

HIGH-FREQUENCY M5/M15 CONCURRENT ENTRY SNIPER import time class HighFrequencySniper: def __init__(self): self.target_profit = 25.00 # Targeted Delta Move self.max_execution_time = 3600 # 1 Hour Sandbox (Seconds) self.lot_allocation = "CALIBRATED_TO_RISK" def execute_hft_scan(self, current_price, m5_rsi, m15_order_block): print(f"[SCANNING] Current Kernel Metric: ${current_price:.2f

# HIGH-FREQUENCY M5/M15 CONCURRENT ENTRY SNIPER import time class HighFrequencySniper: def __init__(self): self.target_profit = 25.00 # Targeted Delta Move self.max_execution_time = 3600 # 1 Hour Sandbox (Seconds) self.lot_allocation = "CALIBRATED_TO_RISK" def execute_hft_scan(self, current_price, m5_rsi, m15_order_block): print(f"[SCANNING] Current Kernel Metric: ${current_price:.2f}")

I need a trading bot, please i need this project urgently and when messaing me kindly send me samples of past works and dont forget i need the project to be done as soon as possible

*Need an MQL5 EA for MT5 to trade gold and forex automatically. Must include Stop Loss, Take Profit, and basic risk management. Budget is $30 to $50. Looking for clean, stable code that works on VPS.*

Hello Developers, I am looking for an experienced MQL5 developer to complete the development of a custom MetaTrader 5 Expert Advisor (EA) based on my proprietary trading strategy. I already have a partially developed EA that includes the required custom indicators and part of the trading logic. The project can either be completed by modifying the existing EA or, if more appropriate, by rebuilding it from scratch

Informazioni sul progetto

Budget

30+ USD

Scadenze

da 1 a 2 giorno(i)

Qualità delle specifiche
Qualità del controllo dei risultati
Disponibilità e capacità di comunicazione