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
1
Valutazioni
Progetti
2
0%
Arbitraggio
1
0%
/
0%
In ritardo
2
100%
Gratuito
2
Valutazioni
Progetti
66
12%
Arbitraggio
12
58%
/
42%
In ritardo
1
2%
Gratuito
3
Valutazioni
Progetti
50
42%
Arbitraggio
3
33%
/
33%
In ritardo
4
8%
Gratuito
4
Valutazioni
Progetti
10
50%
Arbitraggio
6
17%
/
50%
In ritardo
3
30%
In elaborazione
5
Valutazioni
Progetti
4
50%
Arbitraggio
4
0%
/
75%
In ritardo
0
Gratuito
Ordini simili
EA Crafter
500+ USD
Act as a professional Quantitative Developer and Risk Manager. I want to build a systematic trading strategy rulebook that prioritizes capital preservation and statistical edge over raw performance. Please generate a structured trading strategy using the following framework: 1. ASSET CLASS & TIMEFRAME: - Asset: [e.g., Apple (AAPL), Bitcoin (BTC), or EUR/USD] - Timeframe: [e.g., 5-minute, 1-hour, Daily] 2. CORE
JOB TITLE: XAUUSD ONLY MQL5 Strategy Developer Needed To Improve Existing MT5 EA Winrate JOB DESCRIPTION: I already have a working MetaTrader 5 Expert Advisor with a fixed set file and existing trading logic. The strategy is based on Volume Profile / Delta bias, ATR-based TP/SL, ATR deviation filtering, ATR trade spacing, break-even after TP1, and TP lock management. I am looking for an experienced MQL5 / trading
Driven Multiple Choice
30+ USD
Part 1: Project setup Input settings (risk, stop loss, take profit, EMA periods) Indicator initialization Trade management framework Part 2: Trading logic EMA crossover detection Buy/Sell entry rules One-trade-per-symbol check Part 3: Risk management Automatic lot size calculation Stop-loss and take-profit placement Trade execution and error handling Part 4: Final touches On-screen information Optimization
Institutional‑Grade Multi‑Currency MT5 EA
1000 - 1300 USD
Hello, I am reopening this project with a fully updated and clarified specification. I am looking for a high‑level MQL5 developer who can deliver a clean, stable, and professional Phase 1 version of my: Institutional‑Grade Multi‑Currency MT5 EA (A2SR + SMC + Smart Recovery + Smart Grid + Liquidity + Volatility + Safety Filters) This EA is not a simple indicator conversion or a basic strategy. It is a structured
I have an expert advisor's investor login. I want you to study it and make me the exact same EA. There should be absolutely no differences or mistakes. You should have great observation skills for this aswell
HFT / Latency Arbitrage / Scalper needed
30 - 5000 USD
I am looking for an experienced MQL5 or MQL4 developer with a strong background in low-latency algorithmic trading, market data integration, arbitrage and execution optimization. The project involves developing a high-performance HFT Expert Advisor (EA) for XAUUSD or US30 on IC Markets that is designed for robust execution in both demo and live environments. The EA may use market data feeds (such as lmax,one zero or
Hft gold ea live account ic market
30 - 3000 USD
I am looking for an experienced MQL5 or MQL4 developer with a strong understanding of high-frequency trading (HFT) concepts who can explain how certain HFT-style strategies have historically been able to pass proprietary firm evaluations while also being profitable on demo accounts and capable of transitioning successfully to live trading. I am interested in understanding the legitimate trading logic, execution
Advanced Forex Expert Advisor-fully automated system
200 - 300 USD
I require a custom EA and an accompanying custom indicator built in MQL5 for Meta Trader 4/5. The EA must be fully automated (Algo Trading); Telegram-Signal-Linked and named 'AMK Fx'
Professional AI Automation Trading Bot for Forex & Crypto
500 - 1500 USD
Title Professional AI Automation Trading Bot for Forex & Crypto Solution Language Python (preferred) or MQL5 depending on integration requirements. Categories Expert Advisor (EA) for MetaTrader 5 Automated trading strategies AI/ML-based signal generation Risk management automation Required Skills Strong knowledge of MQL5/Python Experience with MetaTrader API integration Machine learning model deployment
Informazioni sul progetto
Budget
30+ USD
Scadenze
da 1 a 2 giorno(i)