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
Sviluppatore 1
Valutazioni
(2)
Progetti
2
0%
Arbitraggio
1
0% / 0%
In ritardo
2
100%
Gratuito
2
Sviluppatore 2
Valutazioni
(43)
Progetti
66
12%
Arbitraggio
12
58% / 42%
In ritardo
1
2%
Gratuito
3
Sviluppatore 3
Valutazioni
(35)
Progetti
50
42%
Arbitraggio
3
33% / 33%
In ritardo
4
8%
Gratuito
4
Sviluppatore 4
Valutazioni
(6)
Progetti
10
50%
Arbitraggio
6
17% / 50%
In ritardo
3
30%
In elaborazione
5
Sviluppatore 5
Valutazioni
(5)
Progetti
4
50%
Arbitraggio
4
0% / 75%
In ritardo
0
Gratuito
Ordini simili
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
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
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
Brotus AI 32+ USD
And let's talk about Linux and more about those technologies, ideas, those AI ideas.Let's make an AI technology summit for us base on wgat i wanna build and their example pictures of roadmapBoss can we take those idea all we've talked about base on technology, tech, UI...J.A.R.V.I.S...eDEX-UI into reality (solution) using laptop cause I think it give accces to build app amd more
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'
i am looking to upgrade my trading telegram bot and add live data to it and also make it linked to a dashboard where i can trace the users who register in my bot and pay and make them go in my private channel and manages the expiry date of each user
Hello, I'm looking for an expert who can help me acquire a secure, easy-to-use bot with Turkish language support for automated buying and selling in Forex, commodities, and cryptocurrencies, and who can also teach me how to set it up and use it
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
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

Informazioni sul progetto

Budget
30+ USD
Scadenze
da 1 a 2 giorno(i)