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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
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
30+ USD
Scadenze
da 1 a 2 giorno(i)