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NESESITO QUE ME HAGAN UN BOT CON ESTA INFORMACION EN PYTON

MQL5 Uzmanlar Python

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NESESITO QUE ME HAGAN UN BOT CON ESTA INFORMACION EN PYTON 









mport ccxt

import pandas as pd
import numpy as np
import ta

# Configuración de la API
exchange = ccxt.binance()  # Cambia a tu exchange preferido
symbol = 'BTC/USDT'  # Activo a operar
timeframe = '1h'  # Marco temporal
risk_percentage = 0.02  # Riesgo por operación
stop_loss_percentage = 0.02  # 2% stop loss
take_profit_percentage = 0.04  # 4% take profit

# Función para obtener datos históricos
def get_historical_data(symbol, timeframe):
    bars = exchange.fetch_ohlcv(symbol, timeframe)
    df = pd.DataFrame(bars, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])
    df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
    return df

# Función para calcular indicadores
def calculate_indicators(df):
    df['RSI'] = ta.momentum.RSIIndicator(df['close']).rsi()
    df['MACD'] = ta.trend.MACD(df['close']).macd()
    df['Signal'] = ta.trend.MACD(df['close']).macd_signal()
    df['OBV'] = ta.volume.OnBalanceVolumeIndicator(df['close'], df['volume']).on_balance_volume()
    df['Stochastic'] = ta.momentum.StochasticOscillator(df['high'], df['low'], df['close']).stoch()
    return df

# Estrategia de Trading
def strategy(df):
    last_row = df.iloc[-1]
    
    # Condiciones de compra
    if (last_row['RSI'] < 30) and (last_row['MACD'] > last_row['Signal']):
        return 'buy'
    
    # Condiciones de venta
    elif (last_row['RSI'] > 70) and (last_row['MACD'] < last_row['Signal']):
        return 'sell'
    
    return 'hold'

# Función de gestión de riesgo
def calculate_position_size(balance, risk_percentage):
    return balance * risk_percentage

# Función para ejecutar ordenes con stop loss y take profit
def execute_order(signal, position_size):
    market_price = exchange.fetch_ticker(symbol)['last']
    
    if signal == 'buy':
        # Ejecutar orden de compra
        order = exchange.create_market_order(symbol, 'buy', position_size)
        # Calcular niveles de stop loss y take profit
        stop_loss_price = market_price * (1 - stop_loss_percentage)
        take_profit_price = market_price * (1 + take_profit_percentage)
        
        # Establecer stop loss
        exchange.create_order(symbol, 'stop_market', 'sell', position_size, stop_loss_price)
        # Establecer take profit
        exchange.create_limit_order(symbol, 'sell', position_size, take_profit_price)

    elif signal == 'sell':
        # Ejecutar orden de venta
        order = exchange.create_market_order(symbol, 'sell', position_size)
        # Calcular niveles de stop loss y take profit
        stop_loss_price = market_price * (1 + stop_loss_percentage)
        take_profit_price = market_price * (1 - take_profit_percentage)
        
        # Establecer stop loss
        exchange.create_order(symbol, 'stop_market', 'buy', position_size, stop_loss_price)
        # Establecer take profit
        exchange.create_limit_order(symbol, 'buy', position_size, take_profit_price)

# Loop principal del bot
def run_bot():
    balance = exchange.fetch_balance()['total']['USDT']  # Ajusta según tu activo
    df = get_historical_data(symbol, timeframe)
    df = calculate_indicators(df)
    
    signal = strategy(df)
    
    if signal in ['buy', 'sell']:
        position_size = calculate_position_size(balance, risk_percentage)
        execute_order(signal, position_size)

# Ejecutar el bot
if _name_ == "_main_":
    run_bot()

Yanıtlandı

1
Geliştirici 1
Derecelendirme
(184)
Projeler
317
24%
Arabuluculuk
24
33% / 13%
Süresi dolmuş
23
7%
Çalışıyor
Yayınlandı: 3 kod
2
Geliştirici 2
Derecelendirme
(1)
Projeler
1
0%
Arabuluculuk
1
0% / 0%
Süresi dolmuş
0
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