Algorithmic investing reinvented.

Generated Code

# Setup logging configuration
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')

# Define your strategy
class ExampleStrategy(bt.Strategy):  # You must leave this name ExampleStrategy the same or the strategy will not run
    # implement new params based on user specification
    params = (
        ('period', 5),  # RSI period
        ('upperband', 70.0),  # Upper band for RSI
    )

    def __init__(self):
        # Compute the RSI with a 5-day period
        self.rsi = bt.indicators.RSI(self.datas[0], period=self.p.period)
        logging.info('RSI(5) Indicator initialized.')

    def next(self):
        rsi_value = self.rsi[0]
        close_price = self.datas[0].close[0]

        # Check for buy signal
        if rsi_value > self.p.upperband and not self.position:
            size = int(self.broker.get_cash() / close_price)
            self.buy(size=size)  # Execute buy order with size
            logging.info(f'BUY Signal: RSI(5) > {self.p.upperband} | Date: {self.datas[0].datetime.date(0)} | Size: {size} | Close Price: {close_price}')

        # Check for sell signal
        elif rsi_value < self.p.upperband and self.position:
            self.sell(size=self.position.size)  # Execute sell order
            logging.info(f'SELL Signal: RSI(5) < {self.p.upperband} | Date: {self.datas[0].datetime.date(0)} | Size: {self.position.size} | Close Price: {close_price}')

# Define the lookback period based on the longest indicator params, this must be done to provide a warmup period for indicators
lookback_period = 5  # RSI period

# Fetch and add data to Cerebro, ensuring correct ticker for Bitcoin
btc_data = bt.feeds.PandasData(dataname=yf.download('BTC-USD', start_date, end_date), name='BTC')
cerebro.adddata(btc_data)

globals()['lookback_period'] = lookback_period  # Update global variable for lookback period usage