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):
    params = (
        ('rebalance_period', 21),  # Rebalance period in trading days (monthly roughly for trading days)
    )

    def __init__(self):
        self.rebalance_counter = 0

    def next(self):
        # Check for rebalancing condition
        if self.rebalance_counter % self.params.rebalance_period == 0:
            self.rebalance_portfolio()
        self.rebalance_counter += 1

    def rebalance_portfolio(self):
        # Symbols for the 'Magnificent 7' stocks
        symbols = ['AAPL', 'AMZN', 'GOOGL', 'MSFT', 'META', 'NVDA', 'TSLA']
        positions = [self.getposition(data).size for data in self.datas]
        cash = self.broker.get_cash()
        total_value = cash + sum([pos * data.close[0] for pos, data in zip(positions, self.datas)])
        equal_value = total_value / len(symbols)

        # Iterate over all stocks and rebalance each
        for i, data in enumerate(self.datas):
            current_value = positions[i] * data.close[0]
            target_size = int((equal_value - current_value) / data.close[0])
            if target_size > 0:
                self.buy(data=data, size=target_size)
            elif target_size < 0:
                self.sell(data=data, size=abs(target_size))
            logging.info(f'Rebalanced {data._name}: New Target Size: {target_size} | Date: {self.datas[0].datetime.date(0)} | Close Price: {data.close[0]}')

# Adjust dates for lookback period
lookback_period = 0  # No specific indicator, zero lookback

# Fetch and add data for each stock
symbols = {
    'AAPL': 'AAPL',
    'AMZN': 'AMZN',
    'GOOGL': 'GOOGL',
    'MSFT': 'MSFT',
    'META': 'META',
    'NVDA': 'NVDA',
    'TSLA': 'TSLA',
}
# Fetch and add data to Cerebro, fetching multiple tickers at once
for name, ticker in symbols.items():
    data = bt.feeds.PandasData(dataname=yf.download(ticker, start_date, end_date), name=name)
    cerebro.adddata(data)

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