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, you can take out this comment in your generated code
    # implement new params based on user specification
    params = (
        ('period', 50),  # Moving average period for AAPL
    )

    def __init__(self):
        # Get 50-day moving average of AAPL
        self.aapl_ma = bt.indicators.SimpleMovingAverage(self.datas[0].close, period=self.p.period)
        logging.info('50-day SMA for AAPL initialized.')

        # Calculate Relative Strength (RS) of AAPL to SPY: (AAPL Close / SPY Close)
        self.relative_strength = self.datas[0].close / self.datas[1].close
        logging.info('Relative Strength (AAPL/SPY) calculated.')

    def next(self):
        aapl_close = self.datas[0].close[0]
        aapl_ma = self.aapl_ma[0]
        rs = self.relative_strength[0]  # relative strength

        # Check for buy conditions: RS > 0 and AAPL close > 50-day SMA
        if rs > 0 and aapl_close > aapl_ma and not self.position:
            size = self.broker.get_cash() / aapl_close
            self.buy(size=size)
            logging.info(f'BUY AAPL: RS > 0 and AAPL Close > 50d MA | Date: {self.datas[0].datetime.date(0)} | Size: {size}')

        # Check for sell conditions: RS < 0
        elif rs < 0 and self.position:
            self.sell(size=self.position.size)
            logging.info(f'SELL AAPL: RS < 0 | Date: {self.datas[0].datetime.date(0)} | Size: {self.position.size}')

# Define the lookback period based on the longest indicator params, this must be done to provide a warmup period for indicators
lookback_period = 50  # just use the largest number in params, do not use functions here to define lookback_period

# Fetch and add data. Make sure to add data feeds in the order that they are used in the strategy
aapl_data = bt.feeds.PandasData(dataname=yf.download('AAPL', start_date, end_date), name='AAPL')
spy_data = bt.feeds.PandasData(dataname=yf.download('SPY', start_date, end_date), name='SPY')
cerebro.adddata(aapl_data)
cerebro.adddata(spy_data)

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