Factor Modeling, Portfolio Construction, Python, Log Returns, Finance.
log_returns = np.log(data['Close'] / data['Close'].shift(1)) return log_returns # Download data for tickers 'AAPL', 'AMZN', 'GOOGL' from 2019-01-01 to 2024-04-30 preprocessor = DataPreprocessing( tickers=['AAPL', 'AMZN', 'GOOGL'], start_date='2019-01-01', end_date='2024-04-30') data =