Factor Modeling, Portfolio Construction, Python, Log Returns, Finance.
np.column_stack( (np.ones(len(self.log_returns)), self.factors)) results = {} for ticker in self.log_returns.columns: y = self.log_returns[ticker].values betas = np.linalg.lstsq(factors_matrix, y, rcond=None)[0] results[ticker] = betas[1:] return results def validate_model(self): # Implement model