Factor Modeling, Portfolio Construction, Python, Log Returns, Finance.
Information Ratio for the portfolio # Assume benchmark as the average factor returns benchmark_returns = np.mean(self.factor_model, axis=0) excess_returns = np.dot(self.portfolio_weights, benchmark_returns) - np.mean(benchmark_returns) tracking_error = np.std( benchmark_returns -