period.py 文件源码

def calculate_beta(self):
        """

        .. math::

            \\beta_a = \\frac{\mathrm{Cov}(r_a,r_p)}{\mathrm{Var}(r_p)}

        http://en.wikipedia.org/wiki/Beta_(finance)
        """
        # it doesn't make much sense to calculate beta for less than two days,
        # so return nan.
        if len(self.algorithm_returns) < 2:
            return np.nan, np.nan, np.nan, np.nan, []

        returns_matrix = np.vstack([self.algorithm_returns,
                                    self.benchmark_returns])
        C = np.cov(returns_matrix, ddof=1)

        # If there are missing benchmark values, then we can't calculate the
        # beta.
        if not np.isfinite(C).all():
            return np.nan, np.nan, np.nan, np.nan, []

        eigen_values = la.eigvals(C)
        condition_number = max(eigen_values) / min(eigen_values)
        algorithm_covariance = C[0][1]
        benchmark_variance = C[1][1]
        beta = algorithm_covariance / benchmark_variance

        return (
            beta,
            algorithm_covariance,
            benchmark_variance,
            condition_number,
            eigen_values
        )