a1d1c2ce8d20099a51a3a55d0fcb18659a3e34c9,QUANTAXIS/QAARP/QARisk.py,QA_Risk,calc_sortino,#QA_Risk#Any#Any#Any#,597

Before Change

        // Calculate expected return and std dev of downside returns
        expected_return = daily_returns.mean()
        down_stdev = negative_returns.std()
        
        // Calculate the sortino ratio
        sortino_ratio = (expected_return - rfr)/down_stdev
        // 这里不知道计算年化率如何

After Change

        target = 0

        // Calcualte the daily returns from price data
        df = pd.DataFrame(columns=["Returns","downside_returns"], 
                          index=self.assets.index)
        df["Returns"] = (self.assets.values / self.assets.shift(1).values) - 1
        df["downside_returns"] = 0

        // Select the negative returns only
        df.loc[df["Returns"] < target, "downside_returns"] = df["Returns"] ** 2
        expected_return = df["Returns"].mean()

        // Calculate expected return and std dev of downside returns
        down_stdev = np.sqrt(df["downside_returns"].mean())

        // Calculate the sortino ratio
        sortino_ratio = (expected_return - rfr) / down_stdev

Instances