def MonthlyRet(self, hedge=True):
month_year = pd.Series(
self.Ret.index).apply(lambda x: x.year * 100 + x.month)
is_month_end = (~month_year.duplicated('last')).tolist()
if hedge:
monthRet = pd.Series(
stats.aggregate_returns(self.activeRet, 'monthly'))
monthRet.index = self.activeRet.index[is_month_end]
else:
monthRet = pd.Series(stats.aggregate_returns(self.Ret, 'monthly'))
monthRet.index = self.Ret.index[is_month_end]
return monthRet
def BenchmarkMonthlyRet(self):
benchmarkRet = self.BenchmarkRet.reindex(self.Ret.index)
month_year = pd.Series(
self.Ret.index).apply(lambda x: x.year * 100 + x.month)
is_month_end = (~month_year.duplicated('last')).tolist()
monthRet = pd.Series(stats.aggregate_returns(benchmarkRet, 'monthly'))
monthRet.index = self.Ret.index[is_month_end]
return monthRet
def get_metrics_single_model(ret):
return {
"Mean": ret.mean(),
"Mean (Yearly)": aggregate_returns(ret, convert_to="yearly").mean(),
"Standard Deviation": ret.std(),
"Sharpe Ratio": sharpe_ratio(ret, period='monthly'),
"Skewness": skew(ret),
"Kurtosis": kurtosis(ret),
"Max Drawdown": max_drawdown(ret),
}
def YearlyPerformance(self):
monthlyRet = self.MonthlyRet(False) # 单边做多模型月度收益率
benchmarkMonthlyRet = self.BenchmarkMonthlyRet()
hedgeMonthlyRet = self.MonthlyRet(True) # 对冲组合月收益率
a = stats.aggregate_returns(monthlyRet, 'yearly') # 多头组合分年收益
b = stats.aggregate_returns(benchmarkMonthlyRet, 'yearly') # 基准组合分年收益
_l = []
for i, year in enumerate(a.index):
hedgeMonthlyRet_current_year = hedgeMonthlyRet.ix[str(year)]
monthlyRet_current_year = monthlyRet.ix[str(year)]
benchmarkMonthlyRet_current_year = benchmarkMonthlyRet.ix[str(
year)]
hdSharp_current_year = stats.sharpe_ratio(
hedgeMonthlyRet_current_year, annualization=12)
hdMaxDown_current_year = stats.max_drawdown(
hedgeMonthlyRet_current_year)
hdReturn_current_year = stats.annual_return(
hedgeMonthlyRet_current_year, annualization=12)
hdWinRate_current_year = stats.win_rate(
monthlyRet_current_year, benchmarkMonthlyRet_current_year)
_l.append([
hdSharp_current_year, hdReturn_current_year,
hdMaxDown_current_year, hdWinRate_current_year
])
# 计算全年收益表现
hdSharp_all = stats.sharpe_ratio(hedgeMonthlyRet, annualization=12)
hdMaxDown_all = stats.max_drawdown(hedgeMonthlyRet)
hdReturn_all = stats.annual_return(hedgeMonthlyRet, annualization=12)
hdWinRate_all = stats.win_rate(hedgeMonthlyRet, benchmarkMonthlyRet)
_l.append([hdSharp_all, hdReturn_all, hdMaxDown_all, hdWinRate_all])
result = pd.DataFrame(_l,
columns=['夏普比率', '年化收益', '最大回撤', '胜率'],
index=list(a.index) + ['All'])
return result