Merge pull request #18 from ricequant/develop

Develop

rqrisk/risk.py

@@ -22,7 +22,7 @@
 import numpy as np
 from statsmodels.formula.api import ols
 
-from .utils import indicator_property, IndicatorProperty, annual_factor, safe_div, DAILY
+from .utils import indicator_property, IndicatorProperty, annual_factor, safe_div, DAILY, deprecate_property
 
 
 class Risk(object):
@@ -54,6 +54,18 @@ def benchmark_return(self):
     def benchmark_annual_return(self):
         return (1 + self.benchmark_return) ** (self._annual_factor / self.period_count) - 1
 
+    @indicator_property()
+    def arithmetic_excess_return(self):
+        return self.return_rate - self.benchmark_return
+
+    @indicator_property()
+    def geometric_excess_return(self):
+        return (1 + self.return_rate) / (1 + self.benchmark_return) - 1
+
+    @indicator_property()
+    def geometric_excess_annual_return(self):
+        return (1 + self.annual_return) / (1 + self.benchmark_annual_return) - 1
+
     @indicator_property(min_period_count=2)
     def alpha(self):
         # annualized Jensen's alpha：https://en.wikipedia.org/wiki/Jensen%27s_alpha
@@ -104,14 +116,14 @@ def _calc_cum(returns):
         return df_cum
 
     @classmethod
-    def _calc_max_drawdown(cls, returns):
-        df_cum = cls._calc_cum(returns)
-        max_return = np.maximum.accumulate(df_cum)
-        return abs(((df_cum - max_return) / max_return).min())
+    def _calc_max_drawdown(cls, cum_nav):
+        max_nav = np.maximum.accumulate(cum_nav)
+        return abs(((cum_nav - max_nav) / max_nav).min())
 
     @indicator_property()
     def max_drawdown(self):
-        return self._calc_max_drawdown(self._portfolio)
+        cum_returns = self._calc_cum(self._portfolio)
+        return self._calc_max_drawdown(cum_returns)
 
     @indicator_property(min_period_count=2, value_when_pc_not_satisfied=0.)
     def tracking_error(self):
@@ -167,12 +179,12 @@ def calmar(self):
         else:
             return self.annual_return / self.max_drawdown
 
-    @indicator_property()
+    @deprecate_property
     def excess_return_rate(self):
         # activate return rate
         return np.expm1(np.log1p(self._active_returns).sum())
 
-    @indicator_property()
+    @deprecate_property
     def excess_annual_return(self):
         # active annual return
         return (1 + self.excess_return_rate) ** (self._annual_factor / self.period_count) - 1
@@ -186,9 +198,15 @@ def excess_volatility(self):
     def excess_annual_volatility(self):
         return self.excess_volatility * (self._annual_factor ** 0.5)
 
+    @indicator_property(min_period_count=1)
+    def geometric_excess_drawdown(self):
+        excess = self._calc_cum(self._portfolio) / self._calc_cum(self._benchmark)
+        return self._calc_max_drawdown(excess)
+
     @indicator_property(min_period_count=1)
     def excess_max_drawdown(self):
-        return self._calc_max_drawdown(self._active_returns)
+        cum_returns = self._calc_cum(self._active_returns)
+        return self._calc_max_drawdown(cum_returns)
 
     @indicator_property()
     def var(self):

rqrisk/utils.py

@@ -16,6 +16,10 @@
 #         详细的授权流程，请联系 [email protected] 获取。
 
 import numpy as np
+import logging
+
+
+logger = logging.getLogger()
 
 
 class IndicatorProperty:
@@ -78,3 +82,14 @@ def safe_div(dividend, divisor):
     if divisor == 0:
         return np.nan
     return dividend / divisor
+
+
+def deprecate_property(func):
+
+    @property
+    def inner(self):
+        logger.warning("\"{}\" is deprecate.".format(func.__name__))
+        return func(self)
+
+    return inner
+

setup.cfg

@@ -5,7 +5,7 @@
 
 [metadata]
 name = rqrisk
-version = 1.0.5
+version = 1.0.6
 
 [versioneer]
 VCS = git

test.py

@@ -305,6 +305,19 @@ def _assert(returns, benchmark, ulcer_performance_index):
         assert_almost_equal(r.ulcer_performance_index, ulcer_performance_index)
 
     _assert(positive_returns, simple_benchmark, np.nan)
-    _assert(negative_returns, simple_benchmark, -0.019864148204580486)
-    _assert(weekly_returns, simple_weekly_benchamrk, -0.014606674809517502)
+    _assert(negative_returns, simple_benchmark, -0.017162734495347234)
+    _assert(weekly_returns, simple_weekly_benchamrk, 0.011223184970109419)
+
+
+def test_excess_index():
+
+    def _assert(returns, benchmark, arithmetic_excess_return, geometric_excess_return, geometric_excess_annual_return):
+        r = _r(returns, benchmark, 0)
+        assert_almost_equal(r.arithmetic_excess_return, arithmetic_excess_return)
+        assert_almost_equal(r.geometric_excess_return, geometric_excess_return)
+        assert_almost_equal(r.geometric_excess_annual_return, geometric_excess_annual_return)
+
+    _assert(one_return, one_benchmark, 0, 0, 0)
+    _assert(simple_benchmark, zero_benchmark, 0.0936852726843609, 0.09368527268436089, 11.274002099240212)
+