BUG Refactor stability measure. Before was using cumulative returns where cumulative log-returns should have been used. This leads to different values so also fix the test value.

Author: twiecki

pyfolio/tests/test_timeseries.py

@@ -289,7 +289,7 @@ def test_sharpe_2(self, returns, rolling_sharpe_window, expected):
             returns, rolling_sharpe_window).values.tolist()), expected)
 
     @parameterized.expand([
-        (simple_rets, 0.010766923838471554)
+        (simple_rets, 0.10376378866671222)
     ])
     def test_stability_of_timeseries(self, returns, expected):
         self.assertAlmostEqual(

pyfolio/timeseries.py

@@ -474,6 +474,30 @@ def beta(returns, factor_returns):
 
     return alpha_beta(returns, factor_returns)[1]
 
+def stability_of_timeseries(returns):
+    """Determines R-squared of a linear fit to the cumulative
+    log returns. Computes an ordinary least squares linear fit,
+    and returns R-squared.
+
+    Parameters
+    ----------
+    returns : pd.Series
+        Daily returns of the strategy, noncumulative.
+         - See full explanation in tears.create_full_tear_sheet.
+
+    Returns
+    -------
+    float
+        R-squared.
+
+    """
+
+    cum_log_returns = np.log(1 + returns).cumsum()
+    rhat = stats.linregress(np.arange(len(cum_log_returns)),
+                            cum_log_returns.values)[2]
+
+    return rhat
+
 
 SIMPLE_STAT_FUNCS = [
     annual_return,