pyfacts/pyfacts.py

@@ -328,17 +328,11 @@ class TimeSeries(TimeSeriesCore):
         as_on_delta, prior_delta = _preprocess_match_options(as_on_match, prior_match, closest)
 
         current = _find_closest_date(self, as_on, closest_max_days, as_on_delta, if_not_found)
-
         prev_date = as_on - relativedelta(**{return_period_unit: return_period_value})
         if current[1] != str("nan"):
             previous = _find_closest_date(self, prev_date, closest_max_days, prior_delta, if_not_found)
 
-        if (
-            current[1] == str("nan")
-            or previous[1] == str("nan")
-            or current[0] == str("nan")
-            or previous[0] == str("nan")
-        ):
+        if current[1] == str("nan") or previous[1] == str("nan"):
             return as_on, float("NaN")
 
         returns = current[1] / previous[1]
@@ -599,7 +593,7 @@ class TimeSeries(TimeSeriesCore):
         kwargs["to_date"] = kwargs.get("to_date", self.end_date)
 
         rr = self.calculate_rolling_returns(**kwargs)
-        mean_rr = statistics.mean(filter(lambda x: str(x) != "nan", rr.values))
+        mean_rr = statistics.mean(rr.values)
         if annualise_returns:
             mean_rr = (1 + mean_rr) ** (1 / years) - 1
 

pyfacts/statistics.py

@@ -574,10 +574,8 @@ def sortino_ratio(
         "closest": closest,
         "date_format": date_format,
     }
-    average_rr_ts = time_series_data.calculate_rolling_returns(
-        **common_params, annual_compounded_returns=False, if_not_found="nan"
-    )
-    average_rr = statistics.mean(filter(lambda x: str(x) != "nan", average_rr_ts.values))
+    average_rr_ts = time_series_data.calculate_rolling_returns(**common_params, annual_compounded_returns=False)
+    average_rr = statistics.mean(average_rr_ts.values)
     annualized_average_rr = (1 + average_rr) ** (365 / interval_days) - 1
 
     excess_returns = annualized_average_rr - risk_free_rate

pyfacts/utils.py

@@ -188,15 +188,9 @@ def _find_closest_date(
     """
 
     if delta.days < 0 and date < min(data.data):
-        if if_not_found == "nan":
-            return float("NaN"), float("NaN")
-        else:
-            raise DateOutOfRangeError(date, "min")
+        raise DateOutOfRangeError(date, "min")
     if delta.days > 0 and date > max(data.data):
-        if if_not_found == "nan":
-            return float("NaN"), float("NaN")
-        else:
-            raise DateOutOfRangeError(date, "max")
+        raise DateOutOfRangeError(date, "max")
 
     row: tuple = data.get(date, None)
     if row is not None:

tests/test_stats.py

@@ -117,25 +117,25 @@ class TestSortino:
         )
         assert round(sortino, 4) == -5.5233
 
-        sortino = pft.sortino_ratio(
-            ts,
-            risk_free_rate=0.052,
-            from_date="2017-02-05",
-            to_date="2021-12-31",
-            return_period_unit="months",
-            return_period_value=1,
-        )
-        assert round(sortino, 4) == -1.93
+    #     sharpe_ratio = pft.sharpe_ratio(
+    #         ts,
+    #         risk_free_rate=0.052,
+    #         from_date="2017-02-05",
+    #         to_date="2021-12-31",
+    #         return_period_unit="months",
+    #         return_period_value=1,
+    #     )
+    #     assert round(sharpe_ratio, 4) == 0.4898
 
-        sortino = pft.sortino_ratio(
-            ts,
-            risk_free_rate=0.052,
-            from_date="2018-01-01",
-            to_date="2021-12-31",
-            return_period_unit="months",
-            return_period_value=12,
-        )
-        assert round(sortino, 4) == -3.9805
+    #     sharpe_ratio = pft.sharpe_ratio(
+    #         ts,
+    #         risk_free_rate=0.052,
+    #         from_date="2018-01-01",
+    #         to_date="2021-12-31",
+    #         return_period_unit="months",
+    #         return_period_value=12,
+    #     )
+    #     assert round(sharpe_ratio, 4) == 0.3199
 
 
 class TestBeta: