new solution to mypy opinion on pandas.pct_change(fill_method). no lo…

…nger explicitly required with new pandas_stubs
CaptorAB · Sep 11, 2024 · ce39144 · ce39144
1 parent e5b810d
commit ce39144
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Showing 4 changed files with 30 additions and 62 deletions.
diff --git a/openseries/_common_model.py b/openseries/_common_model.py
@@ -351,9 +351,7 @@ def worst_month(self: Self) -> float | Series[float]:
         """
         wmdf = self.tsdf.copy()
         wmdf.index = DatetimeIndex(wmdf.index)
-        result = wmdf.resample("BME").last().pct_change(
-            fill_method=None,  # type: ignore[arg-type,unused-ignore]
-        ).min()
+        result = wmdf.resample("BME").last().pct_change().min()
 
         if self.tsdf.shape[1] == 1:
             return float(result.iloc[0])
@@ -1023,8 +1021,7 @@ def arithmetic_ret_func(
 
         result = (
             self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-            .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
-            .mean()
+            .pct_change().mean()
             * time_factor
         )
 
@@ -1082,9 +1079,7 @@ def vol_func(
             time_factor = how_many / fraction
 
         data = self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-        result = data.pct_change(
-            fill_method=None,  # type: ignore[arg-type,unused-ignore]
-        ).std().mul(sqrt(time_factor))
+        result = data.pct_change().std().mul(sqrt(time_factor))
 
         if self.tsdf.shape[1] == 1:
             return float(cast(SupportsFloat, result.iloc[0]))
@@ -1280,22 +1275,20 @@ def _var_implied_vol_and_target_func(
         if drift_adjust:
             imp_vol = (-sqrt(time_factor) / norm.ppf(level)) * (
                 self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-                .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
+                .pct_change()
                 .quantile(1 - level, interpolation=interpolation)
                 - self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-                .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
+                .pct_change()
                 .sum()
                 / len(
-                    self.tsdf.loc[cast(int, earlier) : cast(int, later)].pct_change(
-                        fill_method=None,  # type: ignore[arg-type,unused-ignore]
-                    ),
+                    self.tsdf.loc[cast(int, earlier) : cast(int, later)].pct_change(),
                 )
             )
         else:
             imp_vol = (
                 -sqrt(time_factor)
                 * self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-                .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
+                .pct_change()
                 .quantile(1 - level, interpolation=interpolation)
                 / norm.ppf(level)
             )
@@ -1358,16 +1351,14 @@ def cvar_down_func(
         cvar_df = self.tsdf.loc[cast(int, earlier) : cast(int, later)].copy(deep=True)
         result = [
             cvar_df.loc[:, x]  # type: ignore[call-overload,index]
-            .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
+            .pct_change()
             .sort_values()
             .iloc[
                 : int(
                     ceil(
                         (1 - level)
                         * cvar_df.loc[:, x]  # type: ignore[index]
-                        .pct_change(
-                            fill_method=None,  # type: ignore[arg-type,unused-ignore]
-                        )
+                        .pct_change()
                         .count(),
                     ),
                 )
@@ -1427,7 +1418,7 @@ def downside_deviation_func(
         )
         how_many = (
             self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-            .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
+            .pct_change()
             .count(numeric_only=True)
         )
         if periods_in_a_year_fixed:
@@ -1442,7 +1433,7 @@ def downside_deviation_func(
 
         dddf = (
             self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-            .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
+            .pct_change()
             .sub(min_accepted_return / time_factor)
         )
 
@@ -1545,7 +1536,7 @@ def skew_func(
         )
         result: NDArray[float64] = skew(
             a=self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-            .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
+            .pct_change()
             .to_numpy(),
             bias=True,
             nan_policy="omit",
@@ -1592,9 +1583,7 @@ def kurtosis_func(
             to_dt=to_date,
         )
         result: NDArray[float64] = kurtosis(
-            self.tsdf.loc[cast(int, earlier) : cast(int, later)].pct_change(
-                fill_method=None,  # type: ignore[arg-type,unused-ignore]
-            ),
+            self.tsdf.loc[cast(int, earlier) : cast(int, later)].pct_change(),
             fisher=True,
             bias=True,
             nan_policy="omit",
@@ -1690,18 +1679,15 @@ def positive_share_func(
         )
         pos = (
             self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-            .pct_change(fill_method=None)[1:][  # type: ignore[arg-type,unused-ignore]
-                self.tsdf.loc[cast(int, earlier) : cast(int, later)].pct_change(
-                    fill_method=None,  # type: ignore[arg-type,unused-ignore]
-                )[1:]
+            .pct_change()[1:][
+                self.tsdf.loc[cast(int, earlier) : cast(int, later)].pct_change()[1:]
                 > zero
             ]
             .count()
         )
         tot = (
             self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-            .pct_change(fill_method=None)[1:]  # type: ignore[arg-type,unused-ignore]
-            .count()
+            .pct_change().count()
         )
         share = pos / tot
         if self.tsdf.shape[1] == 1:
@@ -1878,9 +1864,7 @@ def omega_ratio_func(
             from_dt=from_date,
             to_dt=to_date,
         )
-        retdf = self.tsdf.loc[cast(int, earlier) : cast(int, later)].pct_change(
-            fill_method=None,  # type: ignore[arg-type,unused-ignore]
-        )
+        retdf = self.tsdf.loc[cast(int, earlier) : cast(int, later)].pct_change()
         pos = retdf[retdf > min_accepted_return].sub(min_accepted_return).sum()
         neg = retdf[retdf < min_accepted_return].sub(min_accepted_return).sum()
         ratio = pos / -neg
@@ -1968,9 +1952,7 @@ def value_ret_calendar_period(
             period = "-".join([str(year), str(month).zfill(2)])
         vrdf = self.tsdf.copy()
         vrdf.index = DatetimeIndex(vrdf.index)
-        resultdf = DataFrame(vrdf.pct_change(
-            fill_method=None,  # type: ignore[arg-type,unused-ignore]
-        ))
+        resultdf = DataFrame(vrdf.pct_change())
         result = resultdf.loc[period] + 1
         cal_period = result.cumprod(axis="index").iloc[-1] - 1
         if self.tsdf.shape[1] == 1:
@@ -2022,8 +2004,7 @@ def var_down_func(
         )
         result = (
             self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-            .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
-            .quantile(1 - level, interpolation=interpolation)
+            .pct_change().quantile(1 - level, interpolation=interpolation)
         )
 
         if self.tsdf.shape[1] == 1:
@@ -2070,7 +2051,7 @@ def worst_func(
         )
         result = (
             self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-            .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
+            .pct_change()
             .rolling(observations, min_periods=observations)
             .sum()
             .min()
@@ -2116,9 +2097,7 @@ def z_score_func(
             from_dt=from_date,
             to_dt=to_date,
         )
-        zscframe = self.tsdf.loc[cast(int, earlier) : cast(int, later)].pct_change(
-            fill_method=None,  # type: ignore[arg-type,unused-ignore]
-        )
+        zscframe = self.tsdf.loc[cast(int, earlier) : cast(int, later)].pct_change()
         result = (zscframe.iloc[-1] - zscframe.mean()) / zscframe.std()
 
         if self.tsdf.shape[1] == 1:
@@ -2187,8 +2166,7 @@ def rolling_return(
         ret_label = cast(tuple[str], self.tsdf.iloc[:, column].name)[0]
         retseries = (
             self.tsdf.iloc[:, column]
-            .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
-            .rolling(observations, min_periods=observations)
+            .pct_change().rolling(observations, min_periods=observations)
             .sum()
         )
         retdf = retseries.dropna().to_frame()
@@ -2264,9 +2242,7 @@ def rolling_vol(
         else:
             time_factor = self.periods_in_a_year
         vol_label = cast(tuple[str, ValueType], self.tsdf.iloc[:, column].name)[0]
-        dframe = self.tsdf.iloc[:, column].pct_change(
-            fill_method=None,  # type: ignore[arg-type,unused-ignore]
-        )
+        dframe = self.tsdf.iloc[:, column].pct_change()
         volseries = dframe.rolling(
             observations,
             min_periods=observations,

diff --git a/openseries/series.py b/openseries/series.py
@@ -436,9 +436,7 @@ def value_to_ret(self: Self) -> Self:
             The returns of the values in the series
 
         """
-        self.tsdf = self.tsdf.pct_change(
-            fill_method=None,   # type: ignore[arg-type,unused-ignore]
-        )
+        self.tsdf = self.tsdf.pct_change()
         self.tsdf.iloc[0] = 0
         self.valuetype = ValueType.RTRN
         self.tsdf.columns = MultiIndex.from_arrays(
@@ -698,9 +696,7 @@ def running_adjustment(
             returns_input = True
         else:
             values = [cast(float, self.tsdf.iloc[0, 0])]
-            ra_df = self.tsdf.pct_change(
-                fill_method=None,  # type: ignore[arg-type,unused-ignore]
-            )
+            ra_df = self.tsdf.pct_change()
             returns_input = False
         ra_df = ra_df.dropna()
 

diff --git a/openseries/simulation.py b/openseries/simulation.py
@@ -123,9 +123,7 @@ def realized_mean_return(self: Self) -> float:
         return cast(
             float,
             (
-                self.results.pct_change(
-                    fill_method=None,  # type: ignore[arg-type,unused-ignore]
-                ).mean()
+                self.results.pct_change().mean()
                 * self.trading_days_in_year
             ).iloc[0],
         )
@@ -143,9 +141,7 @@ def realized_vol(self: Self) -> float:
         return cast(
             float,
             (
-                self.results.pct_change(
-                    fill_method=None,  # type: ignore[arg-type,unused-ignore]
-                ).std()
+                self.results.pct_change().std()
                 * sqrt(self.trading_days_in_year)
             ).iloc[0],
         )

diff --git a/poetry.lock b/poetry.lock