diff --git a/openseries/_common_model.py b/openseries/_common_model.py
index 5a5d97f9..4cc39a46 100644
--- a/openseries/_common_model.py
+++ b/openseries/_common_model.py
@@ -351,9 +351,9 @@ 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=cast(str, None)).min()
-        )
+        result = wmdf.resample("BME").last().pct_change(
+            fill_method=None,  # type: ignore[arg-type,unused-ignore]
+        ).min()
 
         if self.tsdf.shape[1] == 1:
             return float(result.iloc[0])
@@ -1023,7 +1023,7 @@ def arithmetic_ret_func(
 
         result = (
             self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-            .pct_change(fill_method=cast(str, None))
+            .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
             .mean()
             * time_factor
         )
@@ -1082,9 +1082,9 @@ def vol_func(
             time_factor = how_many / fraction
 
         data = self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-        result = (
-            data.pct_change(fill_method=cast(str, None)).std().mul(sqrt(time_factor))
-        )
+        result = data.pct_change(
+            fill_method=None,  # type: ignore[arg-type,unused-ignore]
+        ).std().mul(sqrt(time_factor))
 
         if self.tsdf.shape[1] == 1:
             return float(cast(SupportsFloat, result.iloc[0]))
@@ -1280,14 +1280,14 @@ 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=cast(str, None))
+                .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
                 .quantile(1 - level, interpolation=interpolation)
                 - self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-                .pct_change(fill_method=cast(str, None))
+                .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
                 .sum()
                 / len(
                     self.tsdf.loc[cast(int, earlier) : cast(int, later)].pct_change(
-                        fill_method=cast(str, None),
+                        fill_method=None,  # type: ignore[arg-type,unused-ignore]
                     ),
                 )
             )
@@ -1295,7 +1295,7 @@ def _var_implied_vol_and_target_func(
             imp_vol = (
                 -sqrt(time_factor)
                 * self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-                .pct_change(fill_method=cast(str, None))
+                .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
                 .quantile(1 - level, interpolation=interpolation)
                 / norm.ppf(level)
             )
@@ -1358,14 +1358,16 @@ 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=cast(str, None))
+            .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
             .sort_values()
             .iloc[
                 : int(
                     ceil(
                         (1 - level)
                         * cvar_df.loc[:, x]  # type: ignore[index]
-                        .pct_change(fill_method=cast(str, None))
+                        .pct_change(
+                            fill_method=None,  # type: ignore[arg-type,unused-ignore]
+                        )
                         .count(),
                     ),
                 )
@@ -1425,7 +1427,7 @@ def downside_deviation_func(
         )
         how_many = (
             self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-            .pct_change(fill_method=cast(str, None))
+            .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
             .count(numeric_only=True)
         )
         if periods_in_a_year_fixed:
@@ -1440,7 +1442,7 @@ def downside_deviation_func(
 
         dddf = (
             self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-            .pct_change(fill_method=cast(str, None))
+            .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
             .sub(min_accepted_return / time_factor)
         )
 
@@ -1543,7 +1545,7 @@ def skew_func(
         )
         result: NDArray[float64] = skew(
             a=self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-            .pct_change(fill_method=cast(str, None))
+            .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
             .to_numpy(),
             bias=True,
             nan_policy="omit",
@@ -1591,7 +1593,7 @@ def kurtosis_func(
         )
         result: NDArray[float64] = kurtosis(
             self.tsdf.loc[cast(int, earlier) : cast(int, later)].pct_change(
-                fill_method=cast(str, None),
+                fill_method=None,  # type: ignore[arg-type,unused-ignore]
             ),
             fisher=True,
             bias=True,
@@ -1688,9 +1690,9 @@ def positive_share_func(
         )
         pos = (
             self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-            .pct_change(fill_method=cast(str, None))[1:][
+            .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=cast(str, None),
+                    fill_method=None,  # type: ignore[arg-type,unused-ignore]
                 )[1:]
                 > zero
             ]
@@ -1698,7 +1700,7 @@ def positive_share_func(
         )
         tot = (
             self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-            .pct_change(fill_method=cast(str, None))[1:]
+            .pct_change(fill_method=None)[1:]  # type: ignore[arg-type,unused-ignore]
             .count()
         )
         share = pos / tot
@@ -1877,7 +1879,7 @@ def omega_ratio_func(
             to_dt=to_date,
         )
         retdf = self.tsdf.loc[cast(int, earlier) : cast(int, later)].pct_change(
-            fill_method=cast(str, None),
+            fill_method=None,  # type: ignore[arg-type,unused-ignore]
         )
         pos = retdf[retdf > min_accepted_return].sub(min_accepted_return).sum()
         neg = retdf[retdf < min_accepted_return].sub(min_accepted_return).sum()
@@ -1966,7 +1968,9 @@ 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]
+        resultdf = DataFrame(vrdf.pct_change(
+            fill_method=None,  # type: ignore[arg-type,unused-ignore]
+        ))
         result = resultdf.loc[period] + 1
         cal_period = result.cumprod(axis="index").iloc[-1] - 1
         if self.tsdf.shape[1] == 1:
@@ -2018,7 +2022,7 @@ def var_down_func(
         )
         result = (
             self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-            .pct_change(fill_method=cast(str, None))
+            .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
             .quantile(1 - level, interpolation=interpolation)
         )
 
@@ -2066,7 +2070,7 @@ def worst_func(
         )
         result = (
             self.tsdf.loc[cast(int, earlier) : cast(int, later)]
-            .pct_change(fill_method=cast(str, None))
+            .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
             .rolling(observations, min_periods=observations)
             .sum()
             .min()
@@ -2113,7 +2117,7 @@ def z_score_func(
             to_dt=to_date,
         )
         zscframe = self.tsdf.loc[cast(int, earlier) : cast(int, later)].pct_change(
-            fill_method=cast(str, None),
+            fill_method=None,  # type: ignore[arg-type,unused-ignore]
         )
         result = (zscframe.iloc[-1] - zscframe.mean()) / zscframe.std()
 
@@ -2183,7 +2187,7 @@ def rolling_return(
         ret_label = cast(tuple[str], self.tsdf.iloc[:, column].name)[0]
         retseries = (
             self.tsdf.iloc[:, column]
-            .pct_change(fill_method=cast(str, None))
+            .pct_change(fill_method=None)  # type: ignore[arg-type,unused-ignore]
             .rolling(observations, min_periods=observations)
             .sum()
         )
@@ -2260,7 +2264,9 @@ 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=cast(str, None))
+        dframe = self.tsdf.iloc[:, column].pct_change(
+            fill_method=None,  # type: ignore[arg-type,unused-ignore]
+        )
         volseries = dframe.rolling(
             observations,
             min_periods=observations,
diff --git a/openseries/series.py b/openseries/series.py
index ed36528c..40703c0f 100644
--- a/openseries/series.py
+++ b/openseries/series.py
@@ -436,7 +436,9 @@ 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]
+        self.tsdf = self.tsdf.pct_change(
+            fill_method=None,   # type: ignore[arg-type,unused-ignore]
+        )
         self.tsdf.iloc[0] = 0
         self.valuetype = ValueType.RTRN
         self.tsdf.columns = MultiIndex.from_arrays(
@@ -696,7 +698,9 @@ 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]
+            ra_df = self.tsdf.pct_change(
+                fill_method=None,  # type: ignore[arg-type,unused-ignore]
+            )
             returns_input = False
         ra_df = ra_df.dropna()
 
diff --git a/openseries/simulation.py b/openseries/simulation.py
index 7725dc95..1e687dcc 100644
--- a/openseries/simulation.py
+++ b/openseries/simulation.py
@@ -123,7 +123,9 @@ def realized_mean_return(self: Self) -> float:
         return cast(
             float,
             (
-                self.results.pct_change(fill_method=cast(str, None)).mean()
+                self.results.pct_change(
+                    fill_method=None,  # type: ignore[arg-type,unused-ignore]
+                ).mean()
                 * self.trading_days_in_year
             ).iloc[0],
         )
@@ -141,7 +143,9 @@ def realized_vol(self: Self) -> float:
         return cast(
             float,
             (
-                self.results.pct_change(fill_method=cast(str, None)).std()
+                self.results.pct_change(
+                    fill_method=None,  # type: ignore[arg-type,unused-ignore]
+                ).std()
                 * sqrt(self.trading_days_in_year)
             ).iloc[0],
         )
diff --git a/poetry.lock b/poetry.lock
index 63f97b8c..380fe528 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1017,13 +1017,13 @@ typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
 
 [[package]]
 name = "pytest"
-version = "8.3.2"
+version = "8.3.3"
 description = "pytest: simple powerful testing with Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "pytest-8.3.2-py3-none-any.whl", hash = "sha256:4ba08f9ae7dcf84ded419494d229b48d0903ea6407b030eaec46df5e6a73bba5"},
-    {file = "pytest-8.3.2.tar.gz", hash = "sha256:c132345d12ce551242c87269de812483f5bcc87cdbb4722e48487ba194f9fdce"},
+    {file = "pytest-8.3.3-py3-none-any.whl", hash = "sha256:a6853c7375b2663155079443d2e45de913a911a11d669df02a50814944db57b2"},
+    {file = "pytest-8.3.3.tar.gz", hash = "sha256:70b98107bd648308a7952b06e6ca9a50bc660be218d53c257cc1fc94fda10181"},
 ]
 
 [package.dependencies]
@@ -1425,4 +1425,4 @@ test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<3.13"
-content-hash = "b1cc6d9dd45b76fb9a89a0b85972b7f0e08ebb19dc005d93b1790763f3e0b541"
+content-hash = "3f77d7875b797a28f719a99957e0fe224a097f9a15bc7e9bd17eaebc50479318"
diff --git a/pyproject.toml b/pyproject.toml
index 92228c14..c2f99f08 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -52,7 +52,7 @@ genbadge = {version = ">=1.1.1,<2.0.0", extras = ["coverage"]}
 mypy = "^1.11.2"
 pandas-stubs = ">=2.1.2,<3.0.0"
 pre-commit = ">=3.7.1,<4.0.0"
-pytest = ">=8.2.2,<9.0.0"
+pytest = "^8.3.3"
 ruff = "^0.6.4"
 types-openpyxl = ">=3.1.2,<4.0.0"
 types-python-dateutil = ">=2.8.2,<3.0.0"