diff --git a/quantstats_lumi/.DS_Store b/quantstats_lumi/.DS_Store
new file mode 100644
index 0000000..e83d81a
Binary files /dev/null and b/quantstats_lumi/.DS_Store differ
diff --git a/quantstats_lumi/_plotting/wrappers.py b/quantstats_lumi/_plotting/wrappers.py
index 1866ed6..dd1e28c 100644
--- a/quantstats_lumi/_plotting/wrappers.py
+++ b/quantstats_lumi/_plotting/wrappers.py
@@ -82,7 +82,11 @@ def snapshot(
         returns.columns = strategy_colname
 
     colors = _GRAYSCALE_COLORS if grayscale else _FLATUI_COLORS
-    returns = _utils.make_portfolio(returns.dropna(), 1, mode).pct_change().fillna(0)
+    returns = (
+        _utils.make_portfolio(returns.dropna(), 1, mode)
+        .pct_change(fill_method=None)
+        .fillna(0)
+    )
 
     if figsize is None:
         size = list(_plt.gcf().get_size_inches())
diff --git a/quantstats_lumi/utils.py b/quantstats_lumi/utils.py
index d2d4c9d..22fd986 100644
--- a/quantstats_lumi/utils.py
+++ b/quantstats_lumi/utils.py
@@ -17,13 +17,15 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-import io as _io
 import datetime as _dt
-import pandas as _pd
+import inspect
+import io as _io
+
 import numpy as _np
+import pandas as _pd
 import yfinance as _yf
+
 from . import stats as _stats
-import inspect
 
 
 def _mtd(df):
@@ -208,9 +210,9 @@ def _prepare_returns(data, rf=0.0, nperiods=None):
     if isinstance(data, _pd.DataFrame):
         for col in data.columns:
             if data[col].dropna().min() >= 0 and data[col].dropna().max() > 1:
-                data[col] = data[col].pct_change()
+                data[col] = data[col].pct_change(fill_method=None)
     elif data.min() >= 0 and data.max() > 1:
-        data = data.pct_change()
+        data = data.pct_change(fill_method=None)
 
     # cleanup data
     data = data.replace([_np.inf, -_np.inf], float("NaN"))
@@ -239,7 +241,7 @@ def download_returns(ticker, period="max", proxy=None):
         params["start"] = period[0]
     else:
         params["period"] = period
-    return _yf.download(**params)["Close"].pct_change()
+    return _yf.download(**params)["Close"].pct_change(fill_method=None)
 
 
 def _prepare_benchmark(benchmark=None, period="max", rf=0.0, prepare_returns=True):
@@ -259,14 +261,13 @@ def _prepare_benchmark(benchmark=None, period="max", rf=0.0, prepare_returns=Tru
         benchmark = benchmark[benchmark.columns[0]].copy()
 
     if isinstance(period, _pd.DatetimeIndex) and set(period) != set(benchmark.index):
-
         # Adjust Benchmark to Strategy frequency
         benchmark_prices = to_prices(benchmark, base=1)
         new_index = _pd.date_range(start=period[0], end=period[-1], freq="D")
         benchmark = (
             benchmark_prices.reindex(new_index, method="bfill")
             .reindex(period)
-            .pct_change()
+            .pct_change(fill_method=None)
             .fillna(0)
         )
         benchmark = benchmark[benchmark.index.isin(period)]