diff --git a/quantstats_lumi/_plotting/core.py b/quantstats_lumi/_plotting/core.py
index 44c1a08..1dee056 100644
--- a/quantstats_lumi/_plotting/core.py
+++ b/quantstats_lumi/_plotting/core.py
@@ -418,7 +418,7 @@ def plot_histogram(
 
     colors, _, _ = _get_colors(grayscale)
 
-    apply_fnc = _stats.comp if compounded else _np.sum
+    apply_fnc = _stats.comp if compounded else 'sum'
     if benchmark is not None:
         benchmark = (
             benchmark.fillna(0)
@@ -1003,7 +1003,7 @@ def plot_distribution(
     port = _pd.DataFrame(returns.fillna(0))
     port.columns = ["Daily"]
 
-    apply_fnc = _stats.comp if compounded else _np.sum
+    apply_fnc = _stats.comp if compounded else 'sum'
 
     port["Weekly"] = port["Daily"].resample("W-MON").apply(apply_fnc)
     port["Weekly"] = port["Weekly"].ffill()
diff --git a/quantstats_lumi/_plotting/wrappers.py b/quantstats_lumi/_plotting/wrappers.py
index 3b4ec24..3f85f7d 100644
--- a/quantstats_lumi/_plotting/wrappers.py
+++ b/quantstats_lumi/_plotting/wrappers.py
@@ -26,7 +26,6 @@
 import seaborn as _sns
 from matplotlib.ticker import FuncFormatter as _FuncFormatter
 from matplotlib.ticker import StrMethodFormatter as _StrMethodFormatter
-from pandas import DataFrame as _df
 
 from .. import stats as _stats
 from .. import utils as _utils
@@ -552,7 +551,7 @@ def yearly_returns(
     if compounded:
         returns = returns.resample("YE").apply(_stats.comp)
     else:
-        returns = returns.resample("YE").apply(_df.sum)
+        returns = returns.resample("YE").sum()
     returns = returns.resample("YE").last()
 
     fig = _core.plot_returns_bars(
diff --git a/quantstats_lumi/reports.py b/quantstats_lumi/reports.py
index b340fae..8ca94b8 100644
--- a/quantstats_lumi/reports.py
+++ b/quantstats_lumi/reports.py
@@ -993,7 +993,7 @@ def metrics(
 
     # returns
     metrics["~~"] = blank
-    comp_func = _stats.comp if compounded else _np.sum
+    comp_func = _stats.comp if compounded else lambda x: _np.sum(x, axis=0)
 
     today = df.index[-1]  # _dt.today()
     metrics["MTD %"] = comp_func(df[df.index >= _dt(today.year, today.month, 1)]) * pct
diff --git a/quantstats_lumi/stats.py b/quantstats_lumi/stats.py
index f5f99f4..810bab6 100644
--- a/quantstats_lumi/stats.py
+++ b/quantstats_lumi/stats.py
@@ -79,7 +79,7 @@ def get_outliers(data):
         else:
             returns = returns[returns.columns[0]]
 
-    apply_fnc = comp if compounded else _np.sum
+    apply_fnc = comp if compounded else 'sum'
     daily = returns.dropna()
 
     if prepare_returns:
@@ -594,7 +594,7 @@ def cagr(returns, rf=0.0, compounded=True, periods=365):
     if compounded:
         total = comp(total)
     else:
-        total = _np.sum(total)
+        total = _np.sum(total, axis=0)
 
     years = (returns.index[-1] - returns.index[0]).days / periods