diff --git a/backtester/statistics/charts.py b/backtester/statistics/charts.py
index f0333a3..2bdea84 100644
--- a/backtester/statistics/charts.py
+++ b/backtester/statistics/charts.py
@@ -5,59 +5,59 @@ import altair as alt
 
 def returns_chart(report):
     # Time interval selector
-    time_interval = alt.selection(type="interval", encodings=["x"])
+    time_interval = alt.selection(type='interval', encodings=['x'])
 
     # Area plot
-    areas = alt.Chart().mark_area(opacity=0.6).encode(x='index:T',
-                                                      y=alt.Y("accumulated return:Q", axis=alt.Axis(format="%")))
+    areas = alt.Chart().mark_area(opacity=0.7).encode(x='index:T',
+                                                      y=alt.Y('accumulated return:Q', axis=alt.Axis(format='%')))
 
     # Nearest point selector
-    nearest = alt.selection(type="single", nearest=True, on="mouseover", fields=["index"], empty="none")
+    nearest = alt.selection(type='single', nearest=True, on='mouseover', fields=['index'], empty='none')
 
     points = areas.mark_point().encode(opacity=alt.condition(nearest, alt.value(1), alt.value(0)))
 
     # Transparent date selector
     selectors = alt.Chart().mark_point().encode(
-        x="index:T",
+        x='index:T',
         opacity=alt.value(0),
     ).add_selection(nearest)
 
-    text = areas.mark_text(align="left", dx=5,
-                           dy=-5).encode(text=alt.condition(nearest, "accumulated return:Q", alt.value(" ")))
+    text = areas.mark_text(
+        align='left', dx=5,
+        dy=-5).encode(text=alt.condition(nearest, 'accumulated return:Q', alt.value(' '))).transform_calculate(
+            label='datum.y + " %"')
 
-    layered = alt.layer(areas.encode(
-        alt.X('index:T', axis=alt.Axis(title="date"), scale=alt.Scale(domain=time_interval))),
-                        selectors,
+    layered = alt.layer(selectors,
                         points,
                         text,
+                        areas.encode(
+                            alt.X('index:T', axis=alt.Axis(title='date'), scale=alt.Scale(domain=time_interval))),
                         width=700,
                         height=350,
-                        title="Returns over time")
+                        title='Returns over time')
 
     lower = areas.properties(width=700, height=70).add_selection(time_interval)
 
-    chart = alt.vconcat(layered, lower, data=report.reset_index())
-
-    return chart
+    return alt.vconcat(layered, lower, data=report.reset_index())
 
 
 def returns_histogram(report):
-    bar = alt.Chart(report).mark_bar().encode(x=alt.X("% change:Q",
+    bar = alt.Chart(report).mark_bar().encode(x=alt.X('% change:Q',
                                                       bin=alt.BinParams(maxbins=100),
                                                       axis=alt.Axis(format='%')),
-                                              y="count():Q")
+                                              y='count():Q')
     return bar
 
 
 def monthly_returns_heatmap(report):
-    resample = report.resample("M")["capital"].last()
+    resample = report.resample('M')['capital'].last()
     monthly_returns = resample.pct_change().reset_index()
     monthly_returns['capital'].iat[0] = resample.iloc[0] / report.iloc[0]['capital'] - 1
-    monthly_returns.columns = ["date", "capital"]
+    monthly_returns.columns = ['date', 'capital']
 
     chart = alt.Chart(monthly_returns).mark_rect().encode(
-        alt.X("year(date):O", title="Year"), alt.Y("month(date):O", title="Month"),
-        alt.Color("mean(capital)", title="Return", scale=alt.Scale(scheme="redyellowgreen")),
-        alt.Tooltip("mean(capital)", format=".2f")).properties(title="Monthly Returns")
+        alt.X('year(date):O', title='Year'), alt.Y('month(date):O', title='Month'),
+        alt.Color('mean(capital)', title='Return', scale=alt.Scale(scheme='redyellowgreen')),
+        alt.Tooltip('mean(capital)', format='.2f')).properties(title='Monthly Returns')
 
     return chart