Added Legend to Cumulative Returns Plot

functions.py

@@ -17,6 +17,7 @@ init_notebook_mode(connected=True)
 # Hiding Warnings
 import warnings
 warnings.filterwarnings('ignore')
+
 def perform_portfolio_analysis(df, tickers_weights):
     """
     This function takes historical stock data and the weights of the securities in the portfolio,
@@ -58,7 +59,7 @@ def perform_portfolio_analysis(df, tickers_weights):
             individual_sharpe[ticker] = sharpe # Adding Sharpe Ratio for each ticker
 
             # Creating subplots for comparison across securities
-            fig1 = make_subplots(rows = 1, cols = 2, horizontal_spacing=0.2,
+            fig1 = make_subplots(rows = 1, cols = 2, horizontal_spacing=0.25,
                             column_titles=['Historical Performance Assets', 'Risk-Reward'],
                             column_widths=[.55, .45],
                             shared_xaxes=False, shared_yaxes=False)
@@ -70,7 +71,7 @@ def perform_portfolio_analysis(df, tickers_weights):
                                   mode = 'lines',
                                   name = ticker,
                                   hovertemplate = '%{y:.2f}%',
-                                  showlegend=False),
+                                  showlegend=True),
                             row=1, col=1)
 
     # Defining colors for markers on the second subplot
@@ -99,7 +100,9 @@ def perform_portfolio_analysis(df, tickers_weights):
     },
                        template = 'plotly_white',
                        height = 650, width = 1250,
-                       hovermode = 'x unified')
+                       hovermode = 'x unified',
+                       legend_x=.45,
+                       legend_y=.5)
         
     fig1.update_yaxes(title_text='Returns (%)', col=1)
     fig1.update_yaxes(title_text='Returns (%)', col = 2)
@@ -152,7 +155,7 @@ def portfolio_vs_benchmark(port_returns, benchmark_returns):
     benchmark_sharpe = (exces_benchmark_returns.mean() / benchmark_returns.std() * np.sqrt(252)).round(2)
 
     # Creating a subplot to compare portfolio performance with the benchmark
-    fig2 = make_subplots(rows = 1, cols = 2, horizontal_spacing=0.2,
+    fig2 = make_subplots(rows = 1, cols = 2, horizontal_spacing=0.25,
                         column_titles=['Cumulative Returns', 'Portfolio Risk-Reward'],
                         column_widths=[.55, .45],
                         shared_xaxes=False, shared_yaxes=False)
@@ -195,7 +198,10 @@ def portfolio_vs_benchmark(port_returns, benchmark_returns):
     },
                       template = 'plotly_white',
                       height = 650, width = 1250,
-                      hovermode = 'x unified')
+                      hovermode = 'x unified',
+                      #legend_x=.45,
+                      #legend_y=.5
+                      )
     
     fig2.update_yaxes(title_text='Cumulative Returns (%)', col=1)
     fig2.update_yaxes(title_text='Cumulative Returns (%)', col = 2)