plot_mv_simple.py

#-- Plot the risk vs. return of randomly generated portfolios
#- Convert the list from before into an array for easy plotting
mean_variance_pairs = np.array(mean_variance_pairs)
risk_free_rate=0 #-- Include risk free rate here for sharpe ratio

#-- Create Plot
fig = go.Figure()
fig.add_trace(go.Scatter(x=mean_variance_pairs[:,1]**0.5, 
                         y=mean_variance_pairs[:,0], 
                      #- Add color scale for sharpe ratio   
                      marker=dict(color=(mean_variance_pairs[:,0]-risk_free_rate)/(mean_variance_pairs[:,1]**0.5), 
                                  showscale=True, 
                                  size=7,
                                  line=dict(width=1),
                                  colorscale="RdBu",
                                  colorbar=dict(title="Sharpe<br>Ratio")
                                 ), 
                      mode='markers'))
#- Add title/labels
fig.update_layout(template='plotly_white',
                  xaxis=dict(title='Annualised Risk (Volatility)'),
                  yaxis=dict(title='Annualised Return'),
                  title='Sample of Random Portfolios',
                  coloraxis_colorbar=dict(title="Sharpe Ratio"))