okama.EfficientFrontier.get_monte_carlo

EfficientFrontier.get_monte_carlo(n=100, kind='mean')

Generate N random portfolios with Monte Carlo simulation.

Risk (annualized standard deviation) and Return (CAGR) are calculated for a set of random weights.

Parameters:

nint, default 100

Number of random portfolios to generate with Monte Carlo simulation.

kind{‘mean’,’cagr’}, default ‘mean’

Use CAGR for return if kind=’cagr’, or annualized arithmetic mean if kind=’mean’.

Returns:

DataFrame

Table with Return, Risk and weights values for random portfolios.

Examples

>>> assets = ['SPY.US', 'AGG.US', 'GLD.US']
>>> last_date='2021-07'
>>> base_currency = 'EUR'
>>> y = ok.EfficientFrontier(assets, ccy=base_currency, last_date=last_date)
>>> y.get_monte_carlo(n=10)  # generate 10 random portfolios
       Risk    Return    SPY.US    AGG.US    GLD.US
0  0.099168  0.101667  0.470953  0.205227  0.323819
1  0.099790  0.076282  0.070792  0.558928  0.370280
2  0.129312  0.106620  0.274261  0.050524  0.675215
3  0.102031  0.083311  0.129375  0.443444  0.427182
4  0.102956  0.105136  0.489213  0.146174  0.364614
5  0.095690  0.091834  0.297122  0.335066  0.367812
6  0.103747  0.090285  0.203408  0.334694  0.461898
7  0.148311  0.099617  0.082660  0.120871  0.796470
8  0.115780  0.082983  0.042871  0.422335  0.534794
9  0.093903  0.088553  0.266303  0.387332  0.346365

To plot Monte Carlo simulation result it’s useful to combine in with the Efficien Frontier chart. Additionaly assets points could be plotted with ‘Plot.plot_assets()’.

>>> import matplotlib.pyplot as plt
>>> fig = plt.figure()
>>> # Plot the assets points (optional).
>>> # The same first and last dates, base currency and return type should be used.
>>> y.plot_assets(kind='cagr')
>>> ax = plt.gca()
>>> # Plot random portfolios risk-return points.
>>> mc = y.get_monte_carlo(n=1000, kind='cagr')
>>> ax.scatter(mc.Risk, mc.CAGR, linewidth=0, color='green')
>>> # Plot the Efficient (optional)
>>> df = y.ef_points
>>> ax.plot(df['Risk'], df['CAGR'], color='black', linestyle='dashed', linewidth=3)
>>> # Set the title and axis labels
>>> ax.set_title('Single period Efficient Frontier & Monte Carlo simulation')
>>> ax.set_xlabel('Risk (Standard Deviation)')
>>> ax.set_ylabel('CAGR')
>>> ax.legend()
>>> plt.show()