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Portfolio Optimization

Portfolio Optimization is used for risk-averse investors to construct portfolios to optimize or maximize expected return based on a given level of market risk, emphasizing that risk is an inherent part of higher reward

This notebook:

  1. Runs an example Monte Carlo Simulation for an optimal portfolio with resulting returns
  2. Creates an Efficient Frontier which is used to identify a set of optimal portfolios that offers the highest expected return for a defined level of risk or the lowest risk for a given level of expected return

Monte Carlo simulations are used by analyst to determine the expected value and optimal distribution of a portfolio.

In [1]:
import numpy as np
import pandas as pd
import hvplot.pandas  # noqa