Portfolio Allocation Optimization with US Equities

Abstract

As a result of the worldwide pandemic, many industries are in need of growth stimuli, and the US equity markets, as the main growth engine, have intrigued investor interest. This article renders a performance analysis using the weights portfolio optimization given as a focal process that is skillfully implemented by financial practitioners. Each portfolio which includes Apple, IBM, Microsoft, Home Depot, Starbucks, NIKE, P&G, QUALCOMM, and JPM, gathers weekly return data from January 2017 to December 2020 and performs a Monte Carlo simulation. The amount of portfolio alternatives will be defined by the strategies being utilized, and it will choose ten stocks from a pool of 100 stocks to form a portfolio. Asset allocation strategies with Mean-Variance and Minimum Variance were constructed using the efficient frontier. Comparing a portfolio's asset allocation performances to that of the benchmark, the S&P 500 index, and an equally weighted strategy portfolio, with respect to asset allocation, the portfolio with the highest Sharpe ratio is the most optimal. The results in this study benefit investors and industry stakeholders in the post-covid era.