The Variance-Covariance model as a decision support for chartered financial analysts in portfolio optimization

Abstract

This study proposes the Variance-Covariance model to improve decision-making regarding the creation and optimization of an investment portfolio made by Chartered Financial Analysts. To optimize an investment portfolio, these specialists must find, given some profitability, how much they should invest in each of the selected stocks to minimize risk. This is typically achieved using the Mean-Variance model proposed by Harry Markowitz. However, it is observed that the use of the Mean-Variance model does not always lead to an expedited selection of shares that make up an investment portfolio. This is because the behaviour of the portfolio components cannot often be assessed with sufficient confidence in their trends. Financial analysts regularly prefer to compose their portfolios so that not all stocks follow the same direction to achieve greater peace of mind in bearish markets. Thus, in this work, the Variance-Covariance mathematical model is proposed as a complement to charting to support the decision criteria regarding portfolio diversification due to adverse conditions in the stock markets. We elaborate on the hypothesis that financial analysts using the Variance-Covariance matrix will achieve better financial decisions in less time-consuming.