The Application of the Main Components in Investment Basket Management: A Case Study of Fifty Stock Exchange Companies

Establishing an investment portfolio is one of the main concerns of managers and investors who are always looking for an effort to form the best investment basket so that they can achieve the most returns. So far, there have been many ways to form an investment basket, the most famous of which is Maritz's approach. The average theory of variance has many practical drawbacks due to the difficulty in estimating the expected returns and covariance for different asset classes. The purpose of this study is to maximize risk -adjusted return on the portfolio using PCA method in a data base of stock returns. The data base used for this case study is the daily data modified of 50 top stock and relevant stock index companies for the period 25/4/2016 to 7/2/2021 for 1027 trading days. We use a dimensional reduction algorithm (PCA) to allocate capital to different asset classes to maximize risk -adjusted returns and the results are compared with the equal weight allocation approach (1/N). There is also a post -test framework for evaluating the performance of the investment baskets provided. According to the results, the variance explained by the three main components can be an indicator for identifying the most important business risks.