Optimization of the mean-absolute deviation portfolio investment in some mining stocks using the singular covariance matrix method

Abstract

Investing in mining stocks, investors often face risk problems. Usually to minimize risk, it is done by forming an investment portfolio. This paper aims to discuss the optimization of the investment portfolio. The data analyzed are several mining stocks traded on the capital market in Indonesia. Optimization is done using the mean-absolute deviation model with the singular covariance matrix method and the non-singular covariance matrix method to determine the optimal weight of the two existing methods. Based on the results of the optimization, we can obtain a weight allocation composition that provides an optimal portfolio. In addition, we also estimate the amount of return on expectations and risks in the optimal portfolio formed. So that the composition of this optimal weight can be used as a consideration for investors in investing their capital in several analyzed mining stocks.