Abstract

Investing during a pandemic is very challenging. Even in these difficult times, the investor must appropriately allocate assets into his portfolio. In this article, we discuss investing in the stock market. We are interested in creating portfolios of shares that consist of financial assets. The individual methods we use are designed to provide an allocation of funds in between individual shares. In the modern portfolio theory, the Markowitz model (Markowitz, 1952) is being used to solve these problems. The paper's main goal is to propose an efficient, robust approach to solve the Markowitz optimization problem adjusted for periods of a global decline in financial markets. In our research, we focus on robust optimization. Instead of precisely given input parameters, we propose a set of parameters from which we always select the worst possible parameter (so-called worst-case optimization). The robustness of optimization is achieved using so-called filter matrices. These matrices are used to modify historical data directly during optimization. The proposed model modifies the data by using different lengths of historical returns. Our proposed model is then compared with the original Markowitz non-robust model. We compare these two models using the properties of the second derivative of the optimization problem. Our results are visualized for different levels of investor’s risk aversion. We present our methods on historical price data of five randomly selected companies traded on the US market. By comparing the proposed robust approach with the non-robust one, we show that different lengths of historical returns capture volatility changes earlier. The investor can thus reduce his risk aversion and increase his expected returns.

Highlights

  • The main idea of portfolio management is based on the investor who has chosen a set of financial assets or stock exchange shares from which he wants to build his portfolio

  • We mainly focus on robust optimization problems that expect some uncertainty in input parameters

  • This paper aims to develop a new approach for robust optimization and examine the differences in portfolio optimization models after the application of robust variations

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Summary

Introduction

The main idea of portfolio management is based on the investor who has chosen a set of financial assets or stock exchange shares from which he wants to build his portfolio. The distribution of his money among the shares is crucial for the level of his returns. The basic optimization model often used in modern portfolio theory is known as the Markowitz Mean-Variance model (Markowitz, 1952). The formulation of this model is given in the section Theoretical background of this paper

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