ABSTRACT
Decision making on the capital market through the quantitative approaches of operations research are often based on historical data that the investor naturally observes because history can have a significant impact on a future development. It is therefore natural that this article studies the strength of the effect of the selected historical periods on investment decision, or the composition of the investment portfolio. The basis of this empirical study is a mean-semivariance model that shows certain benefits over the notorious mean-variance model standardly used to a portfolio selection. Return and risk are calculated from several historical time periods with different lengths in the spirit of determined investment strategies. The time analysis also covers the study of the effect of the outbreak of the COVID-19 pandemic on the portfolio shape. The effect of historical period, or data, on the portfolio composition is empirically studied on the capital market with open unit trusts. The composition of the portfolios is analyzed and compared, as well as the efficient frontiers, through various historical periods. This reveals the considerable and different influence of the observed history on the composition of portfolios, and thus on their characteristics. In addition, the performed time analysis offers interesting overview of the participation of funds in portfolios. Thus, 'promising' funds as well as funds with negligible potential can be identified.
ABSTRACT
Companies in the energy sector, due to their important role in the economy and the specificity of energy sources, are exposed to many types of risk, ranging from the risk associated with the company’s operations and the global economic and political situation in the world. Energy companies are usually large capital companies whose shares are listed on the stock market. The mentioned risk factors may shape the risk level of these companies. The study aims to examine the relationship between market and accounting risk measures for Polish energy companies listed on the Warsaw Stock Exchange. This paper uses market and accounting betas in the conventional and downside approach. In addition to market measures of total risk, it also examines the variability of ROA for energy companies. The study of the relationship between market risk measures and accounting risk measures was based on Pearson’s correlation coefficient, standard linear regression, and quantile regression. The relationship between market and accounting measures of total and systematic risk was identified. Moreover, quantile regressions revealed that the slope for accounting variables varies across the quantiles. Our research shows that for energy companies not listed on the capital markets, for which no market risk measures can be derived, accounting betas and downside accounting can be useful tools in risk analysis. The contribution of the article to the risk analysis of energy companies is the use of unpopular accounting beta factors and a new modification of these coefficients for downside risk.