Оцінювання ризикованості акцій на фондовому ринку України

Abstract

Досліджено волатильність акцій на фондовому ринку України. Використано методологію дослідження часових рядів за допомогою ARCH-моделей. Досліджено акції емітентів, що увійшли до списку десяти компаній, які у 2015 році користувалися найбільшим попитом на біржовому ринку України. Для акцій кожної компанії побудовано GARCH, GJR та EGARCH моделі з різними параметрами. Серед них вибрано найкращі за допомогою критеріїв Акайке і Шварца та знайдено прогнозні значення волатильності.

In this paper the author examines the volatility of the shares on the stock market of Ukraine. This analysis focuses on the time series investigation by the ARCH estimation technique. We research stocks of issuers included in the list of Top 10 companies that in 2015 were of the greatest demand in the stock market of Ukraine. The stock prices fall or rise depending on the economic situation. The change in stock prices in finances is called volatility. The degree of risk is more convenient to consider the volatility of returns because the value of returns depends on the size or value of the asset at the beginning and at the end of a planned period as well as on the nature of the change in this value during the reporting period. The stronger asset prices deviations from the mean value are, the higher is the risk of this asset. Therefore, volatility is a key concept for market risk assessment and making decisions on investment. It is investigated that the financial time series have specific features, which can only be taken into account by certain econometric models. Econometric models of conditional heteroskedasticity ARCH (autoregressive conditional heteroskedasticity), GARCH (generalized autoregressive conditional heteroscedasticity) and their various modifications become a standard tool for evaluating of volatility changes in recent years. In the article the Ukrainian stock market is described, the series of stock prices of leading Ukrainian companies from April 1, 2009 to August 31, 2016 are analyzed. GARCH, GJR and EGARCH models with different parameters are built for stocks of five selected companies and the forecast value volatility based on them is made.