Abstract
The most popular methods for dynamic risk measures – Value-at-Risk (VaR) and Conditional VaR (CVaR) estimating were analyzed, description and comparative analysis of the methods were fulfilled, recommendations on the use were given. Results of the research were presented in the form of a classification scheme of dynamic risk measures estimating that facilitates the choice of an estimation method. The GARCH-based models of dynamic risk measures VaR and CVaR evaluation for artificially generated series and two time series of log return on a daily basis of the most well-known Asian stock indexes Nikkey225 Stock Index and CSI30 were constructed to illustrate the effectiveness of the proposed scheme. A qualitative analysis of the proposed models was conducted. To analyze the quality of the dynamic VaR estimations the Cupets test and the Cristoffersen test were used. For CVaR estimations the V-test was used as quality test. The tests results confirm the high quality of obtained estimations. The proposed classification scheme of dynamic risk measures VaR and CVaR estimating may be useful for risk managers of different financial institutions.
Highlights
Extreme price movements in the financial markets are rather rare but they have a great influence on the financial and political processes in the world
Asian markets Nikkey225 Stock Index – a composite index of the 225 largest companies publicly traded in Tokyo Stock Exchange, and the composite index, based on 300 stocks trading in the Shanghai stock exchange
We carry out a general analysis of the studied time series and the time series of variances
Summary
Extreme price movements in the financial markets are rather rare but they have a great influence on the financial and political processes in the world. Events such as the stock market crash on. The large number of methods, that are actively appearing, leads to the necessity to fulfill their systematization and classification using the methods of system analysis. Such approach simplifies the process of selecting the optimal way for solving the problem for risk management [12]
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