Application of Copula Models in Stock Market Analysis
https://doi.org/10.37661/1816-0301-2024-21-2-24-35
Abstract
Objectives. The objective of the study is to use copula models to analyze shares of the Russian stock market and describe changes in the relationship between the shares before and during the coronavirus infection (COVID-19).
Methods. An algorithm for using copulas and functions of the R programming language in its implementation is presented. To model the dynamics of financial series the ARMA-GJR-GARCH process (autoregressive moving average Glosten-Jagannathan-Runkle model with generalized autoregressive conditional heteroskedasticity) is used. The selection of optimal families and parameters of copula models is carried out. The adequacy of the obtained models is checked and the results of the study of the relationship between the series are analyzed.
Results. An algorithm has been developed for a relatively new approach to using copulas in conjunction with the ARMA-GJR-GARCH model. The approach was used to study the impact of coronavirus in the context of the Russian economy. It is revealed that during the COVID-19 period the dependence between different stocks increases. It is shown that the effect of volatility in financial series increases after the outbreak of the pandemic.
Conclusion. The research algorithm using copula models in conjunction with the ARMA-GJR-GARCH process has shown its feasibility. This approach can be used with other GARCH-type models to study finance and other areas.
About the Authors
A. M. Kendys
Belarusian State University
Belarus
Belarus
Alexey M. Kendys, Student of the Faculty of Applied Mathematics and Computer Science
av. Nezavisimosti, 4, Minsk, 220030
M. M. Troush
Belarusian State University
Belarus
Belarus
Mikolai M. Troush, D. Sc. (Phys.-Math.), Prof.; Prof. at the Department of Probability Theory and Mathematical Statistics, Faculty of Applied Mathematics and Computer Science
av. Nezavisimosti, 4, Minsk, 220030
References
1. Cherubini U., Luciano E., Vecchiato W. Copula Methods in Finance. England, John Wiley & Sons, 2004, 293 p. https://doi.org/10.1002/9781118673331
2. Shchetinin E. Yu. On methods of quantitative analysis of the company’s financial indicators under conditions of high risk of investments. Upravlenie finansovy`mi riskami [Financial Risk Management], 2020, vol. 2, no. 2, pp. 108–119 (In Russ.). https://doi.org/10.36627/2221-7541-2020-2-2-108-119
3. Dewick P. R., Liu S. Copula modelling to analyse financial data. Journal of Risk and Financial Management, 2022, vol. 15, no. 3, p. 104. https://doi.org/10.3390/jrfm15030104
4. Ghaemi A. M., Tavakkoli H. R., Rashidi M. M. Sector-by-sector analysis of dependence dynamics between global large-cap companies and infectious diseases: A time-varying copula approach in EBOV and COVID-19 episodes. PLOS ONE, 2021, vol. 16, no. 11, p. e0259282. https://doi.org/10.1371/journal.pone.0259282
5. Benkraiem R., Garfatta R., Lakhal F., Zorgatid I. Financial contagion intensity during the COVID-19 outbreak: A copula approach. International Review of Financial Analysis, 2022, vol. 81, no. 7, p. 102136. https://doi.org/10.1016/j.irfa.2022.102136
6. Sahu P. K., Bal D. P., Kundu P. Gold price and exchange rate in pre and during Covid-19 period in India: Modelling dependence using copulas. Resources Policy, 2022, vol. 79, no. 4, p. 103126. https://doi.org/10.1016/j.resourpol.2022.103126
7. Golovanov O. A., Tyrsin A. N. Retrospective analysis of the impact of the COVID-19 pandemic on the socio-economic development of the region (on the example of the Sverdlovsk region). Prikladnaya matematika i voprosy` upravleniya [Applied Mathematics and Control Sciences], 2023, no. 1, pp. 61–71 (In Russ.). https://doi.org/10.15593/2499-9873/2023.1.04
8. Nelsen R. B. An Introduction to Copulas, 2nd edition. New York, Springer-Verlag, 2006, 272 p. https://doi.org/10.1007/0-387-28678-0
9. Francq C., Zakoian J. GARCH Models Structure, Statistical Inference and Financial Applications. England, John Wiley & Sons, 2010, 504 p. https://doi.org/10.1002/9780470670057
10. Hofert M., Kojadinovic I., Mächler M., Yan J. Elements of Copula Modeling with R. Switzerland, Springer, 2018, 267 p. https://doi.org/10.1007/978-3-319-89635-9
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For citations:
Kendys A.M., Troush M.M. Application of Copula Models in Stock Market Analysis. Informatics. 2024;21(2):24-35. (In Russ.) https://doi.org/10.37661/1816-0301-2024-21-2-24-35
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