The assessment of the COVID-19 pandemic’s impact on the level of market risk in European companies on the basis of structural changes in the CAPM model

Piotr  Szczepocki; Ewa Feder-Sempach

doi:https://doi.org/10.59139/ws.2025.04.1

Piotr Szczepocki Uniwersytet Łódzki, Wydział Ekonomiczno-Socjologiczny, Instytut Statystyki i Demografii, Polska / University of Lodz, Faculty of Economics and Sociology, Institute of Statistics and Demography, Poland ORCID: https://orcid.org/0000-0001-8377-3831 , Ewa Feder-Sempach Uniwersytet Łódzki, Wydział Ekonomiczno-Socjologiczny, Instytut Ekonomii, Polska / University of Lodz, Faculty of Economics and Sociology, Institute of Economics, Poland ORCID: https://orcid.org/0000-0001-9586-1417 Wiadomości Statystyczne. The Polish Statistician, vol. 70, 2025, 4, s. 1-21 Opublikowano online: 30 kwietnia 2025 DOI https://doi.org/10.59139/ws.2025.04.1

10 Wyświetlenia 6 Pobrania

ARTYKUŁ

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STRESZCZENIE

The crisis caused by the COVID-19 pandemic had a considerable impact on financial markets. The main aim of the study presented in this paper is the assessment of the pandemic’s impact on the level of market risk in the STOXX Europe 600 index companies. The study sample consisted of 243 companies from different European countries and industries listed in euros. The data, for the years 2014–2023, came from the Refinitiv EIKON database. On the basis of the companies’ quotations before the pandemic and after its containment, structural changes in the Capital Asset Pricing Model (CAPM) were analysed. The CAPM model uses the beta coefficient to measure the average level of market (systematic) risk. The study uses the Andrews test to verify the structural changes in a specified period (here: throughout the COVID-19 pandemic).
The results showed structural changes caused by the COVID-19 pandemic in 56 companies, i.e. 23% of the research sample. Not all countries or industries were affected by the crisis. Large stock market capitalisation countries, like France, Germany, Belgium or Spain were impacted to a larger degree than smaller ones. The most changes were observed in the Real Estate sector, marked by the largest number of aggressive companies. The Consumer Non-Cyclical Industry, on the other hand, was the least affected sector. After the COVID-19 crisis, the average level of systematic risk measured by the beta coefficient increased in 38 companies and decreased in 18, which indicates a generally higher level of market risk.

SŁOWA KLUCZOWE

market risk CAPM, structural changes, COVID-19 pandemic, European companies

JEL

C10, C12, C22, C58, G10, G11, G15

BIBLIOGRAFIA

Alfaro, L., Chari, A., Greenland, A. N., & Schott, P. K. (2020). Aggregate and Firm-Level Stock Returns during Pandemics, in Real Time (NBER Working Papers No. 26950). https://www.nber.org/system/files/working_papers/w26950/w26950.pdf.

Andrews, D. W. K. (1989). Tests for Parameter Instability and Structural Change with Unknown Change Point (Cowles Foundation Discussion Paper No. 943). https://cowles.yale.edu/sites/default/files/2022-08/d0943.pdf.

Andrews, D. W. K. (1993). Tests for parameter instability and structural change with unknown change point. Econometrica, 61(4), 821–856. https://doi.org/10.2307/2951764.

Baek, S., Mohanty, S. K., & Glambosky, M. (2020). COVID-19 and stock market volatility:

An industry level analysis. Finance Research Letters, 37, 1–10. https://doi.org/10.1016/j.frl.2020.101748.

Baker, S. R., Bloom, N., Davis, S. J., Kost, K. J., Sammon, M. C., & Viratyosin, T. (2020). The Unprecedented Stock Market Impact of COVID-19 (NBER Working Paper No. 26945). https://doi.org/10.3386/w26945.

Bartram, S. M., & Yaw-Huei, W. (2015). European financial market dependence: An industryanalysis. Journal of Banking and Finance, 59, 146–163. https://doi.org/10.1016/j.jbankfin.2015.06.002.

Bénassy-Quéré, A., & Weder Di Mauro, B. (Eds.). (2020). Europe in the Time of Covid-19. CEPR Press. https://cepr.org/publications/books-and-reports/europe-time-covid-19.

Bey, R. P. (1983). Market Model Stationarity of Individual Public Utilities. Journal of Financial and Quantitative Analysis, 18(1), 67–85. https://doi.org/10.2307/2330805.

Bogołębska, J., Feder-Sempach, E., & Stawasz-Grabowska, E. (2024). Safe Assets in the Global Economy. Supply, Demand and Financial Stability. Routledge. https://doi.org/10.4324/9781003376538.

Brown, R. L., Durbin, J., & Evans, J. M. (1975). Techniques for Testing the Constancy of Regression Relationships over Time. Journal of the Royal Statistical Society. Series B: Statistical Methodology, 37(2), 149–163. https://doi.org/10.1111/j.2517-6161.1975.tb01532.x.

Bulut, E., Marangoz, C., & Daştan, M. (2023). Market Reactions to COVID-19: Does Systemic Risk Vary Across Industries? A Markov-Switching CAPM Approach. Eastern European Economics, 62(1), 69–88. https://doi.org/10.1080/00128775.2023.2173234.

Canegrati, E. (2008). Testing the CAPM: Evidence from Italian Equity Markets (MPRA Paper No. 10407). https://mpra.ub.uni-muenchen.de/10407/.

Chaveau, T., & Maillet, B. (1998). Flexible Least Squares Betas: The French Market Case (Papers 1998-03/fi).

Chen, J. M. (2021). The Capital Asset Pricing Model. Encyclopedia, 1(3), 915–933. https://doi.org/10.3390/encyclopedia1030070.

Choudhry, T., Lu, L., & Peng, K. (2010). Time-varying beta and the Asian financial crisis: Evidence from the Asian industrial sectors. Japan and the World Economy, 22(4), 228–234. https://doi.org/10.1016/j.japwor.2010.06.003.

Choudhry, T., & Wu, H. (2009). Forecasting the weekly time-varying beta of UK firms: GARCH models vs. Kalman filter method. The European Journal of Finance, 15(4), 437–444. https://doi.org/10.1080/13518470802604499.

Dang Ngoc, H., Vu Thi Thuy, V., & Le Van, C. (2021). Covid 19 pandemic and Abnormal Stock Returns of listed companies in Vietnam. Cogent Business and Management, 8(1), 1–18. https://doi.org/10.1080/23311975.2021.1941587.

Dempsey, M. (2013). The Capital Asset Pricing Model (CAPM): The History of a Failed Revolutionary Idea in Finance?. Abacus, 49(S1), 7–23. https://doi.org/10.1111/j.1467-6281.2012.00379.x.

Dębski, W., Feder-Sempach, E., & Szczepocki, P. (2021). Time-Varying Beta – The Case Study of the Largest Companies from the Polish, Czech, and Hungarian Stock Exchange. Emerging Markets Finance & Trade, 57(13), 3855–3877. https://doi.org/10.1080/1540496X.2020.1738188.

Dębski, W., Feder-Sempach, E., & Świderski, B. (2015). Are beta parameters stable on the Warsaw Stock Exchange?. Kwartalnik Kolegium Ekonomiczno-Społecznego. Studia i Prace, 3(3), 65–74. https://doi.org/10.33119/KKESSiP.2015.3.3.5.

Dębski, W., Feder-Sempach, E., & Świderski, B. (2016). Beta stability over bull and bear market on the Warsaw Stock Exchange. Folia Oeconomica Statinesia, 16(1), 75–92. https://doi.org/10.1515/foli-2016-0006.

Dębski, W., Feder-Sempach, E. M., & Wójcik, S. (2017). Stabilność parametru beta dla największych spółek z rynku polskiego, niemieckiego i francuskiego – analiza porównawcza. Annales Universitatis Mariae Curie-Skłodowska. Sectio H – Oeconomia, 51(5), 69–78. https://doi.org/10.17951/h.2017.51.5.69.

Di Liddo, F., Anelli, D., Morano, P., & Tajani, F. (2023). The Impacts of COVID-19 on Real Estate Market Dynamics: A Systematic Literature Review of Emerging Trends. Buildings, 13(9), 1–28. https://doi.org/10.3390/buildings13092334.

Ding, R., & Uryasev, S. (2022). Drawdown beta and portfolio optimization. Quantitative Finance, 22(7), 1265–1276. https://doi.org/10.1080/14697688.2022.2037698.

Fabozzi, F. J., & Francis, J. C. (1978). Betas as a Random Coefficient. Journal of Financial and Quantitative Analysis, 13(1), 101–116. https://doi.org/10.2307/2330525.

Feder-Sempach, E., & Szczepocki, P. (2022). The Bayesian Method in Estimating Polish and German Industry Betas. A Comparative Analysis of the Risk between the Main Economic Sectors from 2001–2020. Comparative Economic Research. Central and Eastern Europe, 25(2), 45–60. https://doi.org/10.18778/1508-2008.25.12.

Feder-Sempach, E., Szczepocki, P., & Dębski, W. (2023). What if beta is not stable? Applying the Kalman filter to risk estimates of top US companies over the long time horizon. Bank i Kredyt. Bank & Credit, 54(1), 25–44. https://doi.org/10.5604/01.3001.0054.5699.

Goodell, J. W. (2020). COVID-19 and finance: Agendas for future research. Finance Research Letters, 35, 1–5. https://doi.org/10.1016/j.frl.2020.101512.

Hansen, B. E. (n.d.). Gauss Programs.

Hansen, B. E. (1997). Approximate Asymptotic P Values for Structural-Change Tests. Journal of Business & Economic Statistics, 15(1), 60–67. https://doi.org/10.1080/07350015.1997.10524687.

Herrera, F. L., González Maiz Jiménez, J., & Reyes Santiago, A. (2022). Forecasting Performance of Different Betas: Mexican Stocks before and during the COVID-19 Pandemic. Emerging Markets Finance and Trade, 58(13), 3868–3880. https://doi.org/10.1080/1540496X.2022.2073813.

Jain, S. (2022). Betas in the time of corona: a conditional CAPM approach using multivariate GARCH model for India. Managerial Finance, 48(2), 243–257. https://doi.org/10.1108/MF-05-2021-0226.

Jostova, G., & Philipov, A. (2005). Bayesian analysis of stochastic betas. Journal of Financial and Quantitative Analysis, 40(4), 747–778. https://doi.org/10.1017/S0022109000001964.

Kayo, E. K., Martelanc, R., Brunaldi, E. O., & da Silva, W. E. (2020). Capital asset pricing model, beta stability, and the pricing puzzle of electricity transmission in Brazil. Energy Policy, 142. https://doi.org/10.1016/j.enpol.2020.111485.

Khan, M. N., Fifield, S. G. M., & Power, D. M. (2024). The impact of the COVID-19 pandemic on stock market volatility: evidence from a selection of developed and emerging stock markets. SN Business & Economics, 4, 1–26. https://doi.org/10.1007/s43546-024-00659-w.

Khan, M., Nawaz Kayani, U., Khan, M., Shahzad Mughal, K., & Haseeb, M. (2023). COVID-19 Pandemic & Financial Market Volatility; Evidence from GARCH Models. Journal of Risk and Financial Management, 16(1), 1–20. https://doi.org/10.3390/jrfm16010050.

Kwon, J. H. (2019). Tail risk and the consumption CAPM. Finance Research Letters, 30, 69–75. https://doi.org/10.1016/j.frl.2019.03.025.

Lintner, J. (1965). The Valuation of Risk Assets and the Selection of Risky Investments in Stock Portfolios and Capital Budgets. The Review of Economics and Statistics, 47(1), 13–37. https://doi.org/10.2307/1924119.

Lisicki, B. (2023). Wpływ pandemii COVID-19 na ryzyko rynkowe akcji mierzone współczynnikiem beta. Wiadomości Statystyczne. The Polish Statistician, 68(1), 1–22. https://doi.org/10.5604/01.3001.0016.2360.

Maji, K. (2010). Validity of Capital Asset Pricing Model & Stability of Systematic Risk (Beta): An Empirical Study on Indian Stock Market. https://doi.org/10.2139/ssrn.1708463.

Mazviona, B. W., & Elias, N. (2013). Stability of Beta Coefficients on the Zimbabwe Stock Exchange After Currency Reform: Chow Approach. International Journal of Business, Economics and Law, 3(1), 44–57.

Mergner, S., & Bulla, J. (2008). Time-varying beta risk of Pan-European industry portfolios: A comparison of alternative modeling techniques. The European Journal of Finance, 14(8), 771–802. https://doi.org/10.1080/13518470802173396.

Miziołek, T., Feder-Sempach, E., & Zaremba, A. (2020). International Equity Exchange-Traded Funds. Navigating Global ETF Market Opportunities and Risks. Palgrave Macmillan. https://doi.org/10.1007/978-3-030-53864-4.

Mossin, J. (1966). Equilibrium in a Capital Asset Market. Econometrica, 34(4), 768–783. https://doi.org/10.2307/1910098.

Onali, E. (2020). COVID-19 and stock market volatility. http://dx.doi.org/10.2139/ssrn.3571453.

Perold, A. F. (2004). The Capital Asset Pricing Model. Journal of Economic Perspectives, 18(3), 3–24. https://doi.org/10.1257/0895330042162340.

Rossi, M. (2016). The capital asset pricing model: a critical literature review. Global Business and Economics Review, 18(5), 604–617. https://dx.doi.org/10.1504/GBER.2016.078682.

Sansa, N. A. (2020). The Impact of the COVID-19 on the Financial Markets: Evidence from Chinaand USA. http://dx.doi.org/10.2139/ssrn.3562530.

Sharpe, W. (1964). Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk. Journal of Finance, 19(3), 425–442. https://doi.org/10.1111/j.1540-6261.1964.tb02865.x.

Slimane, I. B., Bellalah, M., & Rjiba, H. (2017). Time-varying beta during the 2008 financial crisis – evidence from North America and Western Europe. Journal of Risk Finance, 18(4), 398–431. https://doi.org/10.1108/JRF-02-2017-0020.

Topcu, M., & Serkan Gulal, O. (2020). The impact of COVID-19 on emerging stock markets. Finance Research Letters, 36, 1–4. https://doi.org/10.1016/j.frl.2020.101691.

Wells, C. (1994). Variable betas on the Stockholm exchange 1971–1989. Applied Financial Economics, 4(1), 75–92. https://doi.org/10.1080/758522128.

Xiao, C. (2022). An Empirical Test of CAPM Before and After the Pandemic Outbreak – The Case of American Stock Market. In: Proceedings of the 2022 7th International Conference on Financial Innovation and Economic Development (pp. 2449–2457). https://doi.org/10.2991/aebmr.k.220307.401.

Yan, B., Stuart, L., Tu, A., & Zhang, T. (2020). Analysis of the Effect of COVID-19 on the Stock Market and Potential Investing Strategies. https://doi.org/10.2139/ssrn.3563380.

Zeileis, A., Leisch, F., Hornik, K., & Kleiber, C. (2002). strucchange: An R Package for Testing for Structural Change in Linear Regression Models. Journal of Statistical Software, 7(2), 1–38. https://doi.org/10.18637/jss.v007.i02.

Zhang, D., Hu, M., & Ji, Q. (2020). Financial markets under the global pandemic of COVID-19. Finance Research Letters, 36, 1–6. https://doi.org/10.1016/j.frl.2020.101528.

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