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Regression Approach for Modeling COVID-19 Spread and its Impact On Stock Market

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  • Bohdan M. Pavlyshenko

Abstract

The paper studies different regression approaches for modeling COVID-19 spread and its impact on the stock market. The logistic curve model was used with Bayesian regression for predictive analytics of the coronavirus spread. The impact of COVID-19 was studied using regression approach and compared to other crises influence. In practical analytics, it is important to find the maximum of coronavirus cases per day, this point means the estimated half time of coronavirus spread in the region under investigation. The obtained results show that different crises with different reasons have different impact on the same stocks. It is important to analyze their impact separately. Bayesian inference makes it possible to analyze the uncertainty of crisis impacts.

Suggested Citation

  • Bohdan M. Pavlyshenko, 2020. "Regression Approach for Modeling COVID-19 Spread and its Impact On Stock Market," Papers 2004.01489, arXiv.org.
    • Handle: RePEc:arx:papers:2004.01489
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    File URL: http://arxiv.org/pdf/2004.01489
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    1. Carpenter, Bob & Gelman, Andrew & Hoffman, Matthew D. & Lee, Daniel & Goodrich, Ben & Betancourt, Michael & Brubaker, Marcus & Guo, Jiqiang & Li, Peter & Riddell, Allen, 2017. "Stan: A Probabilistic Programming Language," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 76(i01).
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    Cited by:

    1. Ayoub Ammy-Driss & Matthieu Garcin, 2021. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Working Papers hal-02903655, HAL.
    2. Ștefan Cristian Gherghina & Daniel Ștefan Armeanu & Camelia Cătălina Joldeș, 2020. "Stock Market Reactions to COVID-19 Pandemic Outbreak: Quantitative Evidence from ARDL Bounds Tests and Granger Causality Analysis," IJERPH, MDPI, vol. 17(18), pages 1-35, September.
    3. Salisu, Afees A. & Shaik, Muneer, 2022. "Islamic Stock indices and COVID-19 pandemic," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 282-293.
    4. Ammy-Driss, Ayoub & Garcin, Matthieu, 2023. "Efficiency of the financial markets during the COVID-19 crisis: Time-varying parameters of fractional stable dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    5. Ayoub Ammy-Driss & Matthieu Garcin, 2020. "Efficiency of the financial markets during the COVID-19 crisis: time-varying parameters of fractional stable dynamics," Papers 2007.10727, arXiv.org, revised Nov 2021.
    6. Deimante Teresiene & Greta Keliuotyte-Staniuleniene & Yiyi Liao & Rasa Kanapickiene & Ruihui Pu & Siyan Hu & Xiao-Guang Yue, 2021. "The Impact of the COVID-19 Pandemic on Consumer and Business Confidence Indicators," JRFM, MDPI, vol. 14(4), pages 1-23, April.
    7. Matthieu Garcin & Jules Klein & Sana Laaribi, 2020. "Estimation of time-varying kernel densities and chronology of the impact of COVID-19 on financial markets," Papers 2007.09043, arXiv.org, revised Mar 2022.
    8. Matthieu Garcin & Jules Klein & Sana Laaribi, 2022. "Estimation of time-varying kernel densities and chronology of the impact of COVID-19 on financial markets," Working Papers hal-02901988, HAL.
    9. Cătălina Camelia Joldeș, 2020. "Impact of COVID-19 on the Romanian capital market: An assessment of BET index and shares BRD, SNP, TLV, FP & SNP," Journal of Financial Studies, Institute of Financial Studies, vol. 9(5), pages 101-123, November.
    10. Han-Sol Lee & Ekaterina A. Degtereva & Alexander M. Zobov, 2021. "The Impact of the COVID-19 Pandemic on Cross-Border Mergers and Acquisitions’ Determinants: New Empirical Evidence from Quasi-Poisson and Negative Binomial Regression Models," Economies, MDPI, vol. 9(4), pages 1-13, November.
    11. Maaz Khan & Umar Nawaz Kayani & Mrestyal Khan & Khurrum Shahzad Mughal & Mohammad Haseeb, 2023. "COVID-19 Pandemic & Financial Market Volatility; Evidence from GARCH Models," JRFM, MDPI, vol. 16(1), pages 1-20, January.
    12. Bharat Kumar Meher & Iqbal Thonse Hawaldar & Mathew Thomas Gil & Deebom Zorle Dum, 2021. "Measuring Leverage Effect of Covid 19 on Stock Price Volatility of Energy Companies Using High Frequency Data," International Journal of Energy Economics and Policy, Econjournals, vol. 11(6), pages 489-502.

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