IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v592y2022ics0378437121009778.html
   My bibliography  Save this article

A sentiment-based modeling and analysis of stock price during the COVID-19: U- and Swoosh-shaped recovery

Author

Listed:
  • Rai, Anish
  • Mahata, Ajit
  • Nurujjaman, Md
  • Majhi, Sushovan
  • Debnath, Kanish

Abstract

In the aftermath of stock market crash due to COVID-19, not all sectors recovered in the same way. Recently, a stock price model is proposed by Mahata et al. (2021) that describes V- and L-shaped recovery of the stocks and indices, but fails to simulate the U- and Swoosh-shaped recovery that arises due to sharp fall, continuation at the low price and followed by quick recovery, slow recovery for longer period, respectively. We propose a modified model by introducing a new parameter θ=+1,0,−1 to quantify investors’ positive, neutral and negative sentiments, respectively. The model explains movement of sectoral indices with positive financial anti-fragility (ϕ) showing U- and Swoosh-shaped recovery. Simulation using synthetic fund-flow with different shock lengths, ϕ, negative sentiment period and portion of fund-flow during recovery period show U- and Swoosh-shaped recovery. It shows that recovery of indices with positive ϕ becomes very weak with extended shock and negative sentiment period. Stocks with higher ϕ and fund-flow show quick recovery. Simulation of Nifty Bank, Nifty Financial and Nifty Realty show U-shaped recovery and Nifty IT shows Swoosh-shaped recovery. Simulation results are consistent with stock price movement. The estimated time-scale of shock and recovery of these indices are also consistent with the time duration of change of negative sentiment from the onset of COVID-19. We conclude that investors need to evaluate sentiment along with ϕ before investing in stock markets because negative sentiment can dampen the recovery even in financially anti-fragile stocks.

Suggested Citation

  • Rai, Anish & Mahata, Ajit & Nurujjaman, Md & Majhi, Sushovan & Debnath, Kanish, 2022. "A sentiment-based modeling and analysis of stock price during the COVID-19: U- and Swoosh-shaped recovery," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    • Handle: RePEc:eee:phsmap:v:592:y:2022:i:c:s0378437121009778
    DOI: 10.1016/j.physa.2021.126810
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437121009778
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2021.126810?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Numan Ülkü & Enzo Weber, 2014. "Identifying the Interaction between Foreign Investor Flows and Emerging Stock Market Returns," Review of Finance, European Finance Association, vol. 18(4), pages 1541-1581.
    2. Topcu, Mert & Gulal, Omer Serkan, 2020. "The impact of COVID-19 on emerging stock markets," Finance Research Letters, Elsevier, vol. 36(C).
    3. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    4. Cao, Charles & Chang, Eric C. & Wang, Ying, 2008. "An empirical analysis of the dynamic relationship between mutual fund flow and market return volatility," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2111-2123, October.
    5. Darren D. Lee & Robert W. Faff, 2009. "Corporate Sustainability Performance and Idiosyncratic Risk: A Global Perspective," The Financial Review, Eastern Finance Association, vol. 44(2), pages 213-237, May.
    6. Novy-Marx, Robert, 2013. "The other side of value: The gross profitability premium," Journal of Financial Economics, Elsevier, vol. 108(1), pages 1-28.
    7. Jayati Ghosh, 2020. "A critique of the Indian government’s response to the COVID-19 pandemic," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 47(3), pages 519-530, September.
    8. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    9. Alexakis, Christos & Eleftheriou, Konstantinos & Patsoulis, Patroklos, 2021. "COVID-19 containment measures and stock market returns: An international spatial econometrics investigation," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    10. Kling, Gerhard & Gao, Lei, 2008. "Chinese institutional investors' sentiment," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 18(4), pages 374-387, October.
    11. Jean-Philippe Bouchaud & Stefano Ciliberti & Augustin Landier & Guillaume Simon & David Thesmar, 2016. "The Excess Returns of "Quality" Stocks: A Behavioral Anomaly," Papers 1601.04478, arXiv.org.
    12. Marsh, Terry A & Merton, Robert C, 1986. "Dividend Variability and Variance Bounds Tests for the Rationality ofStock Market Prices," American Economic Review, American Economic Association, vol. 76(3), pages 483-498, June.
    13. Zhang, Dayong & Hu, Min & Ji, Qiang, 2020. "Financial markets under the global pandemic of COVID-19," Finance Research Letters, Elsevier, vol. 36(C).
    14. Norden E. Huang & Man‐Li Wu & Wendong Qu & Steven R. Long & Samuel S. P. Shen, 2003. "Applications of Hilbert–Huang transform to non‐stationary financial time series analysis," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 19(3), pages 245-268, July.
    15. Ashraf, Badar Nadeem, 2020. "Economic impact of government interventions during the COVID-19 pandemic: International evidence from financial markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
    16. Mantegna,Rosario N. & Stanley,H. Eugene, 2007. "Introduction to Econophysics," Cambridge Books, Cambridge University Press, number 9780521039871, October.
    17. Marsh, Terry A & Merton, Robert C, 1987. "Dividend Behavior for the Aggregate Stock Market," The Journal of Business, University of Chicago Press, vol. 60(1), pages 1-40, January.
    18. Mahata, Ajit & Rai, Anish & Nurujjaman, Md. & Prakash, Om, 2021. "Modeling and analysis of the effect of COVID-19 on the stock price: V and L-shape recovery," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    19. Charles, Amélie & Darné, Olivier, 2014. "Large shocks in the volatility of the Dow Jones Industrial Average index: 1928–2013," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 188-199.
    20. Tobin Hanspal & Annika Weber & Johannes Wohlfart, 2020. "Exposure to the COVID-19 Stock Market Crash and its Effect on Household Expectations," CEBI working paper series 20-13, University of Copenhagen. Department of Economics. The Center for Economic Behavior and Inequality (CEBI).
    21. Stefano Giglio & Matteo Maggiori & Johannes Stroebel & Stephen Utkus, 2021. "The joint dynamics of investor beliefs and trading during the COVID-19 crash," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 118(4), pages 2010316118-, January.
    22. Coval, Joshua & Stafford, Erik, 2007. "Asset fire sales (and purchases) in equity markets," Journal of Financial Economics, Elsevier, vol. 86(2), pages 479-512, November.
    23. Mazur, Mieszko & Dang, Man & Vega, Miguel, 2021. "COVID-19 and the march 2020 stock market crash. Evidence from S&P1500," Finance Research Letters, Elsevier, vol. 38(C).
    24. Narayan, Paresh Kumar & Phan, Dinh Hoang Bach & Liu, Guangqiang, 2021. "COVID-19 lockdowns, stimulus packages, travel bans, and stock returns," Finance Research Letters, Elsevier, vol. 38(C).
    25. Hanspal, Tobin & Weber, Annika & Wohlfart, Johannes, 2020. "Exposure to the COVID-19 stock market crash and its effect on household expectations," SAFE Working Paper Series 279, Leibniz Institute for Financial Research SAFE.
    26. Anish Rai & Ajit Mahata & Md Nurujjaman & Om Prakash, 2020. "Statistical properties of the aftershocks of stock market crashes revisited: Analysis based on the 1987 crash, financial-crisis-2008 and COVID-19 pandemic," Papers 2012.03012, arXiv.org, revised Sep 2021.
    27. Guo, Kun & Sun, Yi & Qian, Xin, 2017. "Can investor sentiment be used to predict the stock price? Dynamic analysis based on China stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 390-396.
    28. Mahata, Ajit & Bal, Debi Prasad & Nurujjaman, Md, 2020. "Identification of short-term and long-term time scales in stock markets and effect of structural break," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    29. Noelia Romero Castro & Juan Piñeiro Chousa, 2006. "An integrated framework for the financial analysis of sustainability," Business Strategy and the Environment, Wiley Blackwell, vol. 15(5), pages 322-333, September.
    30. Tobin Hanspal & Annika Weber & Johannes Wohlfart, 2020. "Exposure to the Covid-19 Stock Market Crash and its Effect on Household Expectations," CESifo Working Paper Series 8244, CESifo.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gao, Zhenbin & Zhang, Jie, 2023. "The fluctuation correlation between investor sentiment and stock index using VMD-LSTM: Evidence from China stock market," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mahata, Ajit & Rai, Anish & Nurujjaman, Md. & Prakash, Om, 2021. "Modeling and analysis of the effect of COVID-19 on the stock price: V and L-shape recovery," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    2. Heyden, Kim J. & Heyden, Thomas, 2021. "Market reactions to the arrival and containment of COVID-19: An event study," Finance Research Letters, Elsevier, vol. 38(C).
    3. Gregory, Richard Paul, 2022. "ESG scores and the response of the S&P 1500 to monetary and fiscal policy during the Covid-19 pandemic," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 446-456.
    4. Faik Bilgili & Emrah Koçak & Sevda Kuşkaya, 2023. "Dynamics and Co-movements Between the COVID-19 Outbreak and the Stock Market in Latin American Countries: An Evaluation Based on the Wavelet-Partial Wavelet Coherence Model," Evaluation Review, , vol. 47(4), pages 630-652, August.
    5. Sha, Yezhou & Zhang, Yong & Lu, Xiaomeng, 2022. "Household investment diversification amid Covid-19 pandemic: Evidence from Chinese investors," Finance Research Letters, Elsevier, vol. 47(PA).
    6. Boubaker, Sabri & Goodell, John W. & Kumar, Satish & Sureka, Riya, 2023. "COVID-19 and finance scholarship: A systematic and bibliometric analysis," International Review of Financial Analysis, Elsevier, vol. 85(C).
    7. Müller, Lara Marie & Harrs, Sören & Rockenbach, Bettina, 2022. "How Narratives Impact Financial Behavior - Experimental Evidence from the COVID-19 Pandemic," VfS Annual Conference 2022 (Basel): Big Data in Economics 264089, Verein für Socialpolitik / German Economic Association.
    8. Iyke, Bernard Njindan & Maheepala, M.M.J.D., 2022. "Conventional monetary policy, COVID-19, and stock markets in emerging economies," Pacific-Basin Finance Journal, Elsevier, vol. 76(C).
    9. Gu, Tiantian & Venkateswaran, Anand & Erath, Marc, 2023. "Impact of fiscal stimulus on volatility: A cross-country analysis," Research in International Business and Finance, Elsevier, vol. 65(C).
    10. Cakici, Nusret & Zaremba, Adam, 2021. "Who should be afraid of infections? Pandemic exposure and the cross-section of stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 72(C).
    11. Syed Abdul Rehman Khan & Danish Iqbal Godil & Munaza Bibi & Zhang Yu & Syed Muhammad Ahsan Rizvi, 2021. "The Economic and Social Impact of Teleworking in Romania: Present Practices and Post Pandemic Developments," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(58), pages 787-787, August.
    12. Ritika & Himanshu & Nawal Kishor, 2023. "Modeling of factors affecting investment behavior during the pandemic: a grey-DEMATEL approach," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 28(2), pages 222-235, June.
    13. Munusamy Dharani & M. Kabir Hassan & Makeen Huda & Mohammad Zoynul Abedin, 2023. "Covid-19 pandemic and stock returns in India," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 47(1), pages 251-266, March.
    14. Tihana Škrinjarić, 2021. "Profiting on the Stock Market in Pandemic Times: Study of COVID-19 Effects on CESEE Stock Markets," Mathematics, MDPI, vol. 9(17), pages 1-20, August.
    15. Ravi Kashyap, 2021. "Behavioral Bias Benefits: Beating Benchmarks By Bundling Bouncy Baskets," Papers 2109.03740, arXiv.org.
    16. Ravi Kashyap, 2021. "Behavioural Bias Benefits: Beating Benchmarks By Bundling Bouncy Baskets," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(3), pages 4885-4921, September.
    17. Doruk, Ömer Tuğsal & Konuk, Serhat & Atici, Rümeysa, 2021. "Short-term working allowance and firm risk in the post-COVID-19 period: Novel matching evidence from an emerging market," Finance Research Letters, Elsevier, vol. 43(C).
    18. Zhang, Zikai & Neupane, Suman, 2024. "Global IPO underpricing during the Covid-19 pandemic: The impact of firm fundamentals, financial intermediaries, and global factors," International Review of Financial Analysis, Elsevier, vol. 91(C).
    19. Ingar Haaland & Christopher Roth & Johannes Wohlfart, 2023. "Designing Information Provision Experiments," Journal of Economic Literature, American Economic Association, vol. 61(1), pages 3-40, March.
    20. Prelorentzos, Arsenios-Georgios N. & Konstantakis, Konstantinos N. & Michaelides, Panayotis G. & Xidonas, Panos & Goutte, Stephane & Thomakos, Dimitrios D., 2024. "Introducing the GVAR-GARCH model: Evidence from financial markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 91(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:592:y:2022:i:c:s0378437121009778. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.