IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2110.03986.html

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

Author

Listed:
  • Anish Rai
  • Ajit Mahata
  • Md. Nurujjaman
  • Sushovan Majhi
  • Kanish debnath

Abstract

Recently, a stock price model is proposed by A. Mahata et al. [Physica A, 574, 126008 (2021)] to understand the effect of COVID-19 on stock market. It 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 crisis and prolong drop followed by quick recovery (U-shaped) or slow recovery for longer period (Swoosh-shaped recovery). We propose a modified model by introducing a new variable $\theta$ that quantifies the sentiment of the investors. $\theta=+1,~0,~-1$ for positive, neutral and negative sentiment, respectively. The model explains the movement of sectoral indices with positive $\phi$ showing U- and Swoosh-shaped recovery. The simulation using synthetic fund-flow ($\Psi_{st}$) with different shock lengths ($T_S$), $\phi$, negative sentiment period ($T_N$) and portion of fund-flow ($\lambda$) during recovery period show U- and Swoosh-shaped recovery. The results show that the recovery of the indices with positive $\phi$ becomes very weak with the extended $T_S$ and $T_N$. The stocks with higher $\phi$ and $\lambda$ recover quickly. The simulation of the Nifty Bank, Nifty Financial and Nifty Realty show U-shaped recovery and Nifty IT shows Swoosh-shaped recovery. The simulation result is consistent with the real stock price movement. The time-scale ($\tau$) of the shock and recovery of these indices during the COVID-19 are consistent with the time duration of the change of negative sentiment from the onset of the COVID-19. This study may help the investors to plan their investment during different crises.

Suggested Citation

  • Anish Rai & Ajit Mahata & Md. Nurujjaman & Sushovan Majhi & Kanish debnath, 2021. "A sentiment-based modeling and analysis of stock price during the COVID-19: U- and Swoosh-shaped recovery," Papers 2110.03986, arXiv.org.
  • Handle: RePEc:arx:papers:2110.03986
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2110.03986
    File Function: Latest version
    Download Restriction: no
    ---><---

    Other versions of this item:

    Citations

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


    Cited by:

    1. is not listed on IDEAS
    2. Kundan Mukhia & Anish Rai & SR Luwang & Md Nurujjaman & Sushovan Majhi & Chittaranjan Hens, 2024. "Complex network analysis of cryptocurrency market during crashes," Papers 2405.05642, arXiv.org.
    3. Mukhia, Kundan & Rai, Anish & Luwang, S.R. & Nurujjaman, Md & Majhi, Sushovan & Hens, Chittaranjan, 2024. "Complex network analysis of cryptocurrency market during crashes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 653(C).
    4. 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).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:arx:papers:2110.03986. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.