IDEAS home Printed from https://ideas.repec.org/a/eee/reveco/v74y2021icp103-115.html
   My bibliography  Save this article

Information dissemination across global markets during the spread of COVID-19 pandemic

Author

Listed:
  • Tripathi, Abhinava
  • Pandey, Ashish

Abstract

This study examines the information dissemination process across 25 major global market indices during the times of COVID-19 pandemic spread. The results suggest that the information from non-systematic sources contributed to the price decline and increased volatility. In contrast, the systematic information lowered the volatility and facilitated the recovery process towards more stable markets. These results have important implications for policymakers and regulators in the development of efficient markets.

Suggested Citation

  • Tripathi, Abhinava & Pandey, Ashish, 2021. "Information dissemination across global markets during the spread of COVID-19 pandemic," International Review of Economics & Finance, Elsevier, vol. 74(C), pages 103-115.
  • Handle: RePEc:eee:reveco:v:74:y:2021:i:c:p:103-115
    DOI: 10.1016/j.iref.2021.02.004
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1059056021000290
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.iref.2021.02.004?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Stambaugh, Robert F. & Yu, Jianfeng & Yuan, Yu, 2014. "The long of it: Odds that investor sentiment spuriously predicts anomaly returns," Journal of Financial Economics, Elsevier, vol. 114(3), pages 613-619.
    2. Antoniou, Constantinos & Doukas, John A. & Subrahmanyam, Avanidhar, 2013. "Cognitive Dissonance, Sentiment, and Momentum," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(1), pages 245-275, February.
    3. Joon Chae, 2005. "Trading Volume, Information Asymmetry, and Timing Information," Journal of Finance, American Finance Association, vol. 60(1), pages 413-442, February.
    4. Stiglitz, Joseph E, 1989. "Financial Markets and Development," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 5(4), pages 55-68, Winter.
    5. Chinn, Menzie D. & Ito, Hiro, 2006. "What matters for financial development? Capital controls, institutions, and interactions," Journal of Development Economics, Elsevier, vol. 81(1), pages 163-192, October.
    6. Aloui, Riadh & Aïssa, Mohamed Safouane Ben & Nguyen, Duc Khuong, 2011. "Global financial crisis, extreme interdependences, and contagion effects: The role of economic structure?," Journal of Banking & Finance, Elsevier, vol. 35(1), pages 130-141, January.
    7. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    8. 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.
    9. Mougoué, Mbodja & Aggarwal, Raj, 2011. "Trading volume and exchange rate volatility: Evidence for the sequential arrival of information hypothesis," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2690-2703, October.
    10. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    11. Kent Daniel & David Hirshleifer & Avanidhar Subrahmanyam, 1998. "Investor Psychology and Security Market Under- and Overreactions," Journal of Finance, American Finance Association, vol. 53(6), pages 1839-1885, December.
    12. Greenwood, Jeremy & Smith, Bruce D., 1997. "Financial markets in development, and the development of financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 21(1), pages 145-181, January.
    13. Vozlyublennaia, Nadia, 2014. "Investor attention, index performance, and return predictability," Journal of Banking & Finance, Elsevier, vol. 41(C), pages 17-35.
    14. Joseph E. Stiglitz, 1989. "Markets and Development," NBER Working Papers 2961, National Bureau of Economic Research, Inc.
    15. Campello, Murillo & Graham, John R. & Harvey, Campbell R., 2010. "The real effects of financial constraints: Evidence from a financial crisis," Journal of Financial Economics, Elsevier, vol. 97(3), pages 470-487, September.
    16. Merton, Robert C, 1987. "A Simple Model of Capital Market Equilibrium with Incomplete Information," Journal of Finance, American Finance Association, vol. 42(3), pages 483-510, July.
    17. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    18. Matthias Bank & Martin Larch & Georg Peter, 2011. "Google search volume and its influence on liquidity and returns of German stocks," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 25(3), pages 239-264, September.
    19. Jiao, Peiran & Veiga, André & Walther, Ansgar, 2020. "Social media, news media and the stock market," Journal of Economic Behavior & Organization, Elsevier, vol. 176(C), pages 63-90.
    20. De Bondt, Werner F M & Thaler, Richard, 1985. "Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July.
    21. Steven L. Scott & Hal R. Varian, 2015. "Bayesian Variable Selection for Nowcasting Economic Time Series," NBER Chapters, in: Economic Analysis of the Digital Economy, pages 119-135, National Bureau of Economic Research, Inc.
    22. Takeda, Fumiko & Wakao, Takumi, 2014. "Google search intensity and its relationship with returns and trading volume of Japanese stocks," Pacific-Basin Finance Journal, Elsevier, vol. 27(C), pages 1-18.
    23. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    24. John B. Taylor, 2009. "The Financial Crisis and the Policy Responses: An Empirical Analysis of What Went Wrong," NBER Working Papers 14631, National Bureau of Economic Research, Inc.
    25. Stambaugh, Robert F. & Yu, Jianfeng & Yuan, Yu, 2012. "The short of it: Investor sentiment and anomalies," Journal of Financial Economics, Elsevier, vol. 104(2), pages 288-302.
    26. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    27. Ding, Rong & Hou, Wenxuan, 2015. "Retail investor attention and stock liquidity," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 37(C), pages 12-26.
    28. Joseph, Kissan & Babajide Wintoki, M. & Zhang, Zelin, 2011. "Forecasting abnormal stock returns and trading volume using investor sentiment: Evidence from online search," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1116-1127, October.
    29. Durbin, James & Koopman, Siem Jan, 2012. "Time Series Analysis by State Space Methods," OUP Catalogue, Oxford University Press, edition 2, number 9780199641178.
    30. Calice, Giovanni & Chen, Jing & Williams, Julian, 2013. "Liquidity spillovers in sovereign bond and CDS markets: An analysis of the Eurozone sovereign debt crisis," Journal of Economic Behavior & Organization, Elsevier, vol. 85(C), pages 122-143.
    31. Fama, Eugene F., 1998. "Market efficiency, long-term returns, and behavioral finance," Journal of Financial Economics, Elsevier, vol. 49(3), pages 283-306, September.
    32. Aouadi, Amal & Arouri, Mohamed & Teulon, Frédéric, 2013. "Investor attention and stock market activity: Evidence from France," Economic Modelling, Elsevier, vol. 35(C), pages 674-681.
    33. Jeff Fleming & Chris Kirby & Barbara Ostdiek, 2006. "Stochastic Volatility, Trading Volume, and the Daily Flow of Information," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1551-1590, May.
    34. Epps, Thomas W & Epps, Mary Lee, 1976. "The Stochastic Dependence of Security Price Changes and Transaction Volumes: Implications for the Mixture-of-Distributions Hypothesis," Econometrica, Econometric Society, vol. 44(2), pages 305-321, March.
    35. Zhi Da & Joseph Engelberg & Pengjie Gao, 2011. "In Search of Attention," Journal of Finance, American Finance Association, vol. 66(5), pages 1461-1499, October.
    36. Brad M. Barber & Terrance Odean, 2000. "Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors," Journal of Finance, American Finance Association, vol. 55(2), pages 773-806, April.
    37. Chordia, Tarun & Subrahmanyam, Avanidhar, 2004. "Order imbalance and individual stock returns: Theory and evidence," Journal of Financial Economics, Elsevier, vol. 72(3), pages 485-518, June.
    38. Chordia, Tarun & Roll, Richard & Subrahmanyam, Avanidhar, 2008. "Liquidity and market efficiency," Journal of Financial Economics, Elsevier, vol. 87(2), pages 249-268, February.
    39. Harrison Hong & Jeremy C. Stein, 1999. "A Unified Theory of Underreaction, Momentum Trading, and Overreaction in Asset Markets," Journal of Finance, American Finance Association, vol. 54(6), pages 2143-2184, December.
    40. Hasbrouck, Joel, 1988. "Trades, quotes, inventories, and information," Journal of Financial Economics, Elsevier, vol. 22(2), pages 229-252, December.
    41. Smith, Geoffrey Peter, 2012. "Google Internet search activity and volatility prediction in the market for foreign currency," Finance Research Letters, Elsevier, vol. 9(2), pages 103-110.
    42. Figlewski, Stephen, 1981. "The Informational Effects of Restrictions on Short Sales: Some Empirical Evidence," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 16(4), pages 463-476, November.
    43. Figlewski, Stephen C, 1978. "Market "Efficiency" in a Market with Heterogeneous Information," Journal of Political Economy, University of Chicago Press, vol. 86(4), pages 581-597, August.
    44. Ihsan Ullah Badshah, 2013. "Quantile Regression Analysis of the Asymmetric Return‐Volatility Relation," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 33(3), pages 235-265, March.
    45. Brutti, Filippo, 2011. "Sovereign defaults and liquidity crises," Journal of International Economics, Elsevier, vol. 84(1), pages 65-72, May.
    46. Brown, Gregory W. & Cliff, Michael T., 2004. "Investor sentiment and the near-term stock market," Journal of Empirical Finance, Elsevier, vol. 11(1), pages 1-27, January.
    47. Tantaopas, Parkpoom & Padungsaksawasdi, Chaiyuth & Treepongkaruna, Sirimon, 2016. "Attention effect via internet search intensity in Asia-Pacific stock markets," Pacific-Basin Finance Journal, Elsevier, vol. 38(C), pages 107-124.
    48. Vlastakis, Nikolaos & Markellos, Raphael N., 2012. "Information demand and stock market volatility," Journal of Banking & Finance, Elsevier, vol. 36(6), pages 1808-1821.
    49. Brenner, Menachem & Pasquariello, Paolo & Subrahmanyam, Marti, 2009. "On the Volatility and Comovement of U.S. Financial Markets around Macroeconomic News Announcements," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(6), pages 1265-1289, December.
    50. Harris, Lawrence, 1987. "Transaction Data Tests of the Mixture of Distributions Hypothesis," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 22(2), pages 127-141, June.
    51. Andersen, Torben G, 1996. "Return Volatility and Trading Volume: An Information Flow Interpretation of Stochastic Volatility," Journal of Finance, American Finance Association, vol. 51(1), pages 169-204, March.
    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. Song, Ziyu & Gong, Xiaomin & Zhang, Cheng & Yu, Changrui, 2023. "Investor sentiment based on scaled PCA method: A powerful predictor of realized volatility in the Chinese stock market," International Review of Economics & Finance, Elsevier, vol. 83(C), pages 528-545.
    2. Dash, Saumya Ranjan & Maitra, Debasish, 2022. "The COVID-19 pandemic uncertainty, investor sentiment, and global equity markets: Evidence from the time-frequency co-movements," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    3. Hsu, Yu-Lin & Tang, Leilei, 2022. "Effects of investor sentiment and country governance on unexpected conditional volatility during the COVID-19 pandemic: Evidence from global stock markets," International Review of Financial Analysis, Elsevier, vol. 82(C).
    4. Bakry, Walid & Kavalmthara, Peter John & Saverimuttu, Vivienne & Liu, Yiyang & Cyril, Sajan, 2022. "Response of stock market volatility to COVID-19 announcements and stringency measures: A comparison of developed and emerging markets," Finance Research Letters, Elsevier, vol. 46(PA).
    5. Carausu Dumitru-Nicusor & Lupu Dan, 2022. "COVID-19 and stock markets comovement in emerging Europe," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 16(1), pages 660-669, August.
    6. Okorie, David Iheke & Lin, Boqiang, 2023. "Cryptocurrency spectrum and 2020 pandemic: Contagion analysis," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 29-38.

    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. Cheng, Feiyang & Chiao, Chaoshin & Wang, Chunfeng & Fang, Zhenming & Yao, Shouyu, 2021. "Does retail investor attention improve stock liquidity? A dynamic perspective," Economic Modelling, Elsevier, vol. 94(C), pages 170-183.
    2. Keunbae Ahn, 2021. "Predictable Fluctuations in the Cross-Section and Time-Series of Asset Prices," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2021.
    3. Tihana Škrinjarić, 2019. "Time Varying Spillovers between the Online Search Volume and Stock Returns: Case of CESEE Markets," IJFS, MDPI, vol. 7(4), pages 1-30, October.
    4. Sifat, Imtiaz Mohammad & Thaker, Hassanudin Mohd Thas, 2020. "Predictive power of web search behavior in five ASEAN stock markets," Research in International Business and Finance, Elsevier, vol. 52(C).
    5. Christophe Desagre & Catherine D'Hondt, 2020. "Googlization and retail investors' trading activity," LIDAM Discussion Papers LFIN 2020004, Université catholique de Louvain, Louvain Finance (LFIN).
    6. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, September.
    7. Prajwal Eachempati & Praveen Ranjan Srivastava, 2021. "Accounting for unadjusted news sentiment for asset pricing," Qualitative Research in Financial Markets, Emerald Group Publishing Limited, vol. 13(3), pages 383-422, May.
    8. Agarwal, Shweta & Kumar, Shailendra & Goel, Utkarsh, 2019. "Stock market response to information diffusion through internet sources: A literature review," International Journal of Information Management, Elsevier, vol. 45(C), pages 118-131.
    9. Abhinava Tripathi, 2021. "The Arrival of Information and Price Adjustment Across Extreme Quantiles: Global Evidence," IIM Kozhikode Society & Management Review, , vol. 10(1), pages 7-19, January.
    10. Hervé, Fabrice & Zouaoui, Mohamed & Belvaux, Bertrand, 2019. "Noise traders and smart money: Evidence from online searches," Economic Modelling, Elsevier, vol. 83(C), pages 141-149.
    11. Chaiyuth Padungsaksawasdi & Sirimon Treepongkaruna & Robert Brooks, 2019. "Investor Attention and Stock Market Activities: New Evidence from Panel Data," IJFS, MDPI, vol. 7(2), pages 1-19, June.
    12. Chen, Zhongdong & Craig, Karen Ann, 2023. "Active attention, retail investor base, and stock returns," Journal of Behavioral and Experimental Finance, Elsevier, vol. 39(C).
    13. Gang Chu & John W. Goodell & Dehua Shen & Yongjie Zhang, 2022. "Machine learning to establish proxies for investor attention: evidence of improved stock-return prediction," Annals of Operations Research, Springer, vol. 318(1), pages 103-128, November.
    14. Szymon Lis, 2022. "Investor Sentiment in Asset Pricing Models: A Review," Working Papers 2022-14, Faculty of Economic Sciences, University of Warsaw.
    15. Nguyen, Cuong & Hoang, Lai & Shim, Jungwook & Truong, Phuong, 2020. "Internet search intensity, liquidity and returns in emerging markets," Research in International Business and Finance, Elsevier, vol. 52(C).
    16. Cheng, Feiyang & Wang, Chunfeng & Chiao, Chaoshin & Yao, Shouyu & Fang, Zhenming, 2021. "Retail attention, retail trades, and stock price crash risk," Emerging Markets Review, Elsevier, vol. 49(C).
    17. Desagre, Christophe & D’Hondt, Catherine, 2021. "Googlization and retail trading activity," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    18. Ung, Sze Nie & Gebka, Bartosz & Anderson, Robert D.J., 2023. "Is sentiment the solution to the risk–return puzzle? A (cautionary) note," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    19. Yamani, Ehab, 2023. "Return–volume nexus in financial markets: A survey of research," Research in International Business and Finance, Elsevier, vol. 65(C).
    20. Smales, L.A., 2021. "Investor attention and global market returns during the COVID-19 crisis," International Review of Financial Analysis, Elsevier, vol. 73(C).

    More about this item

    Keywords

    Market efficiency; COVID-19; Coronavirus; Financial markets; Informational efficiency;
    All these keywords.

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

    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:eee:reveco:v:74:y:2021:i:c:p:103-115. 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.elsevier.com/locate/inca/620165 .

    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.