IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v17y2024i11p502-d1516484.html
   My bibliography  Save this article

Twitter Economic Uncertainty and Herding Behavior in ESG Markets

Author

Listed:
  • Dimitrios Koutmos

    (Department of Accounting, Finance, and Business Law, College of Business, Texas A&M University—Corpus Christi, Corpus Christi, TX 78412, USA
    Finance Area, Academic Alliance, Texas A&M University System—RELLIS Technology & Innovation Campus, College Station, TX 77843, USA)

Abstract

Attention to environmental, social, and governance (ESG) investing has grown in recent years. Even after the SARS-CoV-2 (COVID-19) global pandemic, there has been a rise in financial instruments that are structured according to certain prescribed “sustainable finance” objectives. From a risk management perspective, and as we continue to see a rise in inflows into such instruments, it is important to appreciate that ESG markets will have a growing influence on our financial system and its development. In light of this, and using a sample of some of the most common and popular US-based ESG index funds, this study explores the extent to which herding behaviors are present in such markets. From a regulatory point of view, such behaviors are important to identify, given that they can lead to excess price volatility, bubbles, and other such market-destabilizing phenomena. In addition, this study builds a framework for exploring whether Twitter-based economic uncertainty, which is arguably a forward-looking indicator of investors’ expectations, can exacerbate herding behaviors in ESG markets. Overall, this study shows the following: (i) herding behaviors are present in ESG markets; (ii) rises in Twitter economic uncertainty can potentially exacerbate such herding; (iii) although ESG funds, like traditional asset classes, generally show a negative risk–return tradeoff, this can be driven by changes in Twitter economic uncertainty.

Suggested Citation

  • Dimitrios Koutmos, 2024. "Twitter Economic Uncertainty and Herding Behavior in ESG Markets," JRFM, MDPI, vol. 17(11), pages 1-19, November.
  • Handle: RePEc:gam:jjrfmx:v:17:y:2024:i:11:p:502-:d:1516484
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/17/11/502/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1911-8074/17/11/502/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Konstantinos Bozos & Timothy King & Dimitrios Koutmos, 2022. "CSR and Firm Risk: Is Shareholder Activism a Double-Edged Sword?," JRFM, MDPI, vol. 15(11), pages 1-22, November.
    2. Cerqueti, Roy & Ciciretti, Rocco & Dalò, Ambrogio & Nicolosi, Marco, 2021. "ESG investing: A chance to reduce systemic risk," Journal of Financial Stability, Elsevier, vol. 54(C).
    3. Bollerslev, Tim & Chou, Ray Y. & Kroner, Kenneth F., 1992. "ARCH modeling in finance : A review of the theory and empirical evidence," Journal of Econometrics, Elsevier, vol. 52(1-2), pages 5-59.
    4. Abdul Waheed & Qingyu Zhang, 2022. "Effect of CSR and Ethical Practices on Sustainable Competitive Performance: A Case of Emerging Markets from Stakeholder Theory Perspective," Journal of Business Ethics, Springer, vol. 175(4), pages 837-855, February.
    5. French, Kenneth R. & Schwert, G. William & Stambaugh, Robert F., 1987. "Expected stock returns and volatility," Journal of Financial Economics, Elsevier, vol. 19(1), pages 3-29, September.
    6. Emil Andersson & Mahim Hoque & Md Lutfur Rahman & Gazi Salah Uddin & Ranadeva Jayasekera, 2022. "ESG investment: What do we learn from its interaction with stock, currency and commodity markets?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3623-3639, July.
    7. Barroso, Pedro & Maio, Paulo, 2024. "The risk–return tradeoff among equity factors," Journal of Empirical Finance, Elsevier, vol. 78(C).
    Full references (including those not matched with items on IDEAS)

    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. Alagidede, Paul & Panagiotidis, Theodore, 2009. "Modelling stock returns in Africa's emerging equity markets," International Review of Financial Analysis, Elsevier, vol. 18(1-2), pages 1-11, March.
    2. Sabur Mollah & Asma Mobarek, 2009. "Market volatility across countries – evidence from international markets," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 26(4), pages 257-274, October.
    3. Chiang, Thomas C., 2019. "Empirical analysis of intertemporal relations between downside risks and expected returns—Evidence from Asian markets," Research in International Business and Finance, Elsevier, vol. 47(C), pages 264-278.
    4. Dongweí Su, 2003. "Risk, Return and Regulation in Chinese Stock Markets," World Scientific Book Chapters, in: Chinese Stock Markets A Research Handbook, chapter 3, pages 75-122, World Scientific Publishing Co. Pte. Ltd..
    5. Frank J. Fabozzi & Radu Tunaru & Tony Wu, 2004. "Modeling Volatility for the Chinese Equity Markets," Annals of Economics and Finance, Society for AEF, vol. 5(1), pages 79-92, May.
    6. Siem Jan Koopman & Eugenie Hol Uspensky, 2002. "The stochastic volatility in mean model: empirical evidence from international stock markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(6), pages 667-689.
    7. LINTON, Olivier & PERRON, Benoît, 1999. "The Shape of the Risk Premium: Evidence from a Semiparametric Garch Model," Cahiers de recherche 9911, Universite de Montreal, Departement de sciences economiques.
    8. David McMillan & Alan Speight, 2006. "Heterogeneous information flows and intra-day volatility dynamics: evidence from the UK FTSE-100 stock index futures market," Applied Financial Economics, Taylor & Francis Journals, vol. 16(13), pages 959-972.
    9. Manabu Asai & Michael McAleer, 2011. "Alternative Asymmetric Stochastic Volatility Models," Econometric Reviews, Taylor & Francis Journals, vol. 30(5), pages 548-564, October.
    10. Kiymaz, Halil & Berument, Hakan, 2003. "The day of the week effect on stock market volatility and volume: International evidence," Review of Financial Economics, Elsevier, vol. 12(4), pages 363-380.
    11. Deniz Erdemlioglu & Sébastien Laurent & Christopher J. Neely, 2013. "Econometric modeling of exchange rate volatility and jumps," Chapters, in: Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), Handbook of Research Methods and Applications in Empirical Finance, chapter 16, pages 373-427, Edward Elgar Publishing.
    12. Balaban, Ercan & Ozgen, Tolga, 2016. "Trading session effects on stock returns and their conditional volatility: Firm-level evidence from a European Union accession country," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 446(C), pages 264-271.
    13. Madhusudan Karmakar, 2007. "Asymmetric Volatility and Risk-return Relationship in the Indian Stock Market," South Asia Economic Journal, Institute of Policy Studies of Sri Lanka, vol. 8(1), pages 99-116, January.
    14. Omar Euch & Masaaki Fukasawa & Mathieu Rosenbaum, 2018. "The microstructural foundations of leverage effect and rough volatility," Finance and Stochastics, Springer, vol. 22(2), pages 241-280, April.
    15. Xiaoquan Jiang & Bong‐Soo Lee, 2006. "The Dynamic Relation Between Returns and Idiosyncratic Volatility," Financial Management, Financial Management Association International, vol. 35(2), pages 43-65, June.
    16. Kai-Li Wang & Christopher Fawson & Christopher B. Barrett & James B. McDonald, 2001. "A flexible parametric GARCH model with an application to exchange rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(4), pages 521-536.
    17. Kim, Sang W. & Rogers, John H., 1995. "International stock price spillovers and market liberalization: Evidence from Korea, Japan, and the United States," Journal of Empirical Finance, Elsevier, vol. 2(2), pages 117-133, June.
    18. Elyasiani, Elyas & Mansur, Iqbal, 1998. "Sensitivity of the bank stock returns distribution to changes in the level and volatility of interest rate: A GARCH-M model," Journal of Banking & Finance, Elsevier, vol. 22(5), pages 535-563, May.
    19. Chan-Lau, Jorge A. & Ivaschenko, Iryna, 2003. "Asian Flu or Wall Street virus? Tech and non-tech spillovers in the United States and Asia," Journal of Multinational Financial Management, Elsevier, vol. 13(4-5), pages 303-322, December.
    20. Peter F. Christoffersen & Francis X. Diebold, 2006. "Financial Asset Returns, Direction-of-Change Forecasting, and Volatility Dynamics," Management Science, INFORMS, vol. 52(8), pages 1273-1287, August.

    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:gam:jjrfmx:v:17:y:2024:i:11:p:502-:d:1516484. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.