IDEAS home Printed from https://ideas.repec.org/a/ebl/ecbull/eb-22-00414.html
   My bibliography  Save this article

Twitter sentiment and stock return volatility of US travel and leisure firms

Author

Listed:
  • Syed jawad hussain Shahzad

    (Montpellier Business School)

  • Elie Bouri

    (School of Business, Lebanese American University, Lebanon)

  • Román Ferrer

    (Department of Financial and Actuarial Economics, University of Valencia, Spain)

Abstract

This paper examines the impact of firm-specific sentiment extracted from Twitter messages on the stock return volatility of US Travel & Leisure stocks. To this end, linear and nonlinear impulse response functions are estimated based on local projection techniques. We find that the return volatility of US Travel & Leisure firms increases in response to twitter messages in the short-term, particularly during periods of high uncertainty. Positive tweets have a stronger effect on stock return volatility than negative tweets, reflecting that positive Twitter sentiment has a clear incentive effect on retail investors in the US Travel & Leisure industry.

Suggested Citation

  • Syed jawad hussain Shahzad & Elie Bouri & Román Ferrer, 2023. "Twitter sentiment and stock return volatility of US travel and leisure firms," Economics Bulletin, AccessEcon, vol. 43(2), pages 1133-1142.
    • Handle: RePEc:ebl:ecbull:eb-22-00414
    as

    Download full text from publisher

    File URL: http://www.accessecon.com/Pubs/EB/2023/Volume43/EB-23-V43-I2-P94.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Parkinson, Michael, 1980. "The Extreme Value Method for Estimating the Variance of the Rate of Return," The Journal of Business, University of Chicago Press, vol. 53(1), pages 61-65, January.
    2. Garman, Mark B & Klass, Michael J, 1980. "On the Estimation of Security Price Volatilities from Historical Data," The Journal of Business, University of Chicago Press, vol. 53(1), pages 67-78, January.
    3. Gu, Chen & Kurov, Alexander, 2020. "Informational role of social media: Evidence from Twitter sentiment," Journal of Banking & Finance, Elsevier, vol. 121(C).
    4. Pradipta Kumar Sahoo & Dinabandhu Sethi & Debashis Acharya, 2019. "Is bitcoin a near stock? Linear and non-linear causal evidence from a price–volume relationship," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 15(4), pages 533-545, April.
    5. Yonggang Lu & Qiujie Zheng, 2021. "Twitter public sentiment dynamics on cruise tourism during the COVID-19 pandemic," Current Issues in Tourism, Taylor & Francis Journals, vol. 24(7), pages 892-898, April.
    6. Díaz-Mendoza, Ana-Carmen & Pardo, Angel, 2020. "Holidays, weekends and range-based volatility," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
    7. Ahmed, M. Iqbal & Cassou, Steven P., 2016. "Does consumer confidence affect durable goods spending during bad and good economic times equally?," Journal of Macroeconomics, Elsevier, vol. 50(C), pages 86-97.
    8. Sigala, Marianna, 2020. "Tourism and COVID-19: Impacts and implications for advancing and resetting industry and research," Journal of Business Research, Elsevier, vol. 117(C), pages 312-321.
    9. Naji Jalkh & Elie Bouri & Xuan Vinh Vo & Anupam Dutta, 2021. "Hedging the risk of travel and leisure stocks: The role of crude oil," Tourism Economics, , vol. 27(7), pages 1337-1356, November.
    10. Daniel Andrei & Michael Hasler, 2015. "Investor Attention and Stock Market Volatility," The Review of Financial Studies, Society for Financial Studies, vol. 28(1), pages 33-72.
    11. Patton, Andrew J. & Sheppard, Kevin, 2009. "Optimal combinations of realised volatility estimators," International Journal of Forecasting, Elsevier, vol. 25(2), pages 218-238.
    12. Pradipta Kumar Sahoo & Dinabandhu Sethi & Debashis Acharya, 2019. "Is bitcoin a near stock? Linear and non-linear causal evidence from a price–volume relationship," International Journal of Managerial Finance, Emerald Group Publishing Limited, vol. 15(4), pages 533-545, April.
    13. Alok Kumar Mishra & Badri Narayan Rath & Aruna Kumar Dash, 2020. "Does the Indian Financial Market Nosedive because of the COVID-19 Outbreak, in Comparison to after Demonetisation and the GST?," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 56(10), pages 2162-2180, August.
    14. Syed Jawad Hussain Shahzad & Thi Hong Van Hoang & Elie Bouri, 2022. "From pandemic to systemic risk: contagion in the U.S. tourism sector," Current Issues in Tourism, Taylor & Francis Journals, vol. 25(1), pages 34-40, January.
    15. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    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. Martina Halouskov'a & Daniel Stav{s}ek & Mat'uv{s} Horv'ath, 2022. "The role of investor attention in global asset price variation during the invasion of Ukraine," Papers 2205.05985, arXiv.org, revised Aug 2022.
    2. Halousková, Martina & Stašek, Daniel & Horváth, Matúš, 2022. "The role of investor attention in global asset price variation during the invasion of Ukraine," Finance Research Letters, Elsevier, vol. 50(C).
    3. Lyócsa, Štefan & Todorova, Neda & Výrost, Tomáš, 2021. "Predicting risk in energy markets: Low-frequency data still matter," Applied Energy, Elsevier, vol. 282(PA).
    4. Lyócsa, Štefan & Molnár, Peter & Výrost, Tomáš, 2021. "Stock market volatility forecasting: Do we need high-frequency data?," International Journal of Forecasting, Elsevier, vol. 37(3), pages 1092-1110.
    5. Lyócsa, Štefan & Plíhal, Tomáš & Výrost, Tomáš, 2021. "FX market volatility modelling: Can we use low-frequency data?," Finance Research Letters, Elsevier, vol. 40(C).
    6. Lyócsa, Štefan & Baumöhl, Eduard & Výrost, Tomáš, 2022. "YOLO trading: Riding with the herd during the GameStop episode," Finance Research Letters, Elsevier, vol. 46(PA).
    7. Al Guindy, Mohamed, 2021. "Cryptocurrency price volatility and investor attention," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 556-570.
    8. Smales, L.A., 2022. "Investor attention in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 79(C).
    9. Ming‐Hung Wu & Wan‐Ting Hu & Pei‐Shih Weng, 2023. "Herd behaviors in index futures trading: Driving factors and impact on market volatility," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(10), pages 1373-1392, October.
    10. Chen, Cathy W.S. & Gerlach, Richard & Hwang, Bruce B.K. & McAleer, Michael, 2012. "Forecasting Value-at-Risk using nonlinear regression quantiles and the intra-day range," International Journal of Forecasting, Elsevier, vol. 28(3), pages 557-574.
    11. Umar, Tarik, 2022. "Complexity aversion when SeekingAlpha," Journal of Accounting and Economics, Elsevier, vol. 73(2).
    12. Arısoy, Yakup Eser & Altay-Salih, Aslıhan & Akdeniz, Levent, 2015. "Aggregate volatility expectations and threshold CAPM," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 231-253.
    13. Claudiu Vinte & Marcel Ausloos, 2022. "The Cross-Sectional Intrinsic Entropy. A Comprehensive Stock Market Volatility Estimator," Papers 2205.00104, arXiv.org.
    14. Igor Kliakhandler, 2007. "Execution edge of pit traders and intraday price ranges of soft commodities," Applied Financial Economics, Taylor & Francis Journals, vol. 17(5), pages 343-350.
    15. Sapkota, Niranjan, 2022. "News-based sentiment and bitcoin volatility," International Review of Financial Analysis, Elsevier, vol. 82(C).
    16. Liu, Lily Y. & Patton, Andrew J. & Sheppard, Kevin, 2015. "Does anything beat 5-minute RV? A comparison of realized measures across multiple asset classes," Journal of Econometrics, Elsevier, vol. 187(1), pages 293-311.
    17. Nikkin L. Beronilla & Dennis S. Mapa, 2008. "Range-based models in estimating value-at-risk (VaR)," Philippine Review of Economics, University of the Philippines School of Economics and Philippine Economic Society, vol. 45(2), pages 87-99, December.
    18. Gerlach, Richard & Wang, Chao, 2020. "Semi-parametric dynamic asymmetric Laplace models for tail risk forecasting, incorporating realized measures," International Journal of Forecasting, Elsevier, vol. 36(2), pages 489-506.
    19. Svetlana Lapinova & Alexander Saichev & Maria Tarakanova, 2012. "Volatility estimation based on extremes of the bridge (in Russian)," Quantile, Quantile, issue 10, pages 73-90, December.
    20. Paresh Kumar Narayan & Sagarika Mishra & Seema Narayan, 2015. "New empirical evidence on the bid-ask spread," Applied Economics, Taylor & Francis Journals, vol. 47(42), pages 4484-4500, September.

    More about this item

    Keywords

    Tourism; Twitter; stock volatility; impulse response function; nonlinearity;
    All these keywords.

    JEL classification:

    • G1 - Financial Economics - - General Financial Markets
    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General

    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:ebl:ecbull:eb-22-00414. 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: John P. Conley (email available below). General contact details of provider: .

    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.