IDEAS home Printed from https://ideas.repec.org/a/sae/toueco/v30y2024i1p236-254.html
   My bibliography  Save this article

Investment sensitivity to market uncertainty in the travel and tourism sector

Author

Listed:
  • Abbas Valadkhani

Abstract

Raising capital is critical for the future expansion of travel and tourism businesses which have been adversely impacted by the COVID-19 pandemic. Investors sold their travel and tourism stocks below true value due to falling earnings during the pandemic. This study compares the sensitivity of stocks in different sectors to uncertainty when they are aggregated into different exchange-traded funds (ETFs). This reduces the extent of firm-specific peculiarities arising from market overreactions to news, mergers and acquisitions through time. Although previous studies have highlighted the effect of uncertainty on the financial decisions of travel and tourism firms, this study identifies a ‘fear-triggering point’ in the VIX index above which travel and tourism ETFs enter the state of uncertainty. This study has thus important implications for raising capital and financing tourism businesses in the US equity market, particularly during heightened uncertainty.

Suggested Citation

  • Abbas Valadkhani, 2024. "Investment sensitivity to market uncertainty in the travel and tourism sector," Tourism Economics, , vol. 30(1), pages 236-254, February.
    • Handle: RePEc:sae:toueco:v:30:y:2024:i:1:p:236-254
    DOI: 10.1177/13548166221151098
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/13548166221151098
    Download Restriction: no
    File URL: https://libkey.io/10.1177/13548166221151098?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
    ---><---

    References listed on IDEAS

    as
    1. Bekaert, Geert & Hoerova, Marie & Lo Duca, Marco, 2013. "Risk, uncertainty and monetary policy," Journal of Monetary Economics, Elsevier, vol. 60(7), pages 771-788.
    2. Samuel Xin Liang & K.C. John Wei, 2020. "Market Volatility Risk and Stock Returns around the World: Implication for Multinational Corporations," International Review of Finance, International Review of Finance Ltd., vol. 20(4), pages 923-959, December.
    3. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    4. 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.
    5. Karolyi, G Andrew & Stulz, Rene M, 1996. "Why Do Markets Move Together? An Investigation of U.S.-Japan Stock Return Comovements," Journal of Finance, American Finance Association, vol. 51(3), pages 951-986, July.
    6. Jushan Bai & Pierre Perron, 1998. "Estimating and Testing Linear Models with Multiple Structural Changes," Econometrica, Econometric Society, vol. 66(1), pages 47-78, January.
    7. Vogelsang, Timothy J & Perron, Pierre, 1998. "Additional Tests for a Unit Root Allowing for a Break in the Trend Function at an Unknown Time," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(4), pages 1073-1100, November.
    8. Carter, David & Mazumder, Sharif & Simkins, Betty & Sisneros, Eric, 2022. "The stock price reaction of the COVID-19 pandemic on the airline, hotel, and tourism industries," Finance Research Letters, Elsevier, vol. 44(C).
    9. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. "On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    10. Pettengill, Glenn N. & Sundaram, Sridhar & Mathur, Ike, 1995. "The Conditional Relation between Beta and Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 30(1), pages 101-116, March.
    11. Xiang Lin & Martin Thomas Falk, 2022. "Nordic stock market performance of the travel and leisure industry during the first wave of Covid-19 pandemic," Tourism Economics, , vol. 28(5), pages 1240-1257, August.
    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. Valadkhani, Abbas, 2023. "Asymmetric downside risk across different sectors of the US equity market," Global Finance Journal, Elsevier, vol. 57(C).
    2. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2019. "Macro-Financial Linkages in the High-Frequency Domain: The Effects of Uncertainty on Realized Volatility," CESifo Working Paper Series 8000, CESifo.
    3. Chen, Xiaoyu & Chiang, Thomas C., 2020. "Empirical investigation of changes in policy uncertainty on stock returns—Evidence from China’s market," Research in International Business and Finance, Elsevier, vol. 53(C).
    4. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    5. Hammoudeh, Shawkat & Yuan, Yuan & Chiang, Thomas & Nandha, Mohan, 2010. "Symmetric and asymmetric US sector return volatilities in presence of oil, financial and economic risks," Energy Policy, Elsevier, vol. 38(8), pages 3922-3932, August.
    6. Paraskevi Katsiampa & Kyriaki Begiazi, 2019. "An empirical analysis of the Scottish housing market by property type," Scottish Journal of Political Economy, Scottish Economic Society, vol. 66(4), pages 559-583, September.
    7. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, December.
    8. Baumöhl, Eduard, 2013. "Stock market integration between the CEE-4 and the G7 markets: Asymmetric DCC and smooth transition approach," MPRA Paper 43834, University Library of Munich, Germany.
    9. McMillan, David G. & Ruiz, Isabel, 2009. "Volatility persistence, long memory and time-varying unconditional mean: Evidence from 10 equity indices," The Quarterly Review of Economics and Finance, Elsevier, vol. 49(2), pages 578-595, May.
    10. Baumöhl, Eduard & Lyócsa, Štefan, 2014. "Volatility and dynamic conditional correlations of worldwide emerging and frontier markets," Economic Modelling, Elsevier, vol. 38(C), pages 175-183.
    11. 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.
    12. Altaf Muhammad & Zhang Shuguang, 2015. "Impact Of Structural Shifts on Variance Persistence in Asymmetric Garch Models: Evidence From Emerging Asian and European Markets," Romanian Statistical Review, Romanian Statistical Review, vol. 63(1), pages 57-70, March.
    13. Czudaj Robert L., 2020. "The role of uncertainty on agricultural futures markets momentum trading and volatility," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(3), pages 1-39, June.
    14. Christoph S. Weber, 2018. "Central bank transparency and inflation (volatility) – new evidence," International Economics and Economic Policy, Springer, vol. 15(1), pages 21-67, January.
    15. He, Changli & Teräsvirta, Timo, 1999. "Higher-order dependence in the general Power ARCH process and a special case," SSE/EFI Working Paper Series in Economics and Finance 315, Stockholm School of Economics.
    16. Ender Su & John Bilson, 2011. "Trading asymmetric trend and volatility by leverage trend GARCH in Taiwan stock index," Applied Economics, Taylor & Francis Journals, vol. 43(26), pages 3891-3905.
    17. Rituparna Sen & Pulkit Mehrotra, 2016. "Modeling Jumps and Volatility of the Indian Stock Market Using High-Frequency Data," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 14(1), pages 137-150, June.
    18. Christophe Chorro & Dominique Guegan & Florian Ielpo, 2010. "Option pricing for GARCH-type models with generalized hyperbolic innovations," Post-Print halshs-00469529, HAL.
    19. Chalamandaris, Georgios & Rompolis, Leonidas S., 2012. "Exploring the role of the realized return distribution in the formation of the implied volatility smile," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 1028-1044.
    20. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.

    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:sae:toueco:v:30:y:2024:i:1:p:236-254. 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: SAGE Publications (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.