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The implications of virtual money on travel and tourism

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  • Manahov, Viktor
  • Li, Mingnan

Abstract

We obtain daily data of Bitcoin, Ethereum, Travala token, Kemacoin and Guider to investigate the implications of history's most famous five heists on travel and tourism. We find a statistically significant spillover effect in the cryptocurrency and tourism token markets with a limited impact on travel and tourism companies' stock prices. We also find evidence of herding behaviour and observe that overall market quality deteriorated because of the heists. To deal with these negative implications, we propose implementing tools based on artificial intelligence algorithms, emphasising the two leading cryptocurrencies – Bitcoin and Ethereum. Tracking major crypto wallets and ‘whales’ can help regulators identify potential hacks and mitigate systemic risk caused by spillovers in cryptocurrency markets.

Suggested Citation

  • Manahov, Viktor & Li, Mingnan, 2024. "The implications of virtual money on travel and tourism," Annals of Tourism Research, Elsevier, vol. 105(C).
    • Handle: RePEc:eee:anture:v:105:y:2024:i:c:s0160738323001597
    DOI: 10.1016/j.annals.2023.103686
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    1. Andrei O. J. Kwok & Sharon G. M. Koh, 2019. "Is blockchain technology a watershed for tourism development?," Current Issues in Tourism, Taylor & Francis Journals, vol. 22(20), pages 2447-2452, December.
    2. Brauneis, Alexander & Mestel, Roland & Theissen, Erik, 2021. "What drives the liquidity of cryptocurrencies? A long-term analysis," Finance Research Letters, Elsevier, vol. 39(C).
    3. Chiang, Thomas C. & Zheng, Dazhi, 2010. "An empirical analysis of herd behavior in global stock markets," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1911-1921, August.
    4. Lorenzo Cappiello & Robert F. Engle & Kevin Sheppard, 2006. "Asymmetric Dynamics in the Correlations of Global Equity and Bond Returns," Journal of Financial Econometrics, Oxford University Press, vol. 4(4), pages 537-572.
    5. Xu, Qiuhua & Zhang, Yixuan & Zhang, Ziyang, 2021. "Tail-risk spillovers in cryptocurrency markets," Finance Research Letters, Elsevier, vol. 38(C).
    6. Chung, Kee H. & Zhang, Hao, 2014. "A simple approximation of intraday spreads using daily data," Journal of Financial Markets, Elsevier, vol. 17(C), pages 94-120.
    7. Obryan Poyser, 2018. "Herding behavior in cryptocurrency markets," Papers 1806.11348, arXiv.org, revised Nov 2018.
    8. Ioannis Antoniadis & Konstantinos Spinthiropoulos & Stamatis Kontsas, 2020. "Blockchain Applications in Tourism and Tourism Marketing: A Short Review," Springer Proceedings in Business and Economics, in: Androniki Kavoura & Efstathios Kefallonitis & Prokopios Theodoridis (ed.), Strategic Innovative Marketing and Tourism, pages 375-384, Springer.
    9. Marco Valeri & Rodolfo Baggio, 2021. "A critical reflection on the adoption of blockchain in tourism," Information Technology & Tourism, Springer, vol. 23(2), pages 121-132, June.
    10. Lesmond, David A & Ogden, Joseph P & Trzcinka, Charles A, 1999. "A New Estimate of Transaction Costs," The Review of Financial Studies, Society for Financial Studies, vol. 12(5), pages 1113-1141.
    11. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
    12. Önder, Irem & Treiblmaier, Horst, 2018. "Blockchain and tourism: Three research propositions," Annals of Tourism Research, Elsevier, vol. 72(C), pages 180-182.
    13. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    14. Sreejith Balasubramanian & Jaspreet Singh Sethi & Shalini Ajayan & Cody Morris Paris, 2022. "An enabling Framework for Blockchain in Tourism," Information Technology & Tourism, Springer, vol. 24(2), pages 165-179, June.
    15. Inessa Tyan & Antonio Guevara-Plaza & Mariemma I. Yagüe, 2021. "The Benefits of Blockchain Technology for Medical Tourism," Sustainability, MDPI, vol. 13(22), pages 1-12, November.
    16. Inessa Tyan & Mariemma I. Yagüe & Antonio Guevara-Plaza, 2020. "Blockchain Technology for Smart Tourism Destinations," Sustainability, MDPI, vol. 12(22), pages 1-11, November.
    17. Timothy King & Dimitrios Koutmos, 2021. "Herding and feedback trading in cryptocurrency markets," Annals of Operations Research, Springer, vol. 300(1), pages 79-96, May.
    18. Fry, John & Cheah, Eng-Tuck, 2016. "Negative bubbles and shocks in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 343-352.
    19. Yue, Wei & Zhang, Sijia & Zhang, Qiang, 2021. "Asymmetric News Effects on Cryptocurrency Liquidity: an Event Study Perspective," Finance Research Letters, Elsevier, vol. 41(C).
    20. Roberto Leonardo Rana & Nino Adamashvili & Caterina Tricase, 2022. "The Impact of Blockchain Technology Adoption on Tourism Industry: A Systematic Literature Review," Sustainability, MDPI, vol. 14(12), pages 1-17, June.
    21. Roll, Richard, 1984. "A Simple Implicit Measure of the Effective Bid-Ask Spread in an Efficient Market," Journal of Finance, American Finance Association, vol. 39(4), pages 1127-1139, September.
    22. Goyenko, Ruslan Y. & Holden, Craig W. & Trzcinka, Charles A., 2009. "Do liquidity measures measure liquidity?," Journal of Financial Economics, Elsevier, vol. 92(2), pages 153-181, May.
    23. Jesse Yli-Huumo & Deokyoon Ko & Sujin Choi & Sooyong Park & Kari Smolander, 2016. "Where Is Current Research on Blockchain Technology?—A Systematic Review," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-27, October.
    24. Ji, Qiang & Bouri, Elie & Lau, Chi Keung Marco & Roubaud, David, 2019. "Dynamic connectedness and integration in cryptocurrency markets," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 257-272.
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