IDEAS home Printed from https://ideas.repec.org/a/gam/jrisks/v11y2023i3p49-d1077135.html
   My bibliography  Save this article

Cryptocurrencies as Gamblified Financial Assets and Cryptocasinos: Novel Risks for a Public Health Approach to Gambling

Author

Listed:
  • Maira Andrade

    (School of Psychology, University of East London, London E16 2RD, UK)

  • Philip W. S. Newall

    (School of Psychological Science, University of Bristol, Bristol BS8 1TU, UK)

Abstract

Policymakers’ attempts to prevent gambling-related harm are affected by the ‘gamblification’ of, for example, video games and investing. This review highlights related issues posed by cryptocurrencies, which are decentralised and volatile digital assets, and which underlie ‘cryptocasinos’—a new generation of online gambling operators. Cryptocurrencies can be traded around the clock and provide the allure of big potential lottery-like wins. Frequent cryptocurrency traders often suffer from gambling-related harm, which suggests that many users are taking on substantial risks. Further, the lack of regulation around cryptocurrencies and social media echo chambers increases users’ risk of being scammed. In comparison to the conventional regulated online gambling sector, cryptocasinos pose novel risks for existing online gamblers, and can also make online gambling accessible to the underage, the self-excluded, and those living in jurisdictions where online gambling is illegal. Researchers and policymakers should continue to monitor developments in this fast-moving space.

Suggested Citation

  • Maira Andrade & Philip W. S. Newall, 2023. "Cryptocurrencies as Gamblified Financial Assets and Cryptocasinos: Novel Risks for a Public Health Approach to Gambling," Risks, MDPI, vol. 11(3), pages 1-14, February.
  • Handle: RePEc:gam:jrisks:v:11:y:2023:i:3:p:49-:d:1077135
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-9091/11/3/49/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-9091/11/3/49/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Daniel Fernandes & John G. Lynch & Richard G. Netemeyer, 2014. "Financial Literacy, Financial Education, and Downstream Financial Behaviors," Management Science, INFORMS, vol. 60(8), pages 1861-1883, August.
    2. Hasso, Tim & Pelster, Matthias & Breitmayer, Bastian, 2019. "Who trades cryptocurrencies, how do they trade it, and how do they perform? Evidence from brokerage accounts," Journal of Behavioral and Experimental Finance, Elsevier, vol. 23(C), pages 64-74.
    3. 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.
    4. Gandal, Neil & Hamrick, JT & Moore, Tyler & Oberman, Tali, 2018. "Price manipulation in the Bitcoin ecosystem," Journal of Monetary Economics, Elsevier, vol. 95(C), pages 86-96.
    5. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & David Martinez-Rego & Fan Wu & Lingbo Li, 2022. "Cryptocurrency trading: a comprehensive survey," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-59, December.
    6. Dowling, Michael, 2022. "Is non-fungible token pricing driven by cryptocurrencies?," Finance Research Letters, Elsevier, vol. 44(C).
    7. Harrison Hong & Jeffrey D. Kubik & Jeremy C. Stein, 2004. "Social Interaction and Stock-Market Participation," Journal of Finance, American Finance Association, vol. 59(1), pages 137-163, February.
    8. Fan Fang & Carmine Ventre & Michail Basios & Leslie Kanthan & Lingbo Li & David Martinez-Regoband & Fan Wu, 2020. "Cryptocurrency Trading: A Comprehensive Survey," Papers 2003.11352, arXiv.org, revised Jan 2022.
    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. Pietro Saggese & Esther Segalla & Michael Sigmund & Burkhard Raunig & Felix Zangerl & Bernhard Haslhofer, 2023. "Assessing the Solvency of Virtual Asset Service Providers: Are Current Standards Sufficient?," Papers 2309.16408, arXiv.org, revised Apr 2024.
    2. Orte, Francisco & Mira, José & Sánchez, María Jesús & Solana, Pablo, 2023. "A random forest-based model for crypto asset forecasts in futures markets with out-of-sample prediction," Research in International Business and Finance, Elsevier, vol. 64(C).
    3. Ştefan Cristian Gherghina & Liliana Nicoleta Simionescu, 2023. "Exploring the asymmetric effect of COVID-19 pandemic news on the cryptocurrency market: evidence from nonlinear autoregressive distributed lag approach and frequency domain causality," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-58, December.
    4. Bernhard Haslhofer & Burkhard Raunig & Pietro Saggase & Esther Segalla & Michael Sigmund & Felix Zangerl, 2023. "Assessing the Solvency of Virtual Asset Service Providers: Are Current Standards Sufficient? (Pietro Saggese, Esther Segalla, Michael Sigmund, Burkhard Raunig, Felix Zangerl, Bernhard Haslhofer)," Working Papers 248, Oesterreichische Nationalbank (Austrian Central Bank).
    5. Saggese, Pietro & Belmonte, Alessandro & Dimitri, Nicola & Facchini, Angelo & Böhme, Rainer, 2023. "Arbitrageurs in the Bitcoin ecosystem: Evidence from user-level trading patterns in the Mt. Gox exchange platform," Journal of Economic Behavior & Organization, Elsevier, vol. 213(C), pages 251-270.
    6. Soria, Jorge & Moya, Jorge & Mohazab, Amin, 2023. "Optimal mining in proof-of-work blockchain protocols," Finance Research Letters, Elsevier, vol. 53(C).
    7. Siu Hin Tang & Mathieu Rosenbaum & Chao Zhou, 2023. "Forecasting Volatility with Machine Learning and Rough Volatility: Example from the Crypto-Winter," Papers 2311.04727, arXiv.org, revised Feb 2024.
    8. Davidoff, Thomas & Gerhard, Patrick & Post, Thomas, 2017. "Reverse mortgages: What homeowners (don’t) know and how it matters," Journal of Economic Behavior & Organization, Elsevier, vol. 133(C), pages 151-171.
    9. Husam Rjoub & Tomiwa Sunday Adebayo & Dervis Kirikkaleli, 2023. "Blockchain technology-based FinTech banking sector involvement using adaptive neuro-fuzzy-based K-nearest neighbors algorithm," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-23, December.
    10. Marcin Wątorek & Jarosław Kwapień & Stanisław Drożdż, 2022. "Multifractal Cross-Correlations of Bitcoin and Ether Trading Characteristics in the Post-COVID-19 Time," Future Internet, MDPI, vol. 14(7), pages 1-15, July.
    11. Laurens Swinkels, 2023. "Empirical evidence on the ownership and liquidity of real estate tokens," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-29, December.
    12. Luyao Zhang & Tianyu Wu & Saad Lahrichi & Carlos-Gustavo Salas-Flores & Jiayi Li, 2022. "A Data Science Pipeline for Algorithmic Trading: A Comparative Study of Applications for Finance and Cryptoeconomics," Papers 2206.14932, arXiv.org.
    13. Kirimhan, Destan, 2023. "Importance of anti-money laundering regulations among prosumers for a cybersecure decentralized finance," Journal of Business Research, Elsevier, vol. 157(C).
    14. Kate Murray & Andrea Rossi & Diego Carraro & Andrea Visentin, 2023. "On Forecasting Cryptocurrency Prices: A Comparison of Machine Learning, Deep Learning, and Ensembles," Forecasting, MDPI, vol. 5(1), pages 1-14, January.
    15. Chang, Sheng-Kai, 2007. "A simple asset pricing model with social interactions and heterogeneous beliefs," Journal of Economic Dynamics and Control, Elsevier, vol. 31(4), pages 1300-1325, April.
    16. Luis Lorenzo & Javier Arroyo, 2023. "Online risk-based portfolio allocation on subsets of crypto assets applying a prototype-based clustering algorithm," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-40, December.
    17. Wujun Lv & Tao Pang & Xiaobao Xia & Jingzhou Yan, 2023. "Dynamic portfolio choice with uncertain rare-events risk in stock and cryptocurrency markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-28, December.
    18. Wei Xu & Daning Hu & Karl Reiner Lang & J. Leon Zhao, 2022. "Blockchain and digital finance," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-4, December.
    19. Delis, Manthos D. & Mylonidis, Nikolaos, 2015. "Trust, happiness, and households’ financial decisions," Journal of Financial Stability, Elsevier, vol. 20(C), pages 82-92.
    20. Bennett, Donyetta & Mekelburg, Erik & Williams, T.H., 2023. "BeFi meets DeFi: A behavioral finance approach to decentralized finance asset pricing," Research in International Business and Finance, Elsevier, vol. 65(C).

    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:jrisks:v:11:y:2023:i:3:p:49-:d:1077135. 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.