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The fair value of a token: How do markets price cryptocurrencies?

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  • Nadler, Philip
  • Guo, Yike

Abstract

With the rise of cryptocurrency tokens as a new asset class, the question of the fair evaluation of a cryptocurrency token has become a question of increasing importance. We estimate the pricing kernel with which users price factors affecting their token holdings. We investigate how traditional risk factors such as market risk are evaluated, as well as how blockchain specific risk factors are priced in. In order to do so, we introduce an asset pricing model and modify its properties to make it applicable to cryptocurrency markets. We group the risk factors into market related and Bitcoin- and Ethereum blockchain specific risk factors. We find that blockchain specific risk factors are priced in. There is evidence that risk factors have moved from Bitcoin to Ethereum specific risk factors with an increasing importance of market factors, providing evidence for a decoupling of on-chain and off-chain trading activity.

Suggested Citation

  • Nadler, Philip & Guo, Yike, 2020. "The fair value of a token: How do markets price cryptocurrencies?," Research in International Business and Finance, Elsevier, vol. 52(C).
  • Handle: RePEc:eee:riibaf:v:52:y:2020:i:c:s0275531919300601
    DOI: 10.1016/j.ribaf.2019.101108
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    as
    1. Symitsi, Efthymia & Chalvatzis, Konstantinos J., 2019. "The economic value of Bitcoin: A portfolio analysis of currencies, gold, oil and stocks," Research in International Business and Finance, Elsevier, vol. 48(C), pages 97-110.
    2. Acharya, Viral V. & Pedersen, Lasse Heje, 2005. "Asset pricing with liquidity risk," Journal of Financial Economics, Elsevier, vol. 77(2), pages 375-410, August.
    3. Yukun Liu & Aleh Tsyvinski, 2018. "Risks and Returns of Cryptocurrency," NBER Working Papers 24877, National Bureau of Economic Research, Inc.
    4. Tim Bollerslev & George Tauchen & Hao Zhou, 2009. "Expected Stock Returns and Variance Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4463-4492, November.
    5. Stephen A. Ross, 2013. "The Arbitrage Theory of Capital Asset Pricing," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 1, pages 11-30, World Scientific Publishing Co. Pte. Ltd..
    6. Huberman, Gur & Kandel, Shmuel & Stambaugh, Robert F, 1987. "Mimicking Portfolios and Exact Arbitrage Pricing," Journal of Finance, American Finance Association, vol. 42(1), pages 1-9, March.
    7. Bullmann, Dirk & Klemm, Jonas & Pinna, Andrea, 2019. "In search for stability in crypto-assets: are stablecoins the solution?," Occasional Paper Series 230, European Central Bank.
    8. Tobias Adrian & Joshua Rosenberg, 2008. "Stock Returns and Volatility: Pricing the Short‐Run and Long‐Run Components of Market Risk," Journal of Finance, American Finance Association, vol. 63(6), pages 2997-3030, December.
    9. Douglas T. Breeden & Michael R Gibbons & Robert H. Litzenberger, "undated". "Empirical Tests of the Consumption-Oriented CAPM," Rodney L. White Center for Financial Research Working Papers 07-89, Wharton School Rodney L. White Center for Financial Research.
    10. Fantazzini, Dean & Nigmatullin, Erik & Sukhanovskaya, Vera & Ivliev, Sergey, 2017. "Everything you always wanted to know about bitcoin modelling but were afraid to ask. Part 2," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 45, pages 5-28.
    11. Huberman, Gur & Leshno, Jacob & Moallemi, Ciamac C., 2017. "Monopoly Without a Monopolist: An Economic Analysis of the Bitcoin Payment System," CEPR Discussion Papers 12322, C.E.P.R. Discussion Papers.
    12. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    13. Ravi Bansal & Dana Kiku & Ivan Shaliastovich & Amir Yaron, 2014. "Volatility, the Macroeconomy, and Asset Prices," Journal of Finance, American Finance Association, vol. 69(6), pages 2471-2511, December.
    14. Härdle, Wolfgang Karl & Trimborn, Simon, 2015. "CRIX or evaluating blockchain based currencies," SFB 649 Discussion Papers 2015-048, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    15. Balduzzi, Pierluigi & Robotti, Cesare, 2008. "Mimicking Portfolios, Economic Risk Premia, and Tests of Multi-Beta Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 354-368.
    16. repec:zbw:bofrdp:2017_027 is not listed on IDEAS
    17. Roman Kozhan & Anthony Neuberger & Paul Schneider, 2013. "The Skew Risk Premium in the Equity Index Market," The Review of Financial Studies, Society for Financial Studies, vol. 26(9), pages 2174-2203.
    18. repec:bla:jfinan:v:44:y:1989:i:2:p:231-62 is not listed on IDEAS
    19. John Lintner, 1965. "Security Prices, Risk, And Maximal Gains From Diversification," Journal of Finance, American Finance Association, vol. 20(4), pages 587-615, December.
    20. Urquhart, Andrew, 2016. "The inefficiency of Bitcoin," Economics Letters, Elsevier, vol. 148(C), pages 80-82.
    21. 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.
    22. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    23. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    24. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    25. Douglas T. Breeden & Michael R Gibbons & Robert H. Litzenberger, "undated". "Empirical Tests of the Consumption-Oriented CAPM," Rodney L. White Center for Financial Research Working Papers 7-89, Wharton School Rodney L. White Center for Financial Research.
    26. Koutmos, Dimitrios, 2018. "Bitcoin returns and transaction activity," Economics Letters, Elsevier, vol. 167(C), pages 81-85.
    27. Wei, Wang Chun, 2018. "Liquidity and market efficiency in cryptocurrencies," Economics Letters, Elsevier, vol. 168(C), pages 21-24.
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    Citations

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    Cited by:

    1. Wang, Jinghua & Ngene, Geoffrey M., 2020. "Does Bitcoin still own the dominant power? An intraday analysis," International Review of Financial Analysis, Elsevier, vol. 71(C).
    2. Kyriazis, Nikolaos & Papadamou, Stephanos & Corbet, Shaen, 2020. "A systematic review of the bubble dynamics of cryptocurrency prices," Research in International Business and Finance, Elsevier, vol. 54(C).
    3. Şoiman, Florentina & Dumas, Jean-Guillaume & Jimenez-Garces, Sonia, 2023. "What drives DeFi market returns?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 85(C).
    4. Saggu, Aman & Ante, Lennart & Demir, Ender, 2024. "Anticipatory gains and event-driven losses in blockchain-based fan tokens: Evidence from the FIFA World Cup," Research in International Business and Finance, Elsevier, vol. 70(PA).
    5. Patel, Ritesh & Migliavacca, Milena & Oriani, Marco E., 2022. "Blockchain in banking and finance: A bibliometric review," Research in International Business and Finance, Elsevier, vol. 62(C).
    6. Sun, Xiaotong & Stasinakis, Charalampos & Sermpinis, Georgios, 2024. "Decentralization illusion in Decentralized Finance: Evidence from tokenized voting in MakerDAO polls," Journal of Financial Stability, Elsevier, vol. 73(C).
    7. Jean-Guillaume Dumas & Sonia Jimenez-Garces & Florentina Șoiman, 2021. "Risk analyses of the crypto-market: A literature review," Post-Print hal-03112920, HAL.
    8. Dulani Jayasuriya Daluwathumullagamage & Alexandra Sims, 2021. "Fantastic Beasts: Blockchain Based Banking," JRFM, MDPI, vol. 14(4), pages 1-43, April.
    9. Gill-de-Albornoz, Belén & Lafuente, Juan A. & Monfort, Mercedes & Ordoñez, Javier, 2024. "Bitcoin attention and economic policy uncertainty," Finance Research Letters, Elsevier, vol. 60(C).
    10. Jean-Guillaume Dumas & Sonia Jimenez-Garcès & Florentina Șoiman, 2021. "Blockchain technology and crypto-assets market analysis: vulnerabilities and risk assessment," Working Papers hal-03112920, HAL.
    11. Kamilla Marchewka-Bartkowiak & Karolina Anna Nowak & Michał Litwiński, 2022. "Digital valuation of personality using personal tokens," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1555-1576, September.
    12. Almeida, José & Gonçalves, Tiago Cruz, 2023. "A systematic literature review of investor behavior in the cryptocurrency markets," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).

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    More about this item

    Keywords

    Bitcoin; Cryptocurrencies; Asset pricing; Risk factors;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G19 - Financial Economics - - General Financial Markets - - - Other
    • D58 - Microeconomics - - General Equilibrium and Disequilibrium - - - Computable and Other Applied General Equilibrium Models

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