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Valuation, Liquidity Price, and Stability of Cryptocurrencies

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  • Carey Caginalp
  • Gunduz Caginalp

Abstract

Cryptocurrencies are examined through the asset flow equations and experimental asset markets. Since tangible value of a typical cryptocurrency is non-existent, the theory suggests that price will gravitate toward liquidity value, i.e., the total amount of cash available for purchase of the asset divided by the number of units. Thus it is unlikely that cryptocurrencies in their current form will be stable in the absence of a mechanism of a link to value.

Suggested Citation

  • Carey Caginalp & Gunduz Caginalp, 2018. "Valuation, Liquidity Price, and Stability of Cryptocurrencies," Papers 1802.09959, arXiv.org.
    • Handle: RePEc:arx:papers:1802.09959
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    References listed on IDEAS

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    1. Robert J. Shiller, 2015. "Irrational Exuberance," Economics Books, Princeton University Press, edition 3, number 10421.
    2. Caginalp, Gunduz & DeSantis, Mark & Sayrak, Akin, 2014. "The nonlinear price dynamics of U.S. equity ETFs," Journal of Econometrics, Elsevier, vol. 183(2), pages 193-201.
    3. Reshmaan N. Hussam & David Porter & Vernon L. Smith, 2008. "Thar She Blows: Can Bubbles Be Rekindled with Experienced Subjects?," American Economic Review, American Economic Association, vol. 98(3), pages 924-937, June.
    4. Smith, Vernon L & Suchanek, Gerry L & Williams, Arlington W, 1988. "Bubbles, Crashes, and Endogenous Expectations in Experimental Spot Asset Markets," Econometrica, Econometric Society, vol. 56(5), pages 1119-1151, September.
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    Cited by:

    1. Carl Luft & Jin Man Lee & Jin W. Choi, 2019. "“Chicago Mercantile Exchange Bitcoin Futures: Volatility, Liquidity and Margin”," SPOUDAI Journal of Economics and Business, SPOUDAI Journal of Economics and Business, University of Piraeus, vol. 69(3), pages 55-74, July-Sept.
    2. Vernon L. Smith, 2020. "Causal versus Consequential Motives in Mental Models of Agent Social and Economic Action: Experiments, and the Neoclassical Diversion in Economics," Kyklos, Wiley Blackwell, vol. 73(3), pages 341-370, August.
    3. Pınar Kaya Soylu & Mustafa Okur & Özgür Çatıkkaş & Z. Ayca Altintig, 2020. "Long Memory in the Volatility of Selected Cryptocurrencies: Bitcoin, Ethereum and Ripple," JRFM, MDPI, vol. 13(6), pages 1-21, May.
    4. Carey Caginalp, 2018. "A Dynamical Systems Approach to Cryptocurrency Stability," Papers 1805.03143, arXiv.org.
    5. Flori, Andrea, 2019. "News and subjective beliefs: A Bayesian approach to Bitcoin investments," Research in International Business and Finance, Elsevier, vol. 50(C), pages 336-356.
    6. Stefano Martinazzi & Daniele Regoli & Andrea Flori, 2020. "A Tale of Two Layers: The Mutual Relationship between Bitcoin and Lightning Network," Risks, MDPI, vol. 8(4), pages 1-18, December.
    7. Garrison Hongyu Song, 2023. "Valuation of Cryptocurrency Without Intrinsic Value: A Promise of Future Payment System and Implications to De-dollarization," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 49(2), pages 221-248, April.
    8. Ke Wu & Spencer Wheatley & Didier Sornette, 2018. "Classification of cryptocurrency coins and tokens by the dynamics of their market capitalisations," Papers 1803.03088, arXiv.org, revised May 2018.

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