IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2310.04907.html
   My bibliography  Save this paper

An Information Theory Approach to the Stock and Cryptocurrency Market: A Statistical Equilibrium Perspective

Author

Listed:
  • Emanuele Citera
  • Francesco De Pretis

Abstract

We study the stochastic structure of cryptocurrency rates of returns as compared to stock returns by focusing on the associated cross-sectional distributions. We build two datasets. The first comprises forty-six major cryptocurrencies, and the second includes all the companies listed in the S&P 500. We collect individual data from January 2017 until December 2022. We then apply the Quantal Response Statistical Equilibrium (QRSE) model to recover the cross-sectional frequency distribution of the daily returns of cryptocurrencies and S&P 500 companies. We study the stochastic structure of these two markets and the properties of investors' behavior over bear and bull trends. Finally, we compare the degree of informational efficiency of these two markets.

Suggested Citation

  • Emanuele Citera & Francesco De Pretis, 2023. "An Information Theory Approach to the Stock and Cryptocurrency Market: A Statistical Equilibrium Perspective," Papers 2310.04907, arXiv.org.
    • Handle: RePEc:arx:papers:2310.04907
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2310.04907
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Batra, Luckshay & Taneja, H.C., 2020. "Evaluating volatile stock markets using information theoretic measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    2. Ellis Scharfenaker, Duncan K. Foley, 2023. "The Neutrality of Money Reconsidered: A Statistical Equilibrium Model of the Labor Market," Working Paper Series, Department of Economics, University of Utah 2023_02, University of Utah, Department of Economics.
    3. Ellis Scharfenaker & Duncan Foley, 2017. "Maximum Entropy Estimation of Statistical Equilibrium in Economic Quantal Response Models," Working Papers 1710, New School for Social Research, Department of Economics, revised May 2017.
    4. Benjamin Patrick Evans & Mikhail Prokopenko, 2021. "A maximum entropy model of bounded rational decision-making with prior beliefs and market feedback," Papers 2102.09180, arXiv.org, revised May 2021.
    5. Dickey, David A & Fuller, Wayne A, 1981. "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root," Econometrica, Econometric Society, vol. 49(4), pages 1057-1072, June.
    6. Luckshay Batra & Harish Chander Taneja, 2022. "Comparison between Information Theoretic Measures to Assess Financial Markets," FinTech, MDPI, vol. 1(2), pages 1-18, May.
    7. Nicola Borri & Kirill Shakhnov, 2022. "The Cross-Section of Cryptocurrency Returns [A simple estimation of bid-ask spreads from daily close, high, and low prices]," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 12(3), pages 667-705.
    8. Soofi, E. S. & Retzer, J. J., 2002. "Information indices: unification and applications," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 17-40, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sündal, Doğuhan, 2024. "Relative size distribution of business firms—A QRSE approach," Economic Modelling, Elsevier, vol. 140(C).

    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. Emanuele Citera, 2021. "Stock Returns, Market Trends, and Information Theory: A Statistical Equilibrium Approach," Working Papers 2116, New School for Social Research, Department of Economics.
    2. Ellis Scharfenaker, 2022. "Statistical Equilibrium Methods In Analytical Political Economy," Journal of Economic Surveys, Wiley Blackwell, vol. 36(2), pages 276-309, April.
    3. Muhammad Zia Ullah Khan & Muhammad Illyas & Muqqadas Rahman & Chaudhary Abdul Rahman, 2015. "Money Monetization and Economic Growth in Pakistan," International Journal of Economics and Empirical Research (IJEER), The Economics and Social Development Organization (TESDO), vol. 3(4), pages 184-192, April.
    4. Yap, Wei Yim & Lam, Jasmine S.L., 2006. "Competition dynamics between container ports in East Asia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(1), pages 35-51, January.
    5. Erasmia Kotroni & Dimitra Kaika & Efthimios Zervas, 2020. "Environmental Kuznets Curve in Greece in the period 1960-2014," International Journal of Energy Economics and Policy, Econjournals, vol. 10(4), pages 364-370.
    6. Shyh-Wei Chen, 2008. "Non-stationarity and Non-linearity in Stock Prices: Evidence from the OECD Countries," Economics Bulletin, AccessEcon, vol. 3(11), pages 1-11.
    7. Ely, David & Salehizadeh, Mehdi, 2001. "American depositary receipts: An analysis of international stock price movements," International Review of Financial Analysis, Elsevier, vol. 10(4), pages 343-363.
    8. Kazem Yavari & Mina Mehrnoosh, 2005. "The Welfare Cost of Inflation in Iran," Iranian Economic Review (IER), Faculty of Economics,University of Tehran.Tehran,Iran, vol. 10(2), pages 111-117, fall.
    9. Choi-Meng Leong & Chin-Hong Puah & Shazali Abu Mansor & Evan Lau, 2010. "Testing the Effectiveness of Monetary Policy in Malaysia Using Alternative Monetary Aggregation," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 4(3), pages 321-338, August.
    10. Ali MNA & Moheddine YOUNSI, 2018. "A monetary conditions index and its application on Tunisian economic forecasting," Journal of Economics and Political Economy, KSP Journals, vol. 5(1), pages 38-56, March.
    11. Jan Babecký & Fabrizio Coricelli & Roman Horváth, 2009. "Assessing Inflation Persistence: Micro Evidence on an Inflation Targeting Economy," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 59(2), pages 102-127, June.
    12. Hauser, Shmuel & Kedar-Levy, Haim & Milo, Orit, 2022. "Price discovery during parallel stocks and options preopening: Information distortion and hints of manipulation," Journal of Financial Markets, Elsevier, vol. 59(PA).
    13. Rocha, Roberto de Rezende, 1991. "Inflation and stabilization in Yugoslavia," Policy Research Working Paper Series 752, The World Bank.
    14. Dhanya Jothimani & Ravi Shankar & Surendra S. Yadav, 2016. "Discrete Wavelet Transform-Based Prediction of Stock Index: A Study on National Stock Exchange Fifty Index," Papers 1605.07278, arXiv.org.
    15. Maria Soledad Martinez Peria, 2002. "The Impact of Banking Crises on Money Demand and Price Stability," IMF Staff Papers, Palgrave Macmillan, vol. 49(3), pages 1-1.
    16. Chi-Wei Su, 2012. "The relationship between exchange rate and macroeconomic variables in China," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 30(1), pages 33-56.
    17. Apergis, Nicholas, 2005. "An estimation of the natural rate of unemployment in Greece," Journal of Policy Modeling, Elsevier, vol. 27(1), pages 91-99, February.
    18. Erida Curraj, 2019. "Vintage Design Furniture in Albania, a New Retro Design Paradigm in the Post-Communist Era," European Journal of Engineering and Formal Sciences Articles, Revistia Research and Publishing, vol. 2, ejef_19.
    19. Grigori Fainstein & Igor Novikov, 2011. "The Comparative Analysis of Credit Risk Determinants In the Banking Sector of the Baltic States," Review of Economics & Finance, Better Advances Press, Canada, vol. 1, pages 20-45, June.
    20. Hu, Junjie & López Cabrera, Brenda & Melzer, Awdesch, 2021. "Advanced statistical learning on short term load process forecasting," IRTG 1792 Discussion Papers 2021-020, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:arx:papers:2310.04907. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.