IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v56y2023ics1544612323004415.html
   My bibliography  Save this article

Extrapolative beliefs about Bitcoin returns

Author

Listed:
  • Petkova, Ralitsa

Abstract

Using survey data from Sentix which records whether investors are bullish, bearish, or neutral about the future price of Bitcoin, we examine how investors form expectations about Bitcoin returns. We use a model for expectations with an exponential decay of weights on past returns and find that investors extrapolate from Bitcoin’s past returns in a way that puts more weight on more recent returns. Compared to institutional investors, individuals display a higher degree of extrapolation, consistent with the perception that nonprofessionals are more prone to behavioral biases. The extrapolative component of expectations is a significant predictor of Bitcoin returns in the short term, however, its explanatory power is small. Understanding how investors in the cryptocurrency market form their beliefs is important because variation in beliefs could affect Bitcoin price dynamics and potentially lead to excess volatility, momentum, and reversal.

Suggested Citation

  • Petkova, Ralitsa, 2023. "Extrapolative beliefs about Bitcoin returns," Finance Research Letters, Elsevier, vol. 56(C).
    • Handle: RePEc:eee:finlet:v:56:y:2023:i:c:s1544612323004415
    DOI: 10.1016/j.frl.2023.104069
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612323004415
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2023.104069?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Stefano Giglio & Matteo Maggiori & Johannes Stroebel & Stephen Utkus, 2021. "Five Facts about Beliefs and Portfolios," American Economic Review, American Economic Association, vol. 111(5), pages 1481-1522, May.
    2. Shen, Dehua & Urquhart, Andrew & Wang, Pengfei, 2019. "Does twitter predict Bitcoin?," Economics Letters, Elsevier, vol. 174(C), pages 118-122.
    3. Kosc, Krzysztof & Sakowski, Paweł & Ślepaczuk, Robert, 2019. "Momentum and contrarian effects on the cryptocurrency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 691-701.
    4. Peter Temin & Hans-Joachim Voth, 2004. "Riding the South Sea Bubble," American Economic Review, American Economic Association, vol. 94(5), pages 1654-1668, December.
    5. Bacchetta, Philippe & Mertens, Elmar & van Wincoop, Eric, 2009. "Predictability in financial markets: What do survey expectations tell us?," Journal of International Money and Finance, Elsevier, vol. 28(3), pages 406-426, April.
    6. De Long, J Bradford, et al, 1990. "Positive Feedback Investment Strategies and Destabilizing Rational Speculation," Journal of Finance, American Finance Association, vol. 45(2), pages 379-395, June.
    7. Ana Fostel & John Geanakoplos, 2012. "Tranching, CDS, and Asset Prices: How Financial Innovation Can Cause Bubbles and Crashes," American Economic Journal: Macroeconomics, American Economic Association, vol. 4(1), pages 190-225, January.
    8. Theresa Kuchler & Basit Zafar, 2019. "Personal Experiences and Expectations about Aggregate Outcomes," Journal of Finance, American Finance Association, vol. 74(5), pages 2491-2542, October.
    9. Jia, Boxiang & Goodell, John W. & Shen, Dehua, 2022. "Momentum or reversal: Which is the appropriate third factor for cryptocurrencies?," Finance Research Letters, Elsevier, vol. 45(C).
    10. Robin Greenwood & Andrei Shleifer, 2014. "Expectations of Returns and Expected Returns," The Review of Financial Studies, Society for Financial Studies, vol. 27(3), pages 714-746.
    11. Corbet, Shaen & Lucey, Brian & Yarovaya, Larisa, 2018. "Datestamping the Bitcoin and Ethereum bubbles," Finance Research Letters, Elsevier, vol. 26(C), pages 81-88.
    12. Ing-Haw Cheng & Sahil Raina & Wei Xiong, 2014. "Wall Street and the Housing Bubble," American Economic Review, American Economic Association, vol. 104(9), pages 2797-2829, September.
    13. Sensoy, Ahmet, 2019. "The inefficiency of Bitcoin revisited: A high-frequency analysis with alternative currencies," Finance Research Letters, Elsevier, vol. 28(C), pages 68-73.
    14. Grobys, Klaus & Sapkota, Niranjan, 2019. "Cryptocurrencies and momentum," Economics Letters, Elsevier, vol. 180(C), pages 6-10.
    15. Eli Ofek & Matthew Richardson, 2003. "DotCom Mania: The Rise and Fall of Internet Stock Prices," Journal of Finance, American Finance Association, vol. 58(3), pages 1113-1137, June.
    16. Daniel, Kent, et al, 1997. "Measuring Mutual Fund Performance with Characteristic-Based Benchmarks," Journal of Finance, American Finance Association, vol. 52(3), pages 1035-1058, July.
    17. Yukun Liu & Aleh Tsyvinski & Xi Wu, 2022. "Common Risk Factors in Cryptocurrency," Journal of Finance, American Finance Association, vol. 77(2), pages 1133-1177, April.
    18. Yukun Liu & Aleh Tsyvinski, 2021. "Risks and Returns of Cryptocurrency," The Review of Financial Studies, Society for Financial Studies, vol. 34(6), pages 2689-2727.
    19. Da, Zhi & Huang, Xing & Jin, Lawrence J., 2021. "Extrapolative beliefs in the cross-section: What can we learn from the crowds?," Journal of Financial Economics, Elsevier, vol. 140(1), pages 175-196.
    20. repec:bla:jfinan:v:58:y:2003:i:3:p:1113-1138 is not listed on IDEAS
    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. Matteo Benetton & Giovanni Compiani, 2024. "Investors’ Beliefs and Cryptocurrency Prices," The Review of Asset Pricing Studies, Society for Financial Studies, vol. 14(2), pages 197-236.
    2. Matteo Benetton & Giovanni Compiani, 2020. "Investors’ Beliefs and Asset Prices: A Structural Model of Cryptocurrency Demand," Working Papers 2020-107, Becker Friedman Institute for Research In Economics.
    3. Jin, Lawrence J. & Sui, Pengfei, 2022. "Asset pricing with return extrapolation," Journal of Financial Economics, Elsevier, vol. 145(2), pages 273-295.
    4. 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).
    5. Dobrynskaya, Victoria, 2024. "Is downside risk priced in cryptocurrency market?," International Review of Financial Analysis, Elsevier, vol. 91(C).
    6. ÅžimÅŸek, Alp, 2021. "The Macroeconomics of Financial Speculation," CEPR Discussion Papers 15733, C.E.P.R. Discussion Papers.
    7. Greenwood, Robin & Nagel, Stefan, 2009. "Inexperienced investors and bubbles," Journal of Financial Economics, Elsevier, vol. 93(2), pages 239-258, August.
    8. Li, Kai, 2021. "Nonlinear effect of sentiment on momentum," Journal of Economic Dynamics and Control, Elsevier, vol. 133(C).
    9. Cakici, Nusret & Zaremba, Adam, 2023. "Recency bias and the cross-section of international stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).
    10. Kogana, Shimon & Makarov, Igor & Niessnerc, Marina & Schoar, Antoinette, 2024. "Are cryptos different? Evidence from retail trading," LSE Research Online Documents on Economics 122266, London School of Economics and Political Science, LSE Library.
    11. Yang, Jen-Wei & Chiu, Shih-Yung & Yen, Kuang-Chieh, 2023. "Does the realized distribution-based measure dominate particular moments? Evidence from cryptocurrency markets," Finance Research Letters, Elsevier, vol. 51(C).
    12. Liebi, Luca J., 2022. "Is there a value premium in cryptoasset markets?," Economic Modelling, Elsevier, vol. 109(C).
    13. Florentina c{S}oiman & Guillaume Dumas & Sonia Jimenez-Garces, 2022. "The return of (I)DeFiX," Papers 2204.00251, arXiv.org.
    14. Fieberg, Christian & Liedtke, Gerrit & Zaremba, Adam, 2024. "Cryptocurrency anomalies and economic constraints," International Review of Financial Analysis, Elsevier, vol. 94(C).
    15. Magnus Dahlquist & Markus Ibert, 2024. "Equity Return Expectations and Portfolios: Evidence from Large Asset Managers," The Review of Financial Studies, Society for Financial Studies, vol. 37(6), pages 1887-1928.
    16. Cakici, Nusret & Shahzad, Syed Jawad Hussain & Będowska-Sójka, Barbara & Zaremba, Adam, 2024. "Machine learning and the cross-section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, vol. 94(C).
    17. Florentina Șoiman & Jean-Guillaume Dumas & Sonia Jimenez-Garces, 2022. "The return of (I)DeFiX [Le rendement de (I)DeFiX]," Working Papers hal-03625891, HAL.
    18. Kuchler, Theresa & Piazzesi, Monika & Ströbel, Johannes, 2022. "Housing Market Expectations," CEPR Discussion Papers 17158, C.E.P.R. Discussion Papers.
    19. Parthajit Kayal & Purnima Rohilla, 2021. "Bitcoin in the economics and finance literature: a survey," SN Business & Economics, Springer, vol. 1(7), pages 1-21, July.
    20. Milan Fičura, 2023. "Impact of size and volume on cryptocurrency momentum and reversal," FFA Working Papers 5.003, Prague University of Economics and Business, revised 05 Apr 2023.

    More about this item

    Keywords

    Bitcoin; Cryptocurrency; Extrapolation; Extrapolative beliefs;
    All these keywords.

    JEL classification:

    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets

    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:eee:finlet:v:56:y:2023:i:c:s1544612323004415. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    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.