IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2604.01431.html

Do Prediction Markets Forecast Cryptocurrency Volatility? Evidence from Kalshi Macro Contracts

Author

Listed:
  • Hardhik Mohanty
  • Bhaskar Krishnamachari

Abstract

Daily probability changes in Kalshi macro prediction markets forecast cryptocurrency realized volatility through two distinct channels. The monetary policy channel, measured by Fed rate repricing on KXFED contracts, predicts Bitcoin volatility in sample with t = 3.63 and p

Suggested Citation

  • Hardhik Mohanty & Bhaskar Krishnamachari, 2026. "Do Prediction Markets Forecast Cryptocurrency Volatility? Evidence from Kalshi Macro Contracts," Papers 2604.01431, arXiv.org.
    • Handle: RePEc:arx:papers:2604.01431
    as

    Download full text from publisher

    File URL: https://arxiv.org/pdf/2604.01431
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ben Omrane, Walid & Dabbou, Halim & Saadi, Samir & Savaser, Tanseli & Sebai, Saber, 2025. "Exploring volatility reactions in cryptocurrency markets using intraday macroeconomic news analysis," International Review of Economics & Finance, Elsevier, vol. 103(C).
    2. Katsiampa, Paraskevi, 2017. "Volatility estimation for Bitcoin: A comparison of GARCH models," Economics Letters, Elsevier, vol. 158(C), pages 3-6.
    3. Fang, Tong & Su, Zhi & Yin, Libo, 2020. "Economic fundamentals or investor perceptions? The role of uncertainty in predicting long-term cryptocurrency volatility," International Review of Financial Analysis, Elsevier, vol. 71(C).
    4. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    5. Manski, Charles F., 2006. "Interpreting the predictions of prediction markets," Economics Letters, Elsevier, vol. 91(3), pages 425-429, June.
    6. Emi Nakamura & Jón Steinsson, 2018. "High-Frequency Identification of Monetary Non-Neutrality: The Information Effect," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 133(3), pages 1283-1330.
    7. 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.
    8. Walther, Thomas & Klein, Tony & Bouri, Elie, 2019. "Exogenous drivers of Bitcoin and Cryptocurrency volatility – A mixed data sampling approach to forecasting," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    9. Demir, Ender & Gozgor, Giray & Lau, Chi Keung Marco & Vigne, Samuel A., 2018. "Does economic policy uncertainty predict the Bitcoin returns? An empirical investigation," Finance Research Letters, Elsevier, vol. 26(C), pages 145-149.
    10. Ben S. Bernanke & Kenneth N. Kuttner, 2005. "What Explains the Stock Market's Reaction to Federal Reserve Policy?," Journal of Finance, American Finance Association, vol. 60(3), pages 1221-1257, June.
    11. Alan Moreira & Tyler Muir, 2017. "Volatility-Managed Portfolios," Journal of Finance, American Finance Association, vol. 72(4), pages 1611-1644, August.
    12. Refet S. Gürkaynak & Brian Sack & Eric Swanson, 2005. "The Sensitivity of Long-Term Interest Rates to Economic News: Evidence and Implications for Macroeconomic Models," American Economic Review, American Economic Association, vol. 95(1), pages 425-436, March.
    13. Corbet, Shaen & Meegan, Andrew & Larkin, Charles & Lucey, Brian & Yarovaya, Larisa, 2018. "Exploring the dynamic relationships between cryptocurrencies and other financial assets," Economics Letters, Elsevier, vol. 165(C), pages 28-34.
    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. Yin, Libo & Nie, Jing & Han, Liyan, 2021. "Understanding cryptocurrency volatility: The role of oil market shocks," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 233-253.
    2. Lyócsa, Štefan & Molnár, Peter & Plíhal, Tomáš & Širaňová, Mária, 2020. "Impact of macroeconomic news, regulation and hacking exchange markets on the volatility of bitcoin," Journal of Economic Dynamics and Control, Elsevier, vol. 119(C).
    3. Guo, Xiaochun & Guo, Kun & Wang, Shouyang, 2026. "The Crypto Risk Composite Index (CCRI)-advancing risk management in the digital asset space," International Review of Financial Analysis, Elsevier, vol. 113(C).
    4. Aurelio F. Bariviera & Ignasi Merediz‐Solà, 2021. "Where Do We Stand In Cryptocurrencies Economic Research? A Survey Based On Hybrid Analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 377-407, April.
    5. Nektarios Aslanidis & Aurelio F. Bariviera & 'Oscar G. L'opez, 2021. "The link between Bitcoin and Google Trends attention," Papers 2106.07104, arXiv.org.
    6. Lucey, Brian M. & Vigne, Samuel A. & Yarovaya, Larisa & Wang, Yizhi, 2022. "The cryptocurrency uncertainty index," Finance Research Letters, Elsevier, vol. 45(C).
    7. Ahmed, Mohamed Shaker & El-Masry, Ahmed A. & Al-Maghyereh, Aktham I. & Kumar, Satish, 2024. "Cryptocurrency volatility: A review, synthesis, and research agenda," Research in International Business and Finance, Elsevier, vol. 71(C).
    8. Aslanidis, Nektarios & Bariviera, Aurelio F. & López, Óscar G., 2022. "The link between cryptocurrencies and Google Trends attention," Finance Research Letters, Elsevier, vol. 47(PA).
    9. Clark, Ephraim & Lahiani, Amine & Mefteh-Wali, Salma, 2023. "Cryptocurrency return predictability: What is the role of the environment?," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    10. Bevilacqua, Mattia & Ellington, Michael & Hizmeri, Rodrigo, 2026. "Testing for differences in high-frequency network connectedness from variance decompositions," Journal of Econometrics, Elsevier, vol. 256(PB).
    11. Zhang, Yue-Jun & Bouri, Elie & Gupta, Rangan & Ma, Shu-Jiao, 2021. "Risk spillover between Bitcoin and conventional financial markets: An expectile-based approach," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    12. Yang Zhou & Chi Xie & Gang-Jin Wang & Jue Gong & You Zhu, 2025. "Forecasting cryptocurrency volatility: a novel framework based on the evolving multiscale graph neural network," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-52, December.
    13. Cynthia Weiyi Cai & Rui Xue & Bi Zhou, 2023. "Cryptocurrency puzzles: a comprehensive review and re-introduction," Journal of Accounting Literature, Emerald Group Publishing Limited, vol. 46(1), pages 26-50, June.
    14. Aras, Serkan & Özdemir, Mehmet Ozan & Çılgın, Cihan, 2025. "Uncertainty or investor attention: Which has more impact on Bitcoin volatility?," Research in International Business and Finance, Elsevier, vol. 77(PB).
    15. Chen, Kairan & Granville, Brigitte & Matousek, Roman, 2026. "Decoding central bank communications with large language models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 109(C).
    16. Ehrmann, Michael & Gnan, Phillipp & Rieder, Kilian, 2023. "Central Bank Communication by ??? The Economics of Public Policy Leaks," CEPR Discussion Papers 18152, Centre for Economic Policy Research.
    17. Benchora, Inessa & Leroy, Aurélien & Raffestin, Louis, 2025. "Is monetary policy transmission green?," Economic Modelling, Elsevier, vol. 144(C).
    18. Nina Boyarchenko & Valentin Haddad & Matthew Plosser, 2016. "The Federal Reserve and market confidence," Staff Reports 773, Federal Reserve Bank of New York.
    19. Klein, Tony & Pham Thu, Hien & Walther, Thomas, 2018. "Bitcoin is not the New Gold – A comparison of volatility, correlation, and portfolio performance," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 105-116.
    20. Olivier Wang, 2025. "Banks, Low Interest Rates, and Monetary Policy Transmission," Journal of Finance, American Finance Association, vol. 80(3), pages 1379-1416, June.

    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:2604.01431. 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: https://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.