IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v16y2023i5p270-d1145938.html
   My bibliography  Save this article

The Efficiency of Weekly Option Prices around Earnings Announcements

Author

Listed:
  • Jonathan A. Milian

    (School of Accounting, Florida International University, Miami, FL 33199, USA)

Abstract

This study examines the efficiency of weekly option prices around firms’ earnings announcements. With most of the largest firms now having options that expire on a weekly basis, option traders can hedge or speculate on earnings news using options that expire very close to a firm’s earnings announcement date. For earnings announcements near an options expiration date, one can estimate a firm’s expected stock price move in response to its earnings news (i.e., its option implied earnings announcement move) as the price of its at-the-money straddle as a proportion of its stock price. This study tests whether differences between historical earnings announcement moves and option implied earnings announcement moves predict straddle returns. Through the analysis of portfolio returns and Fama–MacBeth regressions, this study finds that straddle returns are significantly higher (lower) when the historical earnings announcement move is high (low) relative to the option implied earnings announcement move. In contrast to prior research, this study does not find an association between straddle returns and historical volatility, historical earnings announcement volatility, implied volatility, or the difference between historical volatility and implied volatility. Overall, this study suggests that weekly straddle prices around earnings announcements are not optimally efficient.

Suggested Citation

  • Jonathan A. Milian, 2023. "The Efficiency of Weekly Option Prices around Earnings Announcements," JRFM, MDPI, vol. 16(5), pages 1-14, May.
    • Handle: RePEc:gam:jjrfmx:v:16:y:2023:i:5:p:270-:d:1145938
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/16/5/270/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1911-8074/16/5/270/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Chung, Sung Gon & Louis, Henock, 2017. "Earnings announcements and option returns," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 220-235.
    2. Sudipta Basu & Truong Xuan Duong & Stanimir Markov & Eng-Joo Tan, 2013. "How Important are Earnings Announcements as an Information Source?," European Accounting Review, Taylor & Francis Journals, vol. 22(2), pages 221-256, June.
    3. Gao, Chao & Xing, Yuhang & Zhang, Xiaoyan, 2018. "Anticipating Uncertainty: Straddles around Earnings Announcements," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(6), pages 2587-2617, December.
    4. Torben G. Andersen & Nicola Fusari & Viktor Todorov, 2017. "Short-Term Market Risks Implied by Weekly Options," Journal of Finance, American Finance Association, vol. 72(3), pages 1335-1386, June.
    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. Crego, Julio & Gider, Jasmin, 2024. "The dynamic informativeness of scheduled news," Other publications TiSEM d4538ed2-3aeb-4259-b1f1-2, Tilburg University, School of Economics and Management.
    2. Juan M. Londono & Mehrdad Samadi, 2023. "The Price of Macroeconomic Uncertainty: Evidence from Daily Options," International Finance Discussion Papers 1376, Board of Governors of the Federal Reserve System (U.S.).
    3. Karel Janda, 2019. "Earnings Stability and Peer Company Selection for Multiple Based Indirect Valuation," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 69(1), pages 37-75, February.
    4. H. Peter Boswijk & Roger J. A. Laeven & Evgenii Vladimirov, 2022. "Estimating Option Pricing Models Using a Characteristic Function-Based Linear State Space Representation," Papers 2210.06217, arXiv.org.
    5. Diego Amaya & Jean-François Bégin & Geneviève Gauthier, 2022. "The Informational Content of High-Frequency Option Prices," Management Science, INFORMS, vol. 68(3), pages 2166-2201, March.
    6. Dew-Becker, Ian & Giglio, Stefano & Kelly, Bryan, 2021. "Hedging macroeconomic and financial uncertainty and volatility," Journal of Financial Economics, Elsevier, vol. 142(1), pages 23-45.
    7. Li, Wanyun, 2022. "Disclosure of internal control material weaknesses and optimism in analyst earnings forecasts," International Journal of Accounting Information Systems, Elsevier, vol. 44(C).
    8. Hamed Ghanbari & Michael Oancea & Stylianos Perrakis, 2021. "Shedding light on a dark matter: Jump diffusion and option‐implied investor preferences," European Financial Management, European Financial Management Association, vol. 27(2), pages 244-286, March.
    9. Cascino, Stefano & Clatworthy, Mark A. & Osma, Beatriz Garcia & Gassen, Joachim & Imam, Shahed, 2021. "The usefulness of financial accounting information: evidence from the field," LSE Research Online Documents on Economics 107569, London School of Economics and Political Science, LSE Library.
    10. Amengual, Dante & Xiu, Dacheng, 2018. "Resolution of policy uncertainty and sudden declines in volatility," Journal of Econometrics, Elsevier, vol. 203(2), pages 297-315.
    11. Ramachandran, Lakshmi Shankar & Tayal, Jitendra, 2021. "Mispricing, short-sale constraints, and the cross-section of option returns," Journal of Financial Economics, Elsevier, vol. 141(1), pages 297-321.
    12. Federico M. Bandi & Aleksey Kolokolov & Davide Pirino & Roberto Renòo, 2020. "Zeros," Management Science, INFORMS, vol. 66(8), pages 3466-3479, August.
    13. Hui Chen & Antoine Didisheim & Simon Scheidegger, 2021. "Deep Structural Estimation:With an Application to Option Pricing," Cahiers de Recherches Economiques du Département d'économie 21.14, Université de Lausanne, Faculté des HEC, Département d’économie.
    14. Darsh Kachhara & John K. E Markin & Astha Singh, 2023. "Option Smile Volatility and Implied Probabilities: Implications of Concavity in IV Curves," Papers 2307.15718, arXiv.org, revised Nov 2023.
    15. Wan, Xiangwei & Yang, Nian, 2021. "Hermite expansion of transition densities and European option prices for multivariate diffusions with jumps," Journal of Economic Dynamics and Control, Elsevier, vol. 125(C).
    16. Miguel Duro & Jonas Heese & Gaizka Ormazabal, 2019. "The effect of enforcement transparency: Evidence from SEC comment-letter reviews," Review of Accounting Studies, Springer, vol. 24(3), pages 780-823, September.
    17. Ging-Ginq Pan & Yung-Ming Shiu & Tu-Cheng Wu, 2019. "Is trading in the shortest-term index options profitable?," Review of Derivatives Research, Springer, vol. 22(1), pages 169-201, April.
    18. David Weinbaum & Andrew Fodor & Dmitriy Muravyev & Martijn Cremers, 2023. "Option Trading Activity, News Releases, and Stock Return Predictability," Management Science, INFORMS, vol. 69(8), pages 4810-4827, August.
    19. Shuai Shao & Robert Stoumbos & X. Frank Zhang, 2021. "The power of firm fundamental information in explaining stock returns," Review of Accounting Studies, Springer, vol. 26(4), pages 1249-1289, December.
    20. Siddiqi, Hammad, 2020. "Resource allocation in the brain and the Capital Asset Pricing Model," MPRA Paper 100250, University Library of Munich, Germany.

    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:gam:jjrfmx:v:16:y:2023:i:5:p:270-:d:1145938. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.