IDEAS home Printed from https://ideas.repec.org/a/wly/jfutmk/v45y2025i10p1471-1490.html
   My bibliography  Save this article

Predicting Stock Jumps and Crashes Using Options

Author

Listed:
  • Panayiotis C. Andreou
  • Chulwoo Han
  • Nan Li

Abstract

This paper investigates the informativeness of option‐implied volatility and Greeks in forecasting extreme stock returns. Using a large data set of U.S. stocks and options from 1996 to 2022 and employing Light Gradient‐Boosting Machine as a machine learning algorithm, we show that option characteristics, particularly implied volatility and delta, are strong predictors of extreme returns. The long–short portfolio utilizing option variables significantly outperforms a benchmark using only stock characteristics, suggesting that options provide information beyond what can be inferred from stock characteristics. Put options are revealed to be more informative than call options, and crashes are easier to predict than jumps.

Suggested Citation

  • Panayiotis C. Andreou & Chulwoo Han & Nan Li, 2025. "Predicting Stock Jumps and Crashes Using Options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 45(10), pages 1471-1490, October.
    • Handle: RePEc:wly:jfutmk:v:45:y:2025:i:10:p:1471-1490
    DOI: 10.1002/fut.22609
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/fut.22609
    Download Restriction: no
    File URL: https://libkey.io/10.1002/fut.22609?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
    ---><---

    References listed on IDEAS

    as
    1. Tim Bollerslev & George Tauchen & Hao Zhou, 2009. "Expected Stock Returns and Variance Risk Premia," The Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4463-4492, November.
    2. Thompson, Samuel B., 2011. "Simple formulas for standard errors that cluster by both firm and time," Journal of Financial Economics, Elsevier, vol. 99(1), pages 1-10, January.
    3. Bollerslev, Tim & Gibson, Michael & Zhou, Hao, 2011. "Dynamic estimation of volatility risk premia and investor risk aversion from option-implied and realized volatilities," Journal of Econometrics, Elsevier, vol. 160(1), pages 235-245, January.
    4. Chen, Joseph & Hong, Harrison & Stein, Jeremy C., 2001. "Forecasting crashes: trading volume, past returns, and conditional skewness in stock prices," Journal of Financial Economics, Elsevier, vol. 61(3), pages 345-381, September.
    5. Holger Claessen & Stefan Mittnik, 2002. "Forecasting stock market volatility and the informational efficiency of the DAX-index options market," The European Journal of Finance, Taylor & Francis Journals, vol. 8(3), pages 302-321.
    6. Jackwerth, Jens Carsten & Rubinstein, Mark, 1996. "Recovering Probability Distributions from Option Prices," Journal of Finance, American Finance Association, vol. 51(5), pages 1611-1632, December.
    7. Yan, Shu, 2011. "Jump risk, stock returns, and slope of implied volatility smile," Journal of Financial Economics, Elsevier, vol. 99(1), pages 216-233, January.
    8. Chiras, Donald P. & Manaster, Steven, 1978. "The information content of option prices and a test of market efficiency," Journal of Financial Economics, Elsevier, vol. 6(2-3), pages 213-234.
    9. Conrad, Jennifer & Kapadia, Nishad & Xing, Yuhang, 2014. "Death and jackpot: Why do individual investors hold overpriced stocks?," Journal of Financial Economics, Elsevier, vol. 113(3), pages 455-475.
    10. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
    11. James S. Doran & David R. Peterson & Brian C. Tarrant, 2007. "Is there information in the volatility skew?," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 27(10), pages 921-959, October.
    12. Zhenxiong Li & Marwan Izzeldin & Xingzhi Yao, 2020. "Return predictability of variance differences: A fractionally cointegrated approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(7), pages 1072-1089, July.
    13. Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," Review of Finance, European Finance Association, vol. 33(5), pages 2223-2273.
    14. Bates, David S, 1991. "The Crash of '87: Was It Expected? The Evidence from Options Markets," Journal of Finance, American Finance Association, vol. 46(3), pages 1009-1044, July.
    15. John M. Griffin & Nicholas Hirschey & Samuel Kruger, 2023. "Do Municipal Bond Dealers Give Their Customers “Fair and Reasonable” Pricing?," Journal of Finance, American Finance Association, vol. 78(2), pages 887-934, April.
    16. Jang, Jeewon & Kang, Jangkoo, 2019. "Probability of price crashes, rational speculative bubbles, and the cross-section of stock returns," Journal of Financial Economics, Elsevier, vol. 132(1), pages 222-247.
    17. Xing, Yuhang & Zhang, Xiaoyan & Zhao, Rui, 2010. "What Does the Individual Option Volatility Smirk Tell Us About Future Equity Returns?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(3), pages 641-662, June.
    18. Itamar Drechsler & Amir Yaron, 2011. "What's Vol Got to Do with It," The Review of Financial Studies, Society for Financial Studies, vol. 24(1), pages 1-45.
    19. Cremers, Martijn & Weinbaum, David, 2010. "Deviations from Put-Call Parity and Stock Return Predictability," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 45(2), pages 335-367, April.
    20. repec:bla:jfinan:v:59:y:2004:i:2:p:831-868 is not listed on IDEAS
    21. Cox, John C. & Ross, Stephen A. & Rubinstein, Mark, 1979. "Option pricing: A simplified approach," Journal of Financial Economics, Elsevier, vol. 7(3), pages 229-263, September.
    22. Han, Chulwoo & He, Zhaodong & Toh, Alenson Jun Wei, 2023. "Pairs trading via unsupervised learning," European Journal of Operational Research, Elsevier, vol. 307(2), pages 929-947.
    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. Christoffersen, Peter & Jacobs, Kris & Chang, Bo Young, 2013. "Forecasting with Option-Implied Information," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 581-656, Elsevier.
    2. Elyas Elyasiani & Luca Gambarelli & Silvia Muzzioli, 2015. "Towards a skewness index for the Italian stock market," Department of Economics 0064, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
    3. Guo, Hui & Qiu, Buhui, 2014. "Options-implied variance and future stock returns," Journal of Banking & Finance, Elsevier, vol. 44(C), pages 93-113.
    4. Jeffrey L. Callen & Matthew R. Lyle, 2020. "The term structure of implied costs of equity capital," Review of Accounting Studies, Springer, vol. 25(1), pages 342-404, March.
    5. Sirio Aramonte & Mohammad R. Jahan-Parvar & Samuel Rosen & John W. Schindler, 2022. "Firm-Specific Risk-Neutral Distributions with Options and CDS," Management Science, INFORMS, vol. 68(9), pages 7018-7033, September.
    6. Yue, Tian & Gehricke, Sebastian A. & Zhang, Jin E. & Pan, Zheyao, 2021. "The implied volatility smirk in the Chinese equity options market," Pacific-Basin Finance Journal, Elsevier, vol. 69(C).
    7. Chin‐Ho Chen, 2021. "Investor sentiment, misreaction, and the skewness‐return relationship," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(9), pages 1427-1455, September.
    8. Lin, Tse-Chun & Lu, Xiaolong, 2015. "Why do options prices predict stock returns? Evidence from analyst tipping," Journal of Banking & Finance, Elsevier, vol. 52(C), pages 17-28.
    9. Przemysław S. Stilger & Alexandros Kostakis & Ser-Huang Poon, 2017. "What Does Risk-Neutral Skewness Tell Us About Future Stock Returns?," Management Science, INFORMS, vol. 63(6), pages 1814-1834, June.
    10. Casas Villalba, Maria Isabel & Mao, Xiuping & Lopes Moreira da Veiga, María Helena, 2020. "Adaptative predictability of stock market returns," DES - Working Papers. Statistics and Econometrics. WS 31648, Universidad Carlos III de Madrid. Departamento de Estadística.
    11. Michael Lemmon & Sophie Xiaoyan Ni, 2014. "Differences in Trading and Pricing Between Stock and Index Options," Management Science, INFORMS, vol. 60(8), pages 1985-2001, August.
    12. Lambrinoudakis, Costas & Skiadopoulos, George & Gkionis, Konstantinos, 2019. "Capital structure and financial flexibility: Expectations of future shocks," Journal of Banking & Finance, Elsevier, vol. 104(C), pages 1-18.
    13. Wenxin Guo & Dehong Liu & Carl R. Chen & Peter Lung, 2025. "The Dynamics of Option Volatility Smirk and Option Returns Predictability: Evidence From Chinese SSE50 ETF Options," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 45(7), pages 705-731, July.
    14. Buss, Adrian & Vilkov, Grigory & ,, 2018. "Expected Correlation and Future Market Returns," CEPR Discussion Papers 12760, C.E.P.R. Discussion Papers.
    15. Silvia Muzzioli, 2013. "The Information Content of Option-Based Forecasts of Volatility: Evidence from the Italian Stock Market," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 3(01), pages 1-46.
    16. Seo, Sung Won & Kim, Jun Sik, 2015. "The information content of option-implied information for volatility forecasting with investor sentiment," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 106-120.
    17. Sévi, Benoît, 2013. "An empirical analysis of the downside risk-return trade-off at daily frequency," Economic Modelling, Elsevier, vol. 31(C), pages 189-197.
    18. Yoon, Sun-Joong, 2017. "Time-varying risk aversion and return predictability," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 327-339.
    19. Jungah Yoon & Xinfeng Ruan & Jin E. Zhang, 2022. "VIX option‐implied volatility slope and VIX futures returns," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 42(6), pages 1002-1038, June.
    20. Fabian Hollstein & Marcel Prokopczuk & Björn Tharann & Chardin Wese Simen, 2019. "Predicting the equity market with option-implied variables," The European Journal of Finance, Taylor & Francis Journals, vol. 25(10), pages 937-965, July.

    More about this item

    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:wly:jfutmk:v:45:y:2025:i:10:p:1471-1490. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/0270-7314/ .

    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.