IDEAS home Printed from https://ideas.repec.org/p/zbw/lawfin/37.html
   My bibliography  Save this paper

Option characteristics as cross-sectional predictors

Author

Listed:
  • Neuhierl, Andreas
  • Tang, Xiaoxiao
  • Varneskov, Rasmus Tangsgaard
  • Zhou, Guofu

Abstract

We provide the first comprehensive analysis of option information for pricing the cross-section of stock returns by jointly examining extensive sets of firm and option characteristics. Using portfolio sorts and high-dimensional methods, we show that certain option measures have significant predictive power, even after controlling for firm characteristics, earning a Fama-French three-factor alpha in excess of 20% per annum. Our analysis further reveals that the strongest option characteristics are associated with information about asset mispricing and future tail return realizations. Our findings are consistent with models of informed trading and limits to arbitrage.

Suggested Citation

  • Neuhierl, Andreas & Tang, Xiaoxiao & Varneskov, Rasmus Tangsgaard & Zhou, Guofu, 2022. "Option characteristics as cross-sectional predictors," LawFin Working Paper Series 37, Goethe University, Center for Advanced Studies on the Foundations of Law and Finance (LawFin).
    • Handle: RePEc:zbw:lawfin:37
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/261467/1/1810744954.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ian Dew-Becker & Stefano Giglio, 2023. "Cross-Sectional Uncertainty and the Business Cycle: Evidence from 40 Years of Options Data," American Economic Journal: Macroeconomics, American Economic Association, vol. 15(2), pages 65-96, April.
    2. Bakalli, Gaetan & Guerrier, Stéphane & Scaillet, Olivier, 2023. "A penalized two-pass regression to predict stock returns with time-varying risk premia," Journal of Econometrics, Elsevier, vol. 237(2).
    3. Yong Chen & Zhi Da & Dayong Huang, 2019. "Arbitrage Trading: The Long and the Short of It," The Review of Financial Studies, Society for Financial Studies, vol. 32(4), pages 1608-1646.
    4. Bali, Turan G. & Cakici, Nusret & Whitelaw, Robert F., 2011. "Maxing out: Stocks as lotteries and the cross-section of expected returns," Journal of Financial Economics, Elsevier, vol. 99(2), pages 427-446, February.
    5. Back, Kerry, 1993. "Asymmetric Information and Options," The Review of Financial Studies, Society for Financial Studies, vol. 6(3), pages 435-472.
    6. Amaya, Diego & Christoffersen, Peter & Jacobs, Kris & Vasquez, Aurelio, 2015. "Does realized skewness predict the cross-section of equity returns?," Journal of Financial Economics, Elsevier, vol. 118(1), pages 135-167.
    7. Connor, Gregory & Korajczyk, Robert A., 1986. "Performance measurement with the arbitrage pricing theory : A new framework for analysis," Journal of Financial Economics, Elsevier, vol. 15(3), pages 373-394, March.
    8. Peter Carr & Liuren Wu, 2003. "What Type of Process Underlies Options? A Simple Robust Test," Journal of Finance, American Finance Association, vol. 58(6), pages 2581-2610, December.
    9. Breeden, Douglas T & Litzenberger, Robert H, 1978. "Prices of State-contingent Claims Implicit in Option Prices," The Journal of Business, University of Chicago Press, vol. 51(4), pages 621-651, October.
    10. Fama, Eugene F. & French, Kenneth R., 2015. "A five-factor asset pricing model," Journal of Financial Economics, Elsevier, vol. 116(1), pages 1-22.
    11. Jean-François Bégin & Christian Dorion & Geneviève Gauthier, 2020. "Idiosyncratic Jump Risk Matters: Evidence from Equity Returns and Options," The Review of Financial Studies, Society for Financial Studies, vol. 33(1), pages 155-211.
    12. Chaieb, Ines & Langlois, Hugues & Scaillet, Olivier, 2021. "Factors and risk premia in individual international stock returns," Journal of Financial Economics, Elsevier, vol. 141(2), pages 669-692.
    13. 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.
    14. Shane A. Corwin & Paul Schultz, 2012. "A Simple Way to Estimate Bid‐Ask Spreads from Daily High and Low Prices," Journal of Finance, American Finance Association, vol. 67(2), pages 719-760, April.
    15. Martijn Cremers & Michael Halling & David Weinbaum, 2015. "Aggregate Jump and Volatility Risk in the Cross-Section of Stock Returns," Journal of Finance, American Finance Association, vol. 70(2), pages 577-614, April.
    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. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, December.
    2. Langlois, Hugues, 2020. "Measuring skewness premia," Journal of Financial Economics, Elsevier, vol. 135(2), pages 399-424.
    3. Jiang, Xue & Han, Liyan & Yin, Libo, 2019. "Can skewness predict currency excess returns?," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 628-641.
    4. 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".
    5. Jozef Barunik & Mattia Bevilacqua & Michael Ellington, 2023. "Common Firm-level Investor Fears: Evidence from Equity Options," Papers 2309.03968, arXiv.org.
    6. Nguyen, Duc Binh Benno & Prokopczuk, Marcel & Sibbertsen, Philipp, 2020. "The memory of stock return volatility: Asset pricing implications," Journal of Financial Markets, Elsevier, vol. 47(C).
    7. Lu, Zhongjin & Murray, Scott, 2019. "Bear beta," Journal of Financial Economics, Elsevier, vol. 131(3), pages 736-760.
    8. Hanauer, Matthias X. & Lesnevski, Pavel & Smajlbegovic, Esad, 2023. "Surprise in short interest," Journal of Financial Markets, Elsevier, vol. 65(C).
    9. Felix Reichenbach & Martin Walther, 2023. "Financial recommendations on Reddit, stock returns and cumulative prospect theory," Digital Finance, Springer, vol. 5(2), pages 421-448, June.
    10. 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.
    11. Gkionis, Konstantinos & Kostakis, Alexandros & Skiadopoulos, George & Stilger, Przemyslaw S., 2021. "Positive stock information in out-of-the-money option prices," Journal of Banking & Finance, Elsevier, vol. 128(C).
    12. Li, Xindan & Subrahmanyam, Avanidhar & Yang, Xuewei, 2018. "Can financial innovation succeed by catering to behavioral preferences? Evidence from a callable options market," Journal of Financial Economics, Elsevier, vol. 128(1), pages 38-65.
    13. Jie Cao & Amit Goyal & Xiao Xiao & Xintong Zhan, 2023. "Implied Volatility Changes and Corporate Bond Returns," Management Science, INFORMS, vol. 69(3), pages 1375-1397, March.
    14. Weber, Martin & Jacobs, Heiko & Regele, Tobias, 2015. "Expected Skewness and Momentum," CEPR Discussion Papers 10601, C.E.P.R. Discussion Papers.
    15. Marinela Adriana Finta & José Renato Haas Ornelas, 2018. "Commodity Return Predictability: evidence from implied variance, skewness and their risk premia and their risk premia," Working Papers Series 479, Central Bank of Brazil, Research Department.
    16. Yun Xiang & Shijie Deng, 2025. "Long-range dependence and asset return anomaly," Annals of Operations Research, Springer, vol. 346(1), pages 369-391, March.
    17. Gilstrap, Collin & Petkevich, Alex & Teterin, Pavel, 2020. "Striking up with the in crowd: When option markets and insiders agree," Journal of Banking & Finance, Elsevier, vol. 120(C).
    18. Hollstein, Fabian & Nguyen, Duc Binh Benno & Prokopczuk, Marcel, 2019. "Asset prices and “the devil(s) you know”," Journal of Banking & Finance, Elsevier, vol. 105(C), pages 20-35.
    19. Ruenzi, Stefan & Ungeheuer, Michael & Weigert, Florian, 2020. "Joint Extreme events in equity returns and liquidity and their cross-sectional pricing implications," Journal of Banking & Finance, Elsevier, vol. 115(C).
    20. Finta, Marinela Adriana & Ornelas, José Renato Haas, 2022. "Commodity return predictability: Evidence from implied variance, skewness, and their risk premia☆☆," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 79(C).

    More about this item

    Keywords

    Asset Pricing; Factor Models; High-dimensional Methods; Option Characteristics;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:zbw:lawfin:37. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/hoffmde.html .

    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.