IDEAS home Printed from https://ideas.repec.org/a/gam/jrisks/v10y2022i10p190-d931809.html
   My bibliography  Save this article

Modeling Momentum and Reversals

Author

Listed:
  • Harvey J. Stein

    (Labs Group, Two Sigma, New York, NY 10013, USA
    Department of Mathematics, Columbia University, New York, NY 10027, USA)

  • Jacob Pozharny

    (Bridgeway Capital Management, Houston, Texas 77046, USA)

Abstract

Stock prices are well known to exhibit behaviors that are difficult to model mathematically. Individual stocks are observed to exhibit short term price reversals and long term momentum, while their industries only exhibit momentum. Here we show that individual stocks can be modeled by simple mean reverting processes in such a way that these behaviors are captured, the model is arbitrage free, and market informational efficiency is preserved. Simulation shows that in such a market, when mean reversion is sufficiently high, strategies which use reversals would substantially outperform buy and hold strategies.

Suggested Citation

  • Harvey J. Stein & Jacob Pozharny, 2022. "Modeling Momentum and Reversals," Risks, MDPI, vol. 10(10), pages 1-10, October.
    • Handle: RePEc:gam:jrisks:v:10:y:2022:i:10:p:190-:d:931809
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-9091/10/10/190/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-9091/10/10/190/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kent Daniel & David Hirshleifer & Avanidhar Subrahmanyam, 1998. "Investor Psychology and Security Market Under- and Overreactions," Journal of Finance, American Finance Association, vol. 53(6), pages 1839-1885, December.
    2. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    3. Charles-Olivier Amédée-Manesme & Fabrice Barthélémy & Philippe Bertrand & Jean-Luc Prigent, 2019. "Mixed-asset portfolio allocation under mean-reverting asset returns," Annals of Operations Research, Springer, vol. 281(1), pages 65-98, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Giner, Javier & Zakamulin, Valeriy, 2023. "A regime-switching model of stock returns with momentum and mean reversion," Economic Modelling, Elsevier, vol. 122(C).

    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. John H. Cochrane, 1999. "New facts in finance," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 23(Q III), pages 36-58.
    2. Corgnet, Brice & DeSantis, Mark & Porter, David, 2020. "The distribution of information and the price efficiency of markets," Journal of Economic Dynamics and Control, Elsevier, vol. 110(C).
    3. Mu-En Wu & Wei-Ho Chung, 2019. "Empirical Evaluations on Momentum Effects of Taiwan Index Futures via Stop-Loss and Stop-Profit Mechanisms," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(02), pages 629-648, March.
    4. Navaz Naghavi & Muhammad Shujaat Mubarik & Devinder Kaur, 2018. "Financial Liberalization And Stock Market Efficiency: Measuring The Threshold Effects Of Governance," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 13(04), pages 1-24, December.
    5. Tobias Wiest, 2023. "Momentum: what do we know 30 years after Jegadeesh and Titman’s seminal paper?," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 37(1), pages 95-114, March.
    6. Robert J. Shiller, 2003. "From Efficient Markets Theory to Behavioral Finance," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 83-104, Winter.
    7. Guo, Xu & McAleer, Michael & Wong, Wing-Keung & Zhu, Lixing, 2017. "A Bayesian approach to excess volatility, short-term underreaction and long-term overreaction during financial crises," The North American Journal of Economics and Finance, Elsevier, vol. 42(C), pages 346-358.
    8. Fernando Rubio, 2005. "Estrategias Cuantitativas De Valor Y Retornos Por Accion De Largo," Finance 0503029, University Library of Munich, Germany.
    9. Sapienza, Paola & Polk, Christopher, 2003. "The Real Effects of Investor Sentiment," CEPR Discussion Papers 3826, C.E.P.R. Discussion Papers.
    10. Lim, Kian-Ping & Kim, Jae H., 2011. "Trade openness and the informational efficiency of emerging stock markets," Economic Modelling, Elsevier, vol. 28(5), pages 2228-2238, September.
    11. Schwert, G. William, 2003. "Anomalies and market efficiency," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, edition 1, volume 1, chapter 15, pages 939-974, Elsevier.
    12. Corsetti, Giancarlo & Lafarguette, Romain & Mehl, Arnaud, 2019. "Fast trading and the virtue of entropy: evidence from the foreign exchange market," Working Paper Series 2300, European Central Bank.
    13. Tswei, Keshin, 2013. "Is transaction price more value relevant compared to accounting information? An investigation of a time-series approach," Pacific-Basin Finance Journal, Elsevier, vol. 21(1), pages 1062-1078.
    14. Lu Zhang, 2017. "The Investment CAPM," European Financial Management, European Financial Management Association, vol. 23(4), pages 545-603, September.
    15. Raza, Ahmad & Marshall, Ben R. & Visaltanachoti, Nuttawat, 2014. "Is there momentum or reversal in weekly currency returns?," Journal of International Money and Finance, Elsevier, vol. 45(C), pages 38-60.
    16. Joao Martines-Filho, 2006. "The Performance of Agricultural Market Advisory Services in Corn and Soybeans," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 88(1), pages 162-181.
    17. Utku Uygur & Oktay Taş, 2014. "The impacts of investor sentiment on returns and conditional volatility of international stock markets," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(3), pages 1165-1179, May.
    18. Bryan Fong, 2021. "Analysing the behavioural finance impact of 'fake news' phenomena on financial markets: a representative agent model and empirical validation," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-30, December.
    19. Ramiah, Vikash & Xu, Xiaoming & Moosa, Imad A., 2015. "Neoclassical finance, behavioral finance and noise traders: A review and assessment of the literature," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 89-100.
    20. Corgnet, Brice & DeSantis, Mark & Porter, David, 2021. "Information aggregation and the cognitive make-up of market participants," European Economic Review, Elsevier, vol. 133(C).

    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:jrisks:v:10:y:2022:i:10:p:190-:d:931809. 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.