IDEAS home Printed from https://ideas.repec.org/p/baf/cbafwp/cbafwp1888.html
   My bibliography  Save this paper

Arbitrage Risk and Investor Sentiment as Causes of Persistent Mispricing: the European Evidence

Author

Listed:
  • Massimo Guidolin
  • Andrea Ricci

Abstract

We investigate the relationship between risk-adjusted returns, arbitrage risk and arbitrage asymmetry, and investor sentiment in the European stock market. Under the assumption that idiosyncratic volatility (IVOL) causes arbitrage risk, we analyze the effects of IVOL on the-abnormal returns of the Euro Stoxx 50 large cap constituents. After classifying the stocks in two mispricing categories, we uncover evidence of arbitrage risk especially in the overpriced group: the highest IVOL overpriced portfolio is the most overpriced, which implies persistent subsequent risk-adjusted returns that slowly revert to zero. When the estimation is performed afresh separating the high- from the low-sentiment periods and controlling for macroeconomic conditions, we find evidence of a negative relation between investor sentiment and IVOL effects, which is yet more pronounced for the highest arbitrage-risk stocks, which is consistent with pure, psychological biases strongly affecting the impact of arbitrage risk on the speed of correction of mispricing.

Suggested Citation

  • Massimo Guidolin & Andrea Ricci, 2018. "Arbitrage Risk and Investor Sentiment as Causes of Persistent Mispricing: the European Evidence," BAFFI CAREFIN Working Papers 1888, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
    • Handle: RePEc:baf:cbafwp:cbafwp1888
    as

    Download full text from publisher

    File URL: https://repec.unibocconi.it/baffic/baf/papers/cbafwp1888.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Eugene F. Fama & Kenneth R. French, 2001. "Disappearing Dividends: Changing Firm Characteristics Or Lower Propensity To Pay?," Journal of Applied Corporate Finance, Morgan Stanley, vol. 14(1), pages 67-79, March.
    2. Baker, Malcolm & Stein, Jeremy C., 2004. "Market liquidity as a sentiment indicator," Journal of Financial Markets, Elsevier, vol. 7(3), pages 271-299, June.
    3. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    4. Barberis, Nicholas & Thaler, Richard, 2003. "A survey of behavioral finance," 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 18, pages 1053-1128, Elsevier.
    5. Eugene F. Fama & Kenneth R. French, 2008. "Dissecting Anomalies," Journal of Finance, American Finance Association, vol. 63(4), pages 1653-1678, August.
    6. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    7. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    8. Te‐Feng Chen & Lei Sun & K. C. John Wei & Feixue Xie, 2018. "The profitability effect: Insights from international equity markets," European Financial Management, European Financial Management Association, vol. 24(4), pages 545-580, September.
    9. Michael J. Cooper & Huseyin Gulen & Michael J. Schill, 2008. "Asset Growth and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 63(4), pages 1609-1651, August.
    10. De Long, J Bradford & Shleifer, Andrei & Summers, Lawrence H & Waldmann, Robert J, 1991. "The Survival of Noise Traders in Financial Markets," The Journal of Business, University of Chicago Press, vol. 64(1), pages 1-19, January.
    11. Andrew Ang & Robert J. Hodrick & Yuhang Xing & Xiaoyan Zhang, 2006. "The Cross‐Section of Volatility and Expected Returns," Journal of Finance, American Finance Association, vol. 61(1), pages 259-299, February.
    12. John Capstaff & Jonathan Fletcher, 2011. "Long Term Performance and Choice of SEO Method by UK Firms," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 38(9-10), pages 1262-1289, November.
    13. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    14. repec:bla:jfinan:v:59:y:2004:i:3:p:1125-1165 is not listed on IDEAS
    15. Brad M. Barber & Terrance Odean, 2008. "All That Glitters: The Effect of Attention and News on the Buying Behavior of Individual and Institutional Investors," The Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 785-818, April.
    16. Cao, Jie & Han, Bing, 2016. "Idiosyncratic risk, costly arbitrage, and the cross-section of stock returns," Journal of Banking & Finance, Elsevier, vol. 73(C), pages 1-15.
    17. Blume, Lawrence & Easley, David, 1992. "Evolution and market behavior," Journal of Economic Theory, Elsevier, vol. 58(1), pages 9-40, October.
    18. Fama, Eugene F. & French, Kenneth R., 2006. "Profitability, investment and average returns," Journal of Financial Economics, Elsevier, vol. 82(3), pages 491-518, December.
    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. Guidolin, Massimo & Ricci, Andrea, 2020. "Arbitrage risk and a sentiment as causes of persistent mispricing: The European evidence," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 1-11.
    2. Khasawneh, Maher & McMillan, David G. & Kambouroudis, Dimos, 2024. "Left-tail risk and UK stock return predictability: Underreaction, overreaction, and arbitrage difficulties," International Review of Financial Analysis, Elsevier, vol. 95(PA).
    3. David Hirshleife, 2015. "Behavioral Finance," Annual Review of Financial Economics, Annual Reviews, vol. 7(1), pages 133-159, December.
    4. Jacobs, Heiko, 2015. "What explains the dynamics of 100 anomalies?," Journal of Banking & Finance, Elsevier, vol. 57(C), pages 65-85.
    5. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, January.
    6. Malagon, Juliana & Moreno, David & Rodríguez, Rosa, 2015. "The idiosyncratic volatility anomaly: Corporate investment or investor mispricing?," Journal of Banking & Finance, Elsevier, vol. 60(C), pages 224-238.
    7. Nguyen, Hung T. & Pham, Mia Hang, 2021. "Air pollution and behavioral biases: Evidence from stock market anomalies," Journal of Behavioral and Experimental Finance, Elsevier, vol. 29(C).
    8. Cakici, Nusret & Zaremba, Adam, 2022. "Salience theory and the cross-section of stock returns: International and further evidence," Journal of Financial Economics, Elsevier, vol. 146(2), pages 689-725.
    9. Lin, Chaonan & Chen, Hong-Yi & Ko, Kuan-Cheng & Yang, Nien-Tzu, 2021. "Time-dependent lottery preference and the cross-section of stock returns," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 272-294.
    10. Chung, San-Lin & Hung, Chi-Hsiou & Yeh, Chung-Ying, 2012. "When does investor sentiment predict stock returns?," Journal of Empirical Finance, Elsevier, vol. 19(2), pages 217-240.
    11. Bennett, Donyetta & Mekelburg, Erik & Williams, T.H., 2023. "BeFi meets DeFi: A behavioral finance approach to decentralized finance asset pricing," Research in International Business and Finance, Elsevier, vol. 65(C).
    12. David Hirshleifer & Po-Hsuan Hsu & Dongmei Li, 2018. "Innovative Originality, Profitability, and Stock Returns," The Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2553-2605.
    13. Xiong, Xiong & Meng, Yongqiang & Joseph, Nathan Lael & Shen, Dehua, 2020. "Stock mispricing, hard-to-value stocks and the influence of internet stock message boards," International Review of Financial Analysis, Elsevier, vol. 72(C).
    14. 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.
    15. Kumari, Jyoti, 2019. "Investor sentiment and stock market liquidity: Evidence from an emerging economy," Journal of Behavioral and Experimental Finance, Elsevier, vol. 23(C), pages 166-180.
    16. Lam, F.Y. Eric C. & Wei, K.C. John, 2011. "Limits-to-arbitrage, investment frictions, and the asset growth anomaly," Journal of Financial Economics, Elsevier, vol. 102(1), pages 127-149, October.
    17. Richardson, Scott & Tuna, Irem & Wysocki, Peter, 2010. "Accounting anomalies and fundamental analysis: A review of recent research advances," Journal of Accounting and Economics, Elsevier, vol. 50(2-3), pages 410-454, December.
    18. Cakici, Nusret & Zaremba, Adam, 2023. "Recency bias and the cross-section of international stock returns," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 84(C).
    19. Saumya Ranjan Dash & Jitendra Mahakud, 2013. "Investor Sentiment and Stock Return: Do Industries Matter?," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 7(3), pages 315-349, August.
    20. Guo, Li & Li, Frank Weikai & John Wei, K.C., 2020. "Security analysts and capital market anomalies," Journal of Financial Economics, Elsevier, vol. 137(1), pages 204-230.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

    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:baf:cbafwp:cbafwp1888. 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: Michela Pozzi (email available below). General contact details of provider: https://edirc.repec.org/data/cbbocit.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.