IDEAS home Printed from https://ideas.repec.org/a/bla/finmgt/v44y2015i2p295-322.html
   My bibliography  Save this article

High Idiosyncratic Volatility and Low Returns: A Prospect Theory Explanation

Author

Listed:
  • Ajay Bhootra
  • Jungshik Hur

Abstract

type="main"> The well-documented negative relationship between idiosyncratic volatility and stock returns is puzzling if investors are risk-averse. However, under prospect theory, while investors are risk-averse in the domain of gains, they exhibit risk-seeking behavior in the domain of losses. Consistent with risk-seeking investors’ preference for high-volatility stocks in the loss domain, we find that the negative relationship between idiosyncratic volatility and stock returns is concentrated in stocks with unrealized capital losses, but is nonexistent in stocks with unrealized capital gains. This finding is robust to control for short-term return reversals and maximum daily return, among other variables.

Suggested Citation

  • Ajay Bhootra & Jungshik Hur, 2015. "High Idiosyncratic Volatility and Low Returns: A Prospect Theory Explanation," Financial Management, Financial Management Association International, vol. 44(2), pages 295-322, June.
    • Handle: RePEc:bla:finmgt:v:44:y:2015:i:2:p:295-322
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1111/fima.12057
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Scholes, Myron & Williams, Joseph, 1977. "Estimating betas from nonsynchronous data," Journal of Financial Economics, Elsevier, vol. 5(3), pages 309-327, December.
    2. Karl B. Diether & Kuan-Hui Lee & Ingrid M. Werner, 2009. "Short-Sale Strategies and Return Predictability," Review of Financial Studies, Society for Financial Studies, vol. 22(2), pages 575-607, February.
    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. 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. Ang, Andrew & Hodrick, Robert J. & Xing, Yuhang & Zhang, Xiaoyan, 2009. "High idiosyncratic volatility and low returns: International and further U.S. evidence," Journal of Financial Economics, Elsevier, vol. 91(1), pages 1-23, January.
    6. Bali, Turan G. & Cakici, Nusret, 2008. "Idiosyncratic Volatility and the Cross Section of Expected Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(1), pages 29-58, March.
    7. 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.
    8. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    9. Jegadeesh, Narasimhan, 1990. "Evidence of Predictable Behavior of Security Returns," Journal of Finance, American Finance Association, vol. 45(3), pages 881-898, July.
    10. Lo, Andrew W & MacKinlay, A Craig, 1990. "When Are Contrarian Profits Due to Stock Market Overreaction?," The Review of Financial Studies, Society for Financial Studies, vol. 3(2), pages 175-205.
    11. Brian Boyer & Todd Mitton & Keith Vorkink, 2010. "Expected Idiosyncratic Skewness," Review of Financial Studies, Society for Financial Studies, vol. 23(1), pages 169-202, January.
    12. Grinblatt, Mark & Han, Bing, 2005. "Prospect theory, mental accounting, and momentum," Journal of Financial Economics, Elsevier, vol. 78(2), pages 311-339, November.
    13. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    14. Merton, Robert C, 1987. "A Simple Model of Capital Market Equilibrium with Incomplete Information," Journal of Finance, American Finance Association, vol. 42(3), pages 483-510, July.
    15. Barberis, Nicholas & Xiong, Wei, 2012. "Realization utility," Journal of Financial Economics, Elsevier, vol. 104(2), pages 251-271.
    16. Nicholas Barberis & Ming Huang & Tano Santos, "undated". "Prospect Theory and Asset Prices," CRSP working papers 494, Center for Research in Security Prices, Graduate School of Business, University of Chicago.
    17. Wei Huang & Qianqiu Liu & S. Ghon Rhee & Liang Zhang, 2010. "Return Reversals, Idiosyncratic Risk, and Expected Returns," Review of Financial Studies, Society for Financial Studies, vol. 23(1), pages 147-168, January.
    18. Jason D. Fink & Kristin E. Fink & Hui He, 2012. "Expected Idiosyncratic Volatility Measures and Expected Returns," Financial Management, Financial Management Association International, vol. 41(3), pages 519-553, September.
    19. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    20. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    21. 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.
    22. Bruce N. Lehmann, 1990. "Fads, Martingales, and Market Efficiency," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 105(1), pages 1-28.
    23. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    24. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    25. Pontiff, Jeffrey, 2006. "Costly arbitrage and the myth of idiosyncratic risk," Journal of Accounting and Economics, Elsevier, vol. 42(1-2), pages 35-52, October.
    26. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    27. Jungshik Hur & Mahesh Pritamani & Vivek Sharma, 2010. "Momentum and the Disposition Effect: The Role of Individual Investors," Financial Management, Financial Management Association International, vol. 39(3), pages 1155-1176, September.
    28. Dimson, Elroy, 1979. "Risk measurement when shares are subject to infrequent trading," Journal of Financial Economics, Elsevier, vol. 7(2), pages 197-226, June.
    29. Peterson, David R. & Smedema, Adam R., 2011. "The return impact of realized and expected idiosyncratic volatility," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2547-2558, October.
    30. Shefrin, Hersh & Statman, Meir, 1985. "The Disposition to Sell Winners Too Early and Ride Losers Too Long: Theory and Evidence," Journal of Finance, American Finance Association, vol. 40(3), pages 777-790, July.
    31. Fama, Eugene F & MacBeth, James D, 1973. "Risk, Return, and Equilibrium: Empirical Tests," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 607-636, May-June.
    32. Nicholas Barberis & Ming Huang & Tano Santos, 2001. "Prospect Theory and Asset Prices," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 116(1), pages 1-53.
    33. Fu, Fangjian, 2009. "Idiosyncratic risk and the cross-section of expected stock returns," Journal of Financial Economics, Elsevier, vol. 91(1), pages 24-37, January.
    34. Jegadeesh, Narasimhan & Titman, Sheridan, 1993. "Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency," Journal of Finance, American Finance Association, vol. 48(1), pages 65-91, March.
    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. Tariq Aziz & Valeed Ahmad Ansari, 2017. "Idiosyncratic volatility and stock returns: Indian evidence," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1420998-142, January.
    2. Benoit Carmichael & Gilles Boevi Koumou & Kevin Moran, 2021. "The political reception of innovations," Cahiers de recherche 2107, Centre de recherche sur les risques, les enjeux économiques, et les politiques publiques.
    3. Neszveda, G., 2019. "Essays on behavioral finance," Other publications TiSEM 05059039-5236-42a3-be1b-3, Tilburg University, School of Economics and Management.
    4. Egginton, Jared & Hur, Jungshik, 2018. "The robust “maximum daily return effect as demand for lottery” and “idiosyncratic volatility puzzle”," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 229-245.
    5. Benoît Carmichael & Gilles Boevi Koumou & Kevin Moran, 2021. "The RQE-CAPM : New insights about the pricing of idiosyncratic risk," CIRANO Working Papers 2021s-28, CIRANO.
    6. Haensly, Paul J., 2022. "Lessons from naïve diversification about the risk-reward trade-off," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    7. Mi‐Hsiu Chiang & Hsin‐Yu Chiu & Robin K. Chou, 2021. "Relevance of the disposition effect on the options market: New evidence," Financial Management, Financial Management Association International, vol. 50(1), pages 75-106, March.
    8. Jie Cao & Tarun Chordia & Xintong Zhan, 2021. "The Calendar Effects of the Idiosyncratic Volatility Puzzle: A Tale of Two Days?," Management Science, INFORMS, vol. 67(12), pages 7866-7887, December.
    9. Hur, Jungshik & Singh, Vivek, 2019. "How do disposition effect and anchoring bias interact to impact momentum in stock returns?," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 238-256.
    10. Giannikos, Christos I. & Kakolyris, Andreas & Suen, Tin Shan, 2023. "Prospect theory and a manager's decision to trade a blind principal bid basket," Global Finance Journal, Elsevier, vol. 55(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. Egginton, Jared & Hur, Jungshik, 2018. "The robust “maximum daily return effect as demand for lottery” and “idiosyncratic volatility puzzle”," Journal of Empirical Finance, Elsevier, vol. 47(C), pages 229-245.
    2. Wang, Huijun & Yan, Jinghua & Yu, Jianfeng, 2017. "Reference-dependent preferences and the risk–return trade-off," Journal of Financial Economics, Elsevier, vol. 123(2), pages 395-414.
    3. Tariq Aziz & Valeed Ahmad Ansari, 2017. "Idiosyncratic volatility and stock returns: Indian evidence," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1420998-142, January.
    4. Amit Goyal, 2012. "Empirical cross-sectional asset pricing: a survey," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 26(1), pages 3-38, March.
    5. Aboulamer, Anas & Kryzanowski, Lawrence, 2016. "Are idiosyncratic volatility and MAX priced in the Canadian market?," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 20-36.
    6. 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.
    7. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, June.
    8. Lin, Mei-Chen & Lin, Yu-Ling, 2021. "Idiosyncratic skewness and cross-section of stock returns: Evidence from Taiwan," International Review of Financial Analysis, Elsevier, vol. 77(C).
    9. Son, Nguyen Truong & Nguyen, Nhat Minh, 2019. "Prospect theory value and idiosyncratic volatility: Evidence from the Korean stock market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 21(C), pages 113-122.
    10. Chabi-Yo, Fousseni & Ruenzi, Stefan & Weigert, Florian, 2018. "Crash Sensitivity and the Cross Section of Expected Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(3), pages 1059-1100, June.
    11. Yunting Liu, 2022. "The Short-Run and Long-Run Components of Idiosyncratic Volatility and Stock Returns," Management Science, INFORMS, vol. 68(2), pages 1573-1589, February.
    12. Neszveda, G., 2019. "Essays on behavioral finance," Other publications TiSEM 05059039-5236-42a3-be1b-3, Tilburg University, School of Economics and Management.
    13. 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).
    14. Atilgan, Yigit & Bali, Turan G. & Demirtas, K. Ozgur & Gunaydin, A. Doruk, 2020. "Left-tail momentum: Underreaction to bad news, costly arbitrage and equity returns," Journal of Financial Economics, Elsevier, vol. 135(3), pages 725-753.
    15. Melisa Ozdamar & Levent Akdeniz & Ahmet Sensoy, 2021. "Lottery-like preferences and the MAX effect in the cryptocurrency market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-27, December.
    16. 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).
    17. Ji Cao & Marc Oliver Rieger & Lei Zhao, 2019. "Safety First, Loss Probability, and the Cross Section of Expected Stock Returns," Working Paper Series 2019-02, University of Trier, Research Group Quantitative Finance and Risk Analysis.
    18. Zhong, Angel & Gray, Philip, 2016. "The MAX effect: An exploration of risk and mispricing explanations," Journal of Banking & Finance, Elsevier, vol. 65(C), pages 76-90.
    19. Jiang, Danling & Peterson, David R. & Doran, James S., 2014. "Short-sale constraints and the idiosyncratic volatility puzzle: An event study approach," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 36-59.
    20. Hur, Jungshik & Singh, Vivek, 2019. "How do disposition effect and anchoring bias interact to impact momentum in stock returns?," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 238-256.

    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:bla:finmgt:v:44:y:2015:i:2:p:295-322. 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: https://edirc.repec.org/data/fmaaaea.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.