IDEAS home Printed from https://ideas.repec.org/a/eee/jbfina/v42y2014icp1-10.html
   My bibliography  Save this article

The MAX effect: European evidence

Author

Listed:
  • Walkshäusl, Christian

Abstract

The maximum daily return over the previous month (MAX) of Bali et al. (2011) is a strong and significant predictor of future stock returns in non-U.S. equity markets. Once it is controlled for MAX in the cross-section of average returns, the puzzling negative idiosyncratic volatility-return relation disappears. Consistent with the assumption that MAX is the true effect, for which idiosyncratic volatility is just a proxy, we find that MAX can be traced back to firm fundamentals in the manner of idiosyncratic volatility. The negative MAX-return relation is stronger among firms with high cash flow volatility and weaker among firms with high profitability.

Suggested Citation

  • Walkshäusl, Christian, 2014. "The MAX effect: European evidence," Journal of Banking & Finance, Elsevier, vol. 42(C), pages 1-10.
    • Handle: RePEc:eee:jbfina:v:42:y:2014:i:c:p:1-10
    DOI: 10.1016/j.jbankfin.2014.01.020
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S037842661400034X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jbankfin.2014.01.020?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
    ---><---

    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. repec:bla:jfinan:v:53:y:1998:i:6:p:1975-1999 is not listed on IDEAS
    2. John Y. Campbell & Martin Lettau & Burton G. Malkiel & Yexiao Xu, 2001. "Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk," Journal of Finance, American Finance Association, vol. 56(1), pages 1-43, February.
    3. Ľuboš Pástor & Veronesi Pietro, 2003. "Stock Valuation and Learning about Profitability," Journal of Finance, American Finance Association, vol. 58(5), pages 1749-1789, October.
    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. repec:bla:jfinan:v:58:y:2003:i:5:p:1749-1790 is not listed on IDEAS
    7. Eugene F. Fama & Kenneth R. French, 2008. "Dissecting Anomalies," Journal of Finance, American Finance Association, vol. 63(4), pages 1653-1678, August.
    8. Nicholas Barberis & Ming Huang, 2008. "Stocks as Lotteries: The Implications of Probability Weighting for Security Prices," American Economic Review, American Economic Association, vol. 98(5), pages 2066-2100, December.
    9. 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.
    10. Steven X. Wei & Chu Zhang, 2006. "Why Did Individual Stocks Become More Volatile?," The Journal of Business, University of Chicago Press, vol. 79(1), pages 259-292, January.
    11. Fama, Eugene F. & French, Kenneth R., 2012. "Size, value, and momentum in international stock returns," Journal of Financial Economics, Elsevier, vol. 105(3), pages 457-472.
    12. Banz, Rolf W., 1981. "The relationship between return and market value of common stocks," Journal of Financial Economics, Elsevier, vol. 9(1), pages 3-18, March.
    13. Andy C.W. Chui & Sheridan Titman & K.C. John Wei, 2010. "Individualism and Momentum around the World," Journal of Finance, American Finance Association, vol. 65(1), pages 361-392, February.
    14. 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.
    15. 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.
    16. Haugen, Robert A. & Baker, Nardin L., 1996. "Commonality in the determinants of expected stock returns," Journal of Financial Economics, Elsevier, vol. 41(3), pages 401-439, July.
    17. Heston, Steven L. & Rouwenhorst, K. Geert & Wessels, Roberto E., 1995. "The structure of international stock returns and the integration of capital markets," Journal of Empirical Finance, Elsevier, vol. 2(3), pages 173-197, September.
    18. Alok Kumar, 2009. "Who Gambles in the Stock Market?," Journal of Finance, American Finance Association, vol. 64(4), pages 1889-1933, August.
    19. 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.
    20. repec:bla:jfinan:v:53:y:1998:i:1:p:267-284 is not listed on IDEAS
    21. Paul J. Irvine & Jeffrey Pontiff, 2009. "Idiosyncratic Return Volatility, Cash Flows, and Product Market Competition," The Review of Financial Studies, Society for Financial Studies, vol. 22(3), pages 1149-1177.
    22. 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.
    23. 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.
    24. Loughran, Tim, 1997. "Book-to-Market across Firm Size, Exchange, and Seasonality: Is There an Effect?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 32(3), pages 249-268, September.
    25. John H. Cochrane, 2011. "Presidential Address: Discount Rates," Journal of Finance, American Finance Association, vol. 66(4), pages 1047-1108, August.
    26. Lo, Andrew W & MacKinlay, A Craig, 1990. "Data-Snooping Biases in Tests of Financial Asset Pricing Models," The Review of Financial Studies, Society for Financial Studies, vol. 3(3), pages 431-467.
    27. Carhart, Mark M, 1997. "On Persistence in Mutual Fund Performance," Journal of Finance, American Finance Association, vol. 52(1), pages 57-82, March.
    28. Jegadeesh, Narasimhan, 1990. "Evidence of Predictable Behavior of Security Returns," Journal of Finance, American Finance Association, vol. 45(3), pages 881-898, July.
    29. Kewei Hou & G. Andrew Karolyi & Bong-Chan Kho, 2011. "What Factors Drive Global Stock Returns?," The Review of Financial Studies, Society for Financial Studies, vol. 24(8), pages 2527-2574.
    30. Bali, Turan G. & Demirtas, K. Ozgur & Tehranian, Hassan, 2008. "Aggregate Earnings, Firm-Level Earnings, and Expected Stock Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 43(3), pages 657-684, September.
    31. Paul J. Irvine & Jeffrey Pontiff, 2009. "Idiosyncratic Return Volatility, Cash Flows, and Product Market Competition," The Review of Financial Studies, Society for Financial Studies, vol. 22(3), pages 1149-1177, March.
    32. Keim, Donald B., 1983. "Size-related anomalies and stock return seasonality : Further empirical evidence," Journal of Financial Economics, Elsevier, vol. 12(1), pages 13-32, June.
    33. Fama, Eugene F & French, Kenneth R, 1996. "The CAPM Is Wanted, Dead or Alive," Journal of Finance, American Finance Association, vol. 51(5), pages 1947-1958, December.
    34. Huang, Alan Guoming, 2009. "The cross section of cashflow volatility and expected stock returns," Journal of Empirical Finance, Elsevier, vol. 16(3), pages 409-429, June.
    35. 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.
    36. Fama, Eugene F. & French, Kenneth R., 2006. "Profitability, investment and average returns," Journal of Financial Economics, Elsevier, vol. 82(3), pages 491-518, December.
    37. Elena Asparouhova & Hendrik Bessembinder & Ivalina Kalcheva, 2013. "Noisy Prices and Inference Regarding Returns," Journal of Finance, American Finance Association, vol. 68(2), pages 665-714, April.
    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. Bradrania, Reza & Veron, Jose Francisco, 2023. "The beta anomaly in the Australian stock market and the lottery demand," Pacific-Basin Finance Journal, Elsevier, vol. 77(C).
    2. Nartea, Gilbert V. & Kong, Dongmin & Wu, Ji, 2017. "Do extreme returns matter in emerging markets? Evidence from the Chinese stock market," Journal of Banking & Finance, Elsevier, vol. 76(C), pages 189-197.
    3. Xiaozhen Jing & Dezhong Xu & Bin Li & Tarlok Singh, 2024. "Does the U.S. extreme indicator matter in stock markets? International evidence," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-27, December.
    4. Kwon, Kyung Yoon & Min, Byoung-Kyu & Sun, Chenfei, 2022. "Enhancing the profitability of lottery strategies," Journal of Empirical Finance, Elsevier, vol. 69(C), pages 166-184.
    5. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, January.
    6. Fan, Ruixin & Xiong, Xiong & Gao, Ya, 2021. "Can the probability of extreme returns be the basis for profitable portfolios? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 76(C).
    7. Gao, Ya & Han, Xing & Xiong, Xiong, 2021. "Loss from the chasing of MAX stocks: Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 58(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. Adam Zaremba & Jacob Koby Shemer, 2018. "Price-Based Investment Strategies," Springer Books, Springer, number 978-3-319-91530-2, January.
    2. Kewei Hou & Chen Xue & Lu Zhang, 2017. "Replicating Anomalies," NBER Working Papers 23394, National Bureau of Economic Research, Inc.
    3. 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.
    4. Walkshäusl, Christian, 2015. "Equity financing activities and European value-growth returns," Journal of Banking & Finance, Elsevier, vol. 57(C), pages 27-40.
    5. Waszczuk, Antonina, 2013. "A risk-based explanation of return patterns—Evidence from the Polish stock market," Emerging Markets Review, Elsevier, vol. 15(C), pages 186-210.
    6. 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).
    7. 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.
    8. Cakici, Nusret & Zaremba, Adam, 2021. "Liquidity and the cross-section of international stock returns," Journal of Banking & Finance, Elsevier, vol. 127(C).
    9. 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.
    10. Annaert, Jan & De Ceuster, Marc & Verstegen, Kurt, 2013. "Are extreme returns priced in the stock market? European evidence," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3401-3411.
    11. 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.
    12. 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.
    13. 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.
    14. Hollstein, Fabian & Prokopczuk, Marcel & Wese Simen, Chardin, 2020. "Beta uncertainty," Journal of Banking & Finance, Elsevier, vol. 116(C).
    15. Turan G. Bali & Robert F. Engle & Yi Tang, 2017. "Dynamic Conditional Beta Is Alive and Well in the Cross Section of Daily Stock Returns," Management Science, INFORMS, vol. 63(11), pages 3760-3779, November.
    16. Zhong, Angel, 2018. "Idiosyncratic volatility in the Australian equity market," Pacific-Basin Finance Journal, Elsevier, vol. 50(C), pages 105-125.
    17. Anton Astakhov & Tomas Havranek & Jiri Novak, 2019. "Firm Size And Stock Returns: A Quantitative Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 33(5), pages 1463-1492, December.
    18. Sebastien Valeyre & Sofiane Aboura & Denis Grebenkov, 2019. "The Reactive Beta Model," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 42(1), pages 71-113, March.
    19. Woon Sau Leung & Nicholas Taylor, 2013. "Testing for contagion: the impact of US structured markets on international financial markets," Chapters, in: Adrian R. Bell & Chris Brooks & Marcel Prokopczuk (ed.), Handbook of Research Methods and Applications in Empirical Finance, chapter 11, pages 256-284, Edward Elgar Publishing.
    20. Cakici, Nusret & Zaremba, Adam & Bianchi, Robert J. & Pham, Nga, 2021. "False discoveries in the anomaly research: New insights from the Stock Exchange of Melbourne (1927–1987)," Pacific-Basin Finance Journal, Elsevier, vol. 70(C).

    More about this item

    Keywords

    Maximum daily return; Cross-sectional return predictability; International markets; Idiosyncratic volatility; Cash flow volatility; Profitability;
    All these keywords.

    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    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:eee:jbfina:v:42:y:2014:i:c:p:1-10. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbf .

    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.