IDEAS home Printed from https://ideas.repec.org/a/eee/ecolet/v118y2013i2p342-346.html
   My bibliography  Save this article

What determines the dynamics of absolute excess returns on stock markets?

Author

Listed:
  • Kurz, Claudia
  • Kurz-Kim, Jeong-Ryeol

Abstract

In this paper, we quantify the dynamics of absolute excess returns on stock markets depending on three factors: the average of the absolute excess return, the level of the stock price, and stock market volatility. We also argue that the absolute excess return can be regarded as an empirical measure of the herding behavior of financial investors. Our empirical results for the German stock index show that the absolute excess return depends significantly on all three factors, although volatility may be seen as the strongest factor among them.

Suggested Citation

  • Kurz, Claudia & Kurz-Kim, Jeong-Ryeol, 2013. "What determines the dynamics of absolute excess returns on stock markets?," Economics Letters, Elsevier, vol. 118(2), pages 342-346.
  • Handle: RePEc:eee:ecolet:v:118:y:2013:i:2:p:342-346
    DOI: 10.1016/j.econlet.2012.11.029
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165176512006192
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.econlet.2012.11.029?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. Dilip Abreu & Markus K. Brunnermeier, 2003. "Bubbles and Crashes," Econometrica, Econometric Society, vol. 71(1), pages 173-204, January.
    2. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    3. Anders Johansen & Olivier Ledoit & Didier Sornette, 2000. "Crashes As Critical Points," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(02), pages 219-255.
    4. Sushil Bikhchandani & Sunil Sharma, 2001. "Herd Behavior in Financial Markets," IMF Staff Papers, Palgrave Macmillan, vol. 47(3), pages 1-1.
    5. Cont, Rama & Bouchaud, Jean-Philipe, 2000. "Herd Behavior And Aggregate Fluctuations In Financial Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 4(2), pages 170-196, June.
    6. Jeong-Ryeol Kurz-Kim, 2009. "Further evidence for the negative relationship between stock returns and volatility," Applied Economics Letters, Taylor & Francis Journals, vol. 16(13), pages 1295-1300.
    7. Itzhak Venezia & Amrut Nashikkar & Zur Shapira, 2011. "Firm specific and macro herding by professional and amateur investors and their effects on market volatility," Discussion Paper Series dp586, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    8. Bikhchandani, Sushil & Hirshleifer, David & Welch, Ivo, 1992. "A Theory of Fads, Fashion, Custom, and Cultural Change in Informational Cascades," Journal of Political Economy, University of Chicago Press, vol. 100(5), pages 992-1026, October.
    9. Venezia, Itzhak & Nashikkar, Amrut & Shapira, Zur, 2011. "Firm specific and macro herding by professional and amateur investors and their effects on market volatility," Journal of Banking & Finance, Elsevier, vol. 35(7), pages 1599-1609, July.
    10. Andreas Park & Hamid Sabourian, 2011. "Herding and Contrarian Behavior in Financial Markets," Econometrica, Econometric Society, vol. 79(4), pages 973-1026, July.
    11. Hott, Christian, 2009. "Herding behavior in asset markets," Journal of Financial Stability, Elsevier, vol. 5(1), pages 35-56, January.
    12. Abhijit V. Banerjee, 1992. "A Simple Model of Herd Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 107(3), pages 797-817.
    13. Bogaçhan Çelen & Shachar Kariv, 2004. "Distinguishing Informational Cascades from Herd Behavior in the Laboratory," American Economic Review, American Economic Association, vol. 94(3), pages 484-498, June.
    14. Morone, Andrea, 2012. "A simple model of herd behavior, a comment," Economics Letters, Elsevier, vol. 114(2), pages 208-211.
    15. In Ho Lee, 1998. "Market Crashes and Informational Avalanches," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 65(4), pages 741-759.
    16. Andrea Morone, 2008. "Financial markets in the laboratory: an experimental analysis of some stylized facts," Quantitative Finance, Taylor & Francis Journals, vol. 8(5), pages 513-532.
    17. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-896, July.
    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. Kurz-Kim, Jeong-Ryeol, 2016. "Black Monday, globalization and trading behavior of stock investors," Discussion Papers 18/2016, Deutsche Bundesbank.
    2. Kizys, Renatas & Tzouvanas, Panagiotis & Donadelli, Michael, 2021. "From COVID-19 herd immunity to investor herding in international stock markets: The role of government and regulatory restrictions," International Review of Financial Analysis, Elsevier, vol. 74(C).
    3. Ferreruela, Sandra & Mallor, Tania, 2021. "Herding in the bad times: The 2008 and COVID-19 crises," 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. Puput Tri Komalasari & Marwan Asri & Bernardinus M. Purwanto & Bowo Setiyono, 2022. "Herding behaviour in the capital market: What do we know and what is next?," Management Review Quarterly, Springer, vol. 72(3), pages 745-787, September.
    2. Giovanni Ferri & Andrea Morone, 2014. "The effect of rating agencies on herd behaviour," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 9(1), pages 107-127, April.
    3. Arjoon, Vaalmikki & Bhatnagar, Chandra Shekhar, 2017. "Dynamic herding analysis in a frontier market," Research in International Business and Finance, Elsevier, vol. 42(C), pages 496-508.
    4. Hirshleifer, David & Teoh, Siew Hong, 2008. "Thought and Behavior Contagion in Capital Markets," MPRA Paper 9142, University Library of Munich, Germany.
    5. Kremer, Stephanie & Nautz, Dieter, 2013. "Causes and consequences of short-term institutional herding," Journal of Banking & Finance, Elsevier, vol. 37(5), pages 1676-1686.
    6. Galariotis, Emilios C. & Krokida, Styliani-Iris & Spyrou, Spyros I., 2016. "Bond market investor herding: Evidence from the European financial crisis," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 367-375.
    7. M. Fern'andez-Mart'inez & M. A S'anchez-Granero & Mar'ia Jos'e Mu~noz Torrecillas & Bill McKelvey, 2016. "A comparison among some Hurst exponent approaches to predict nascent bubbles in $500$ company stocks," Papers 1601.04188, arXiv.org.
    8. Makoto Nirei & John Stachurski & Tsutomu Watanabe, 2018. "Trade Clustering and Power Laws in Financial Markets (Published in Theoretical Economics, 15:1365?1398, 2020)," CARF F-Series CARF-F-450, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    9. Nirei, Makoto & Stachurski, John & Watanabe, Tsutomu, 2020. "Trade clustering and power laws in financial markets," Theoretical Economics, Econometric Society, vol. 15(4), November.
    10. Marco Cipriani & Antonio Guarino, 2014. "Estimating a Structural Model of Herd Behavior in Financial Markets," American Economic Review, American Economic Association, vol. 104(1), pages 224-251, January.
    11. Dang, Ha V. & Lin, Mi, 2016. "Herd mentality in the stock market: On the role of idiosyncratic participants with heterogeneous information," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 247-260.
    12. Jaqueson K. Galimberti & Nicolas Suhadolnik & Sergio Silva, 2017. "Cowboying Stock Market Herds with Robot Traders," Computational Economics, Springer;Society for Computational Economics, vol. 50(3), pages 393-423, October.
    13. Wang, Xinru & Kim, Maria H. & Suardi, Sandy, 2022. "Herding and China's market-wide circuit breaker," Journal of Banking & Finance, Elsevier, vol. 141(C).
    14. Fei, Tianlun & Liu, Xiaoquan, 2021. "Herding and market volatility," International Review of Financial Analysis, Elsevier, vol. 78(C).
    15. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2001. "Microscopic Models of Financial Markets," Papers cond-mat/0110354, arXiv.org.
    16. Feri, Francesco & Meléndez-Jiménez, Miguel A. & Ponti, Giovanni & Vega-Redondo, Fernando, 2011. "Error cascades in observational learning: An experiment on the Chinos game," Games and Economic Behavior, Elsevier, vol. 73(1), pages 136-146, September.
    17. Stephanie De Mel & Kaivan Munshi & Soenje Reiche & Hamid Sabourian, 2021. "Herding with Heterogeneous Ability: An Application to Organ Transplantation," Cowles Foundation Discussion Papers 2308, Cowles Foundation for Research in Economics, Yale University.
    18. Sornette, Didier & Zhou, Wei-Xing, 2006. "Importance of positive feedbacks and overconfidence in a self-fulfilling Ising model of financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(2), pages 704-726.
    19. Yide Wang & Chao Yu & Xujie Zhao, 2023. "Does herding effect help forecast market volatility?—Evidence from the Chinese stock market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1275-1290, August.
    20. Andreas Pyka & Uwe Cantner & Alfred Greiner & Thomas Kuhn (ed.), 2009. "Recent Advances in Neo-Schumpeterian Economics," Books, Edward Elgar Publishing, number 12982.

    More about this item

    Keywords

    Absolute excess returns; Uncertainty; Herding behavior; Mean reverting; Stock market volatility;
    All these keywords.

    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • G02 - Financial Economics - - General - - - Behavioral Finance: Underlying Principles

    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:ecolet:v:118:y:2013:i:2:p:342-346. 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/ecolet .

    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.