IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/53802.html
   My bibliography  Save this paper

Investment Decisions by Analysts: A Case Study of KSE

Author

Listed:
  • Shaikh, Salman

Abstract

Security prices in efficient markets reflect all relevant information. Past price formations and even fundamental analysis cannot guarantee abnormal returns consistently to any pre-identified strategy or market participant, be they novice or expert traders. There have been various studies done in past to test market efficiency in emerging markets. However, in this study, we take the approach of surveying the professional investment community and study their stated actions in making investments. Our results indicate prevalence of herding and overconfidence in professional analysts. We also find that analysts extrapolate past into the future forecasts. We also find association between demographic characteristics and choice of security valuation methods that analysts use. In line with Chevalier & Ellison (1998), we find that young people herd less in our sample than the old people.

Suggested Citation

  • Shaikh, Salman, 2013. "Investment Decisions by Analysts: A Case Study of KSE," MPRA Paper 53802, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:53802
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/53802/1/MPRA_paper_53802.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nerissa C. Brown & Kelsey D. Wei & Russ Wermers, 2014. "Analyst Recommendations, Mutual Fund Herding, and Overreaction in Stock Prices," Management Science, INFORMS, vol. 60(1), pages 1-20, January.
    2. Stephen A. Ross, 2013. "The Arbitrage Theory of Capital Asset Pricing," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 1, pages 11-30, World Scientific Publishing Co. Pte. Ltd..
    3. Judith Chevalier & Glenn Ellison, 1999. "Career Concerns of Mutual Fund Managers," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(2), pages 389-432.
    4. Cheng, Yingmei & Liu, Mark H. & Qian, Jun, 2006. "Buy-Side Analysts, Sell-Side Analysts, and Investment Decisions of Money Managers," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 41(1), pages 51-83, March.
    5. 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.
    6. 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..
    7. Michael C. Jensen, 1968. "The Performance Of Mutual Funds In The Period 1945–1964," Journal of Finance, American Finance Association, vol. 23(2), pages 389-416, May.
    8. De Bondt, Werner F M & Thaler, Richard, 1985. "Does the Stock Market Overreact?," Journal of Finance, American Finance Association, vol. 40(3), pages 793-805, July.
    9. 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.
    10. 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.
    11. Black, Fischer & Scholes, Myron S, 1972. "The Valuation of Option Contracts and a Test of Market Efficiency," Journal of Finance, American Finance Association, vol. 27(2), pages 399-417, May.
    12. 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.
    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. Fernando Rubio, 2005. "Eficiencia De Mercado, Administracion De Carteras De Fondos Y Behavioural Finance," Finance 0503028, University Library of Munich, Germany, revised 23 Jul 2005.
    2. John Y. Campbell, 2000. "Asset Pricing at the Millennium," Journal of Finance, American Finance Association, vol. 55(4), pages 1515-1567, August.
    3. Sonntag, Dominik, 2018. "Die Theorie der fairen geometrischen Rendite [The Theory of Fair Geometric Returns]," MPRA Paper 87082, University Library of Munich, Germany.
    4. Committee, Nobel Prize, 2013. "Understanding Asset Prices," Nobel Prize in Economics documents 2013-1, Nobel Prize Committee.
    5. Trabelsi, Mohamed Ali, 2010. "Choix de portefeuille: comparaison des différentes stratégies [Portfolio selection: comparison of different strategies]," MPRA Paper 82946, University Library of Munich, Germany, revised 01 Dec 2010.
    6. 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.
    7. Rocciolo, Francesco & Gheno, Andrea & Brooks, Chris, 2022. "Explaining abnormal returns in stock markets: An alpha-neutral version of the CAPM," International Review of Financial Analysis, Elsevier, vol. 82(C).
    8. van Dijk, Mathijs A., 2011. "Is size dead? A review of the size effect in equity returns," Journal of Banking & Finance, Elsevier, vol. 35(12), pages 3263-3274.
    9. Michael Dempsey, 2015. "Stock Markets, Investments and Corporate Behavior:A Conceptual Framework of Understanding," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number p1007, December.
    10. Martin Gold, 2010. "Fiduciary Finance," Books, Edward Elgar Publishing, number 13813.
    11. Doran, James & Jiang, Danling & Peterson, David, 2007. "Short-Sale Constraints and the Non-January Idiosyncratic Volatility Puzzle," MPRA Paper 4995, University Library of Munich, Germany.
    12. Gabriel Hawawini & Donald B. Keim, "undated". "The Cross Section of Common Stock Returns: A Review of the Evidence and Some New Findings," Rodney L. White Center for Financial Research Working Papers 08-99, Wharton School Rodney L. White Center for Financial Research.
    13. Alex R. Horenstein, 2021. "The Unintended Impact of Academic Research on Asset Returns: The Capital Asset Pricing Model Alpha," Management Science, INFORMS, vol. 67(6), pages 3655-3673, June.
    14. Andreas Ziegler & Michael Schröder & Anja Schulz & Richard Stehle, 2007. "Multifaktormodelle zur Erklärung deutscher Aktienrenditen: Eine empirische Analyse," Schmalenbach Journal of Business Research, Springer, vol. 59(3), pages 355-389, May.
    15. Joachim Freyberger & Andreas Neuhierl & Michael Weber, 2020. "Dissecting Characteristics Nonparametrically," The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2326-2377.
    16. Ebrahim, M. Shahid & Girma, Sourafel & Shah, M. Eskandar & Williams, Jonathan, 2014. "Rationalizing the value premium in emerging markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 29(C), pages 51-70.
    17. Kie Wong & Ruth Tan & Wei Liu, 2006. "The Cross-Section of Stock Returns on The Shanghai Stock Exchange," Review of Quantitative Finance and Accounting, Springer, vol. 26(1), pages 23-39, February.
    18. Ericsson, Johan & Karlsson, Sune, 2003. "Choosing Factors in a Multifactor Asset Pricing Model: A Bayesian Approach," SSE/EFI Working Paper Series in Economics and Finance 524, Stockholm School of Economics, revised 12 Feb 2004.
    19. Neszveda, G., 2019. "Essays on behavioral finance," Other publications TiSEM 05059039-5236-42a3-be1b-3, Tilburg University, School of Economics and Management.
    20. Wu, Xueping, 2002. "A conditional multifactor analysis of return momentum," Journal of Banking & Finance, Elsevier, vol. 26(8), pages 1675-1696, August.

    More about this item

    Keywords

    Investment Behavior; Behavioral Finance; Herding; Mutual Funds; Security Analysis; CAPM; Technical Analysis;
    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
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:pra:mprapa:53802. 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: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.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.