IDEAS home Printed from https://ideas.repec.org/a/eee/empfin/v23y2013icp187-190.html
   My bibliography  Save this article

Aggregate investor preferences and beliefs: A comment

Author

Listed:
  • Post, Thierry
  • Kopa, Miloš

Abstract

A recent study in this journal presents encouraging results of a daunting simulation analysis of the statistical properties of a centered bootstrap approach to stochastic dominance efficiency analysis. However, by relying on the first-order optimality condition in a situation where multiple optima may occur, the empirical analysis draws the questionable conclusion that some of the toughest data sets in empirical asset pricing can be rationalized by the representative investor maximizing an S-shaped utility function, consistent with the so-called Prospect Stochastic Dominance criterion. Further research could be directed to developing global optimization algorithms and consistent re-sampling methods for statistical inference for general risky choice problems.

Suggested Citation

  • Post, Thierry & Kopa, Miloš, 2013. "Aggregate investor preferences and beliefs: A comment," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 187-190.
  • Handle: RePEc:eee:empfin:v:23:y:2013:i:c:p:187-190
    DOI: 10.1016/j.jempfin.2013.06.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0927539813000480
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jempfin.2013.06.003?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. Oliver Linton & Esfandiar Maasoumi & Yoon-Jae Whang, 2005. "Consistent Testing for Stochastic Dominance under General Sampling Schemes," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 735-765.
    2. Garry F. Barrett & Stephen G. Donald, 2003. "Consistent Tests for Stochastic Dominance," Econometrica, Econometric Society, vol. 71(1), pages 71-104, January.
    3. repec:bla:jfinan:v:58:y:2003:i:5:p:1905-1932 is not listed on IDEAS
    4. Thierry Post & Haim Levy, 2005. "Does Risk Seeking Drive Stock Prices? A Stochastic Dominance Analysis of Aggregate Investor Preferences and Beliefs," The Review of Financial Studies, Society for Financial Studies, vol. 18(3), pages 925-953.
    5. Thierry Post, 2003. "Empirical Tests for Stochastic Dominance Efficiency," Journal of Finance, American Finance Association, vol. 58(5), pages 1905-1931, October.
    6. Martin Lettau & Sydney Ludvigson, 2001. "Resurrecting the (C)CAPM: A Cross-Sectional Test When Risk Premia Are Time-Varying," Journal of Political Economy, University of Chicago Press, vol. 109(6), pages 1238-1287, December.
    7. Fang, Yi, 2012. "Aggregate investor preferences and beliefs in stock market: A stochastic dominance analysis," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 528-547.
    8. Post, Thierry & Kopa, Miloš, 2013. "General linear formulations of stochastic dominance criteria," European Journal of Operational Research, Elsevier, vol. 230(2), pages 321-332.
    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. Arvanitis, Stelios & Topaloglou, Nikolas, 2017. "Testing for prospect and Markowitz stochastic dominance efficiency," Journal of Econometrics, Elsevier, vol. 198(2), pages 253-270.
    2. Arvanitis, Stelios & Scaillet, Olivier & Topaloglou, Nikolas, 2020. "Spanning tests for Markowitz stochastic dominance," Journal of Econometrics, Elsevier, vol. 217(2), pages 291-311.
    3. Pinar, Mehmet & Stengos, Thanasis & Topaloglou, Nikolas, 2020. "On the construction of a feasible range of multidimensional poverty under benchmark weight uncertainty," European Journal of Operational Research, Elsevier, vol. 281(2), pages 415-427.
    4. Chan, Raymond H. & Chow, Sheung-Chi & Guo, Xu & Wong, Wing-Keung, 2022. "Central moments, stochastic dominance, moment rule, and diversification with an application," Chaos, Solitons & Fractals, Elsevier, vol. 161(C).
    5. Kolokolova, Olga & Le Courtois, Olivier & Xu, Xia, 2022. "Is the index efficient? A worldwide tour with stochastic dominance," Journal of Financial Markets, Elsevier, vol. 59(PB).
    6. Thierry Post & Yi Fang & Miloš Kopa, 2015. "Linear Tests for Decreasing Absolute Risk Aversion Stochastic Dominance," Management Science, INFORMS, vol. 61(7), pages 1615-1629, July.
    7. Christodoulakis, George & Mohamed, Abdulkadir & Topaloglou, Nikolas, 2018. "Optimal privatization portfolios in the presence of arbitrary risk aversion," European Journal of Operational Research, Elsevier, vol. 265(3), pages 1172-1191.
    8. Hooi Hooi Lean & Michael McAleer & Wing-Keung Wong, 2013. "Risk-averse and Risk-seeking Investor Preferences for Oil Spot and Futures," Documentos de Trabajo del ICAE 2013-31, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico, revised Aug 2013.
    9. Zhidong Bai & Hua Li & Michael McAleer & Wing-Keung Wong, 2015. "Stochastic dominance statistics for risk averters and risk seekers: an analysis of stock preferences for USA and China," Quantitative Finance, Taylor & Francis Journals, vol. 15(5), pages 889-900, May.
    10. Duc Khuong Nguyen & Nikolas Topaloglou & Thomas Walther, 2020. "Asset Classes and Portfolio Diversification: Evidence from a Stochastic Spanning Approach," Working Papers 2020-009, Department of Research, Ipag Business School.
    11. Mehmet Pinar & Thanasis Stengos & Nikolas Topaloglou, 2022. "Stochastic dominance spanning and augmenting the human development index with institutional quality," Annals of Operations Research, Springer, vol. 315(1), pages 341-369, August.
    12. Guo, Xu & Post, Thierry & Wong, Wing-Keung & Zhu, Lixing, 2014. "Moment conditions for Almost Stochastic Dominance," Economics Letters, Elsevier, vol. 124(2), pages 163-167.
    13. Hooi Hooi Lean & Michael McAleer & Wing-Keung Wong, 2010. "Market Efficiency of Oil Spot and Futures: A Stochastic Dominance Approach," CIRJE F-Series CIRJE-F-705, CIRJE, Faculty of Economics, University of Tokyo.
    14. Sungro Lee, Chang Sik Kim, In-Moo Kim & Chang Sik Kim & In-Moo Kim, 2012. "Testing the Monday Effect using High-frequency Intraday Returns: A Spatial Dominance Approach," Korean Economic Review, Korean Economic Association, vol. 28, pages 69-90.
    15. Lean, H.H. & McAleer, M.J. & Wong, W.-K., 2010. "Investor preferences for oil spot and futures based on mean-variance and stochastic dominance," Econometric Institute Research Papers EI 2010-37, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. Zhihui Lv & Amanda M. Y. Chu & Wing Keung Wong & Thomas C. Chiang, 2021. "The maximum-return-and-minimum-volatility effect: evidence from choosing risky and riskless assets to form a portfolio," Risk Management, Palgrave Macmillan, vol. 23(1), pages 97-122, June.
    17. Sheung-Chi Chow & Ma. Rebecca Valenzuela & Wing-Keung Wong, 2016. "New Tests for Richness and Poorness:A Stochastic Dominance Analysis of Income Distributions in Hong Kong," Monash Economics Working Papers 25-16, Monash University, Department of Economics.
    18. Guo, Dongmei & Hu, Yi & Wang, Shouyang & Zhao, Lin, 2016. "Comparing risks with reference points: A stochastic dominance approach," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 105-116.
    19. Zagst, Rudi & Kraus, Julia & Bertrand, Philippe, 2019. "Option-Based performance participation," Journal of Banking & Finance, Elsevier, vol. 105(C), pages 44-61.
    20. Charles Beach, 2023. "Quantile Tool Box Measures for Empirical Analysis and for Testing Distributional Comparisons in Direct Distribution-Free Fashion," Working Paper 1508, Economics Department, Queen's University.

    More about this item

    Keywords

    Stochastic dominance; Utility theory; Risk aversion; Linear programming; Market portfolio efficiency; Asset pricing;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

    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:empfin:v:23:y:2013:i:c:p:187-190. 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/jempfin .

    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.