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Logarithmic Preferences, Myopic Decisions, and Incomplete Information

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  • Feldman, David

Abstract

This paper examines a dynamic production economy with incomplete information and shows that the set of myopic preferences, those that induce myopic decisions, depends on the representation of the information flow. For example, logarithmic preferences are nonmyopic when some of the economic state variables are unobservable. The analysis offers a broader definition of myopic behavior, termed “generalized myopia,” which is independent of the representation of the information flow. Allowing for any smooth concave utility function, logarithmic preferences endogenously emerge as necessary for generalized myopia in incomplete information economies; and when combined with restrictions on the information structure, they become sufficient.

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  • Feldman, David, 1992. "Logarithmic Preferences, Myopic Decisions, and Incomplete Information," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 27(4), pages 619-629, December.
    • Handle: RePEc:cup:jfinqa:v:27:y:1992:i:04:p:619-629_00
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    Cited by:

    1. Lundtofte, Frederik, 2008. "Expected life-time utility and hedging demands in a partially observable economy," European Economic Review, Elsevier, vol. 52(6), pages 1072-1096, August.
    2. Kandel, Shmuel & Stambaugh, Robert F, 1996. "On the Predictability of Stock Returns: An Asset-Allocation Perspective," Journal of Finance, American Finance Association, vol. 51(2), pages 385-424, June.
    3. Suhan Altay & Katia Colaneri & Zehra Eksi, 2017. "Portfolio optimization for a large investor controlling market sentiment under partial information," Papers 1706.03567, arXiv.org.
    4. Honda, Toshiki, 2003. "Optimal portfolio choice for unobservable and regime-switching mean returns," Journal of Economic Dynamics and Control, Elsevier, vol. 28(1), pages 45-78, October.
    5. Basak, Suleyman, 2000. "A model of dynamic equilibrium asset pricing with heterogeneous beliefs and extraneous risk," Journal of Economic Dynamics and Control, Elsevier, vol. 24(1), pages 63-95, January.
    6. Jianjun Miao, 2009. "Ambiguity, Risk and Portfolio Choice under Incomplete Information," Annals of Economics and Finance, Society for AEF, vol. 10(2), pages 257-279, November.
    7. Hening Liu, 2011. "Dynamic portfolio choice under ambiguity and regime switching mean returns," Post-Print hal-00781344, HAL.
    8. Constantinos Kardaras & Hyeng Keun Koo & Johannes Ruf, 2022. "Estimation of growth in fund models," Papers 2208.02573, arXiv.org.
    9. Jacoby, Gady & Lee, Gemma & Paseka, Alexander & Wang, Yan, 2019. "Asset pricing with an imprecise information set," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 82-93.
    10. Soldatos, Gerasimos T., 2015. "Law, Coercion, And Socioeconomic Equilibrium," MPRA Paper 68953, University Library of Munich, Germany.
    11. Haim Kedar-Levy, 2004. "Learning the CAPM through Bubbles," Econometric Society 2004 Far Eastern Meetings 775, Econometric Society.
    12. Aditya Maheshwari & Andrey Sarantsev, 2018. "Modeling Financial System with Interbank Flows, Borrowing, and Investing," Risks, MDPI, vol. 6(4), pages 1-26, November.
    13. Haim Kedar-Levy, 2002. "Price Bubbles of New-Technology IPOs," Journal of Entrepreneurial Finance, Pepperdine University, Graziadio School of Business and Management, vol. 7(2), pages 11-32, Summer.
    14. Frederik Lundtofte, 2013. "The quality of public information and the term structure of interest rates," Review of Quantitative Finance and Accounting, Springer, vol. 40(4), pages 715-740, May.
    15. Xia, Yihong, 2000. "Learning About Predictability: The Effects of Parameter Uncertainty on Dynamic Asset Allocation," University of California at Los Angeles, Anderson Graduate School of Management qt3167f8mz, Anderson Graduate School of Management, UCLA.
    16. Tomas Björk & Mark Davis & Camilla Landén, 2010. "Optimal investment under partial information," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 71(2), pages 371-399, April.
    17. Ziegler, Alexandre, 2002. "State-price densities under heterogeneous beliefs, the smile effect, and implied risk aversion," European Economic Review, Elsevier, vol. 46(8), pages 1539-1557, September.
    18. Detemple, Jérôme, 1993. "Demande de portefeuille et politique de couverture de risque sous information incomplète," L'Actualité Economique, Société Canadienne de Science Economique, vol. 69(1), pages 45-70, mars.
    19. Lars Peter Hansen & Jianjun Miao, 2022. "Asset pricing under smooth ambiguity in continuous time," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 74(2), pages 335-371, September.
    20. Alexandre Ziegler, 2001. "Dividend Growth Uncertainty and Stock Prices," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 137(IV), pages 579-598, December.
    21. Brennan, Michael J & Xia, Yihong, 2001. "Assessing Asset Pricing Anomalies," The Review of Financial Studies, Society for Financial Studies, vol. 14(4), pages 905-942.
    22. David Feldman, 2007. "Incomplete information equilibria: Separation theorems and other myths," Annals of Operations Research, Springer, vol. 151(1), pages 119-149, April.
    23. Liu, Hening, 2011. "Dynamic portfolio choice under ambiguity and regime switching mean returns," Journal of Economic Dynamics and Control, Elsevier, vol. 35(4), pages 623-640, April.

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