IDEAS home Printed from https://ideas.repec.org/p/ven/wpaper/201516.html
   My bibliography  Save this paper

Rational learning for risk-averse investors by conditioning on behavioral choices

Author

Listed:
  • Michele Costola

    (Department of Economics, University Of Venice C� Foscari)

  • Massimiliano Caporin

    (Department of Economics and Management, University Of Padova)

Abstract

We present a rational learner agent, which considers the information coming from a behavioral counterpart during the allocation process. The learner agent adopts a herding behaviour by conditioning her choice on the selection of the portfolio's constituents. The considered framework has therefore two types of agents with two different utility functions: the rational agent with a hyperbolic absolute risk aversion (HARA) utility function and the other one with a general behavioral utility function. We use the concept of performance measure related to utility functions to define agents' preferences: the higher the measure, the higher the expected utility of a given asset. The rational learner agent updates her information in a Bayesian manner similarly to the Black-Litterman model, which makes use of a weighting factor in blending the two components. We support our methodological framework with an empirical analysis including all the assets present in the NASDAQ and NYSE stock exchange from September 1977 to December 2014.

Suggested Citation

  • Michele Costola & Massimiliano Caporin, 2015. "Rational learning for risk-averse investors by conditioning on behavioral choices," Working Papers 2015:16, Department of Economics, University of Venice "Ca' Foscari".
    • Handle: RePEc:ven:wpaper:2015:16
    as

    Download full text from publisher

    File URL: https://www.unive.it/web/fileadmin/user_upload/dipartimenti/DEC/doc/Pubblicazioni_scientifiche/working_papers/2015/WP_DSE_caporin_costola_16_15.pdf
    File Function: First version, anno
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Zakamouline, Valeri & Koekebakker, Steen, 2009. "Portfolio performance evaluation with generalized Sharpe ratios: Beyond the mean and variance," Journal of Banking & Finance, Elsevier, vol. 33(7), pages 1242-1254, July.
    2. Costantini, Mauro & Crespo Cuaresma, Jesus & Hlouskova, Jaroslava, 2014. "Can Macroeconomists Get Rich Forecasting Exchange Rates?," Department of Economics Working Paper Series 176, WU Vienna University of Economics and Business.
    3. Victor DeMiguel & Lorenzo Garlappi & Raman Uppal, 2009. "Optimal Versus Naive Diversification: How Inefficient is the 1-N Portfolio Strategy?," The Review of Financial Studies, Society for Financial Studies, vol. 22(5), pages 1915-1953, May.
    4. Cerqueti, Roy & Costantini, Mauro, 2011. "Testing for rational bubbles in the presence of structural breaks: Evidence from nonstationary panels," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2598-2605, October.
    5. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    6. Meneu, Vicente & Pardo, Angel, 2004. "Pre-holiday effect, large trades and small investor behaviour," Journal of Empirical Finance, Elsevier, vol. 11(2), pages 231-246, March.
    7. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    8. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    9. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    10. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Working Papers 111, Princeton University, Department of Economics, Center for Economic Policy Studies..
    11. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    12. Christian Pedersen & Stephen Satchell, 2002. "On the foundation of performance measures under asymmetric returns," Quantitative Finance, Taylor & Francis Journals, vol. 2(3), pages 217-223.
    13. repec:pri:cepsud:91malkiel is not listed on IDEAS
    14. Massimiliano Caporin & Luca Corazzini & Michele Costola, 2014. "Measuring the Behavioral Component of Financial Fluctuations: An Analysis Based on the S&P 500," CREATES Research Papers 2014-33, Department of Economics and Business Economics, Aarhus University.
    15. Hayette Gatfaoui, 2010. "Deviation from normality and Sharpe ratio behavior: a brief simulation study," Post-Print hal-00568613, HAL.
    16. Shefrin, Hersh & Statman, Meir, 2000. "Behavioral Portfolio Theory," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 35(2), pages 127-151, June.
    17. David E. Bell, 1985. "Disappointment in Decision Making Under Uncertainty," Operations Research, INFORMS, vol. 33(1), pages 1-27, February.
    18. Mehra, Rajnish & Prescott, Edward C., 1985. "The equity premium: A puzzle," Journal of Monetary Economics, Elsevier, vol. 15(2), pages 145-161, March.
    19. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186, Elsevier.
    20. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    21. Aleš Černý, 2003. "Generalised Sharpe Ratios and Asset Pricing in Incomplete Markets," Review of Finance, European Finance Association, vol. 7(2), pages 191-233.
    22. Billio, Monica & Caporin, Massimiliano & Costola, Michele, 2015. "Backward/forward optimal combination of performance measures for equity screening," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 63-83.
    23. Brad M. Barber & Terrance Odean, 2001. "The Internet and the Investor," Journal of Economic Perspectives, American Economic Association, vol. 15(1), pages 41-54, Winter.
    24. Burton G. Malkiel, 2003. "The Efficient Market Hypothesis and Its Critics," Journal of Economic Perspectives, American Economic Association, vol. 17(1), pages 59-82, Winter.
    25. Luisa Tibiletti & Simone Farinelli, 2003. "Upside and downside risk with a benchmark," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 31(4), pages 387-387, December.
    26. Garber, Peter M, 1990. "Famous First Bubbles," Journal of Economic Perspectives, American Economic Association, vol. 4(2), pages 35-54, Spring.
    27. Owen A. Lamont & Richard H. Thaler, 2003. "Anomalies: The Law of One Price in Financial Markets," Journal of Economic Perspectives, American Economic Association, vol. 17(4), pages 191-202, Fall.
    28. Hoffmann, Arvid O.I. & Post, Thomas & Pennings, Joost M.E., 2013. "Individual investor perceptions and behavior during the financial crisis," Journal of Banking & Finance, Elsevier, vol. 37(1), pages 60-74.
    29. 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.
    30. Milton Friedman & L. J. Savage, 1948. "The Utility Analysis of Choices Involving Risk," Journal of Political Economy, University of Chicago Press, vol. 56(4), pages 279-279.
    31. Kobberling, Veronika & Wakker, Peter P., 2005. "An index of loss aversion," Journal of Economic Theory, Elsevier, vol. 122(1), pages 119-131, May.
    32. Cass, David & Stiglitz, Joseph E., 1970. "The structure of investor preferences and asset returns, and separability in portfolio allocation: A contribution to the pure theory of mutual funds," Journal of Economic Theory, Elsevier, vol. 2(2), pages 122-160, June.
    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. Massimiliano Caporin & Luca Corazzini & Michele Costola, 2014. "Measuring the Behavioral Component of Financial Fluctuations: An Analysis Based on the S&P 500," CREATES Research Papers 2014-33, Department of Economics and Business Economics, Aarhus University.
    2. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.
    3. Sheriffdeen A. Tella & Olumuyiwa G. Yinusa & Ayinde Taofeek Olusola & Saban Celik, 2011. "Global Economic Crisis And Stock Markets Efficiency: Evidence From Selected Africa Countries," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 25(1), pages 139-169.
    4. Bennett, Donyetta & Mekelburg, Erik & Williams, T.H., 2023. "BeFi meets DeFi: A behavioral finance approach to decentralized finance asset pricing," Research in International Business and Finance, Elsevier, vol. 65(C).
    5. Nathan Jensen, 2007. "International institutions and market expectations: Stock price responses to the WTO ruling on the 2002 U.S. steel tariffs," The Review of International Organizations, Springer, vol. 2(3), pages 261-280, September.
    6. Huber, Christoph & Kirchler, Michael, 2023. "Experiments in finance: A survey of historical trends," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    7. Szafarz, Ariane, 2012. "Financial crises in efficient markets: How fundamentalists fuel volatility," Journal of Banking & Finance, Elsevier, vol. 36(1), pages 105-111.
    8. He, Xue-Zhong & Li, Youwei, 2015. "Testing of a market fraction model and power-law behaviour in the DAX 30," Journal of Empirical Finance, Elsevier, vol. 31(C), pages 1-17.
    9. Chang, C-L. & Hsu, S.-H. & McAleer, M.J., 2018. "Asymmetric Risk Impacts of Chinese Tourists to Taiwan," Econometric Institute Research Papers EI2018-18, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    10. Chia-Lin Chang & Jukka Ilomäki & Hannu Laurila & Michael McAleer, 2018. "Long Run Returns Predictability and Volatility with Moving Averages," Risks, MDPI, vol. 6(4), pages 1-18, September.
    11. Taufiq Choudhry & Ranadeva Jayasekera, 2015. "Level of efficiency in the UK equity market: empirical study of the effects of the global financial crisis," Review of Quantitative Finance and Accounting, Springer, vol. 44(2), pages 213-242, February.
    12. Saggese, Pietro & Belmonte, Alessandro & Dimitri, Nicola & Facchini, Angelo & Böhme, Rainer, 2023. "Arbitrageurs in the Bitcoin ecosystem: Evidence from user-level trading patterns in the Mt. Gox exchange platform," Journal of Economic Behavior & Organization, Elsevier, vol. 213(C), pages 251-270.
    13. Antonio Díaz & Carlos Esparcia, 2021. "Dynamic optimal portfolio choice under time-varying risk aversion," International Economics, CEPII research center, issue 166, pages 1-22.
    14. Chia-Lin Chang & Jukka Ilomäki & Hannu Laurila & Michael McAleer, 2018. "Moving Average Market Timing in European Energy Markets: Production Versus Emissions," Energies, MDPI, vol. 11(12), pages 1-24, November.
    15. Christopher R. Stephens & Harald A. Benink & José Luís Gordillo & Juan Pablo Pardo-Guerra, 2021. "A New Measure of Market Inefficiency," JRFM, MDPI, vol. 14(6), pages 1-22, June.
    16. Leopoldo S'anchez-Cant'u & Carlos Arturo Soto-Campos & Andriy Kryvko, 2016. "Evidence of Self-Organization in Time Series of Capital Markets," Papers 1604.03996, arXiv.org, revised Mar 2017.
    17. Paul Handro & Bogdan Dima, 2024. "Analyzing Financial Markets Efficiency: Insights from a Bibliometric and Content Review," Journal of Financial Studies, Institute of Financial Studies, vol. 16(9), pages 119-175, May.
    18. Yang, Yanlin & Hu, Xuemei & Jiang, Huifeng, 2022. "Group penalized logistic regressions predict up and down trends for stock prices," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    19. Guillaume Coqueret, 2016. "Empirical properties of a heterogeneous agent model in large dimensions," Post-Print hal-02088097, HAL.
    20. Xue-Zhong He & Youwei Li, 2017. "The adaptiveness in stock markets: testing the stylized facts in the DAX 30," Journal of Evolutionary Economics, Springer, vol. 27(5), pages 1071-1094, November.

    More about this item

    Keywords

    learner agent; investment decision; behavioral agents; Bayesian updating.;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:ven:wpaper:2015:16. 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: Sassano Sonia (email available below). General contact details of provider: https://edirc.repec.org/data/dsvenit.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.