IDEAS home Printed from https://ideas.repec.org/p/hal/journl/hal-01127790.html
   My bibliography  Save this paper

Predicting Stock Returns in the Capital Asset Pricing Model Using Quantile Regression and Belief Functions

Author

Listed:
  • K Autchariyapanitkul

    (CMU - Chiang Mai University)

  • S Chanaim

    (CMU - Chiang Mai University)

  • S Sriboonchitta

    (CMU - Chiang Mai University)

  • T Denoeux

    (Heudiasyc - Heuristique et Diagnostic des Systèmes Complexes [Compiègne] - UTC - Université de Technologie de Compiègne - CNRS - Centre National de la Recherche Scientifique, Labex MS2T - Laboratoire d'Excellence "Maîtrise des Systèmes de Systèmes Technologiques" - UTC - Université de Technologie de Compiègne - CNRS - Centre National de la Recherche Scientifique)

Abstract

We consider an inference method for prediction based on belief functions in quantile regression with an asymmetric Laplace distribution. We apply this method to the capital asset pricing model to estimate the beta coefficient and measure volatility under various market conditions at given quantiles. Likelihood-based belief functions are constructed from historical data of the securities in the S&P500 market. The results give us evidence on the systematic risk, in the form of a consonant belief function specified from the asymmetric Laplace distribution likelihood function given recorded data. Finally, we use the method to forecast the return of an individual stock.

Suggested Citation

  • K Autchariyapanitkul & S Chanaim & S Sriboonchitta & T Denoeux, 2014. "Predicting Stock Returns in the Capital Asset Pricing Model Using Quantile Regression and Belief Functions," Post-Print hal-01127790, HAL.
    • Handle: RePEc:hal:journl:hal-01127790
    DOI: 10.1007/978-3-319-11191-9_24
    Note: View the original document on HAL open archive server: https://hal.science/hal-01127790
    as

    Download full text from publisher

    File URL: https://hal.science/hal-01127790/document
    Download Restriction: no
    File URL: https://libkey.io/10.1007/978-3-319-11191-9_24?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
    ---><---

    References listed on IDEAS

    as
    1. Linden, Mikael, 2001. "A Model for Stock Return Distribution," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 6(2), pages 159-169, April.
    2. Koenker, Roger & Bassett, Gilbert, Jr, 1982. "Robust Tests for Heteroscedasticity Based on Regression Quantiles," Econometrica, Econometric Society, vol. 50(1), pages 43-61, January.
    3. Michelle L. Barnes & Anthony W. Hughes, 2002. "A quantile regression analysis of the cross section of stock market returns," Working Papers 02-2, Federal Reserve Bank of Boston.
    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. Thomas Q. Pedersen, 2015. "Predictable Return Distributions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(2), pages 114-132, March.
    2. Vighneswara Swamy & M. Dharani, 2020. "RETRACTED ARTICLE: Google Search Intensity and the Investor Attention Effect: A Quantile Regression Approach," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 18(2), pages 403-423, June.
    3. Baur, Dirk G. & Schulze, Niels, 2009. "Financial market stability--A test," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(3), pages 506-519, July.
    4. Swamy, Vighneswara & Dharani, M. & Takeda, Fumiko, 2019. "Investor attention and Google Search Volume Index: Evidence from an emerging market using quantile regression analysis," Research in International Business and Finance, Elsevier, vol. 50(C), pages 1-17.
    5. Rajesh K. Aggarwal & Andrew A. Samwick, 1999. "Executive Compensation, Strategic Competition, and Relative Performance Evaluation: Theory and Evidence," Journal of Finance, American Finance Association, vol. 54(6), pages 1999-2043, December.
    6. Peracchi, Franco, 2002. "On estimating conditional quantiles and distribution functions," Computational Statistics & Data Analysis, Elsevier, vol. 38(4), pages 433-447, February.
    7. Park, Donghyun & Xiao, Qin, 2009. "Housing Prices and the Role of Speculation: The Case of Seoul," ADB Economics Working Paper Series 146, Asian Development Bank.
    8. Rodríguez, Mª Araceli, 2005. "Nueva Evidencia Empírica sobre las Turbulencias Cambiarias de la Peseta Española. 1989-1998/New Evidence about Turbulences on the Spanish Peseta. 1989-1998s," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 23, pages 207-230, Abril.
    9. Peoples, James & Talley, Wayne K. & Thanabordeekij, Pithoon, 2006. "Shipping Deregulation's Wage Effect on Low and High Wage Dockworkers," Research in Transportation Economics, Elsevier, vol. 16(1), pages 219-249, January.
    10. Tsimpanos, Apostolos & Tsimbos, Cleon & Kalogirou, Stamatis, 2018. "Assessing spatial variation and heterogeneity of fertility in Greece at local authority level," MPRA Paper 100406, University Library of Munich, Germany.
    11. Narula, Subhash C. & Wellington, John F. & Lewis, Stephen A., 2012. "Valuating residential real estate using parametric programming," European Journal of Operational Research, Elsevier, vol. 217(1), pages 120-128.
    12. Enno Siemsen & Kenneth A. Bollen, 2007. "Least Absolute Deviation Estimation in Structural Equation Modeling," Sociological Methods & Research, , vol. 36(2), pages 227-265, November.
    13. Markus Haas & Stefan Mittnik & Marc Paolella, 2006. "Modelling and predicting market risk with Laplace-Gaussian mixture distributions," Applied Financial Economics, Taylor & Francis Journals, vol. 16(15), pages 1145-1162.
    14. Malik, Saif Ullah & Elahi, Muhammad Ather, 2014. "Analysis of Herd Behavior Using Quantile Regression: Evidence from Karachi Stock Exchange (KSE)," MPRA Paper 55322, University Library of Munich, Germany.
    15. Zangin Zeebari & Ghazi Shukur, 2023. "On The Least Absolute Deviations Method for Ridge Estimation of Sure Models," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 52(14), pages 4773-4791, July.
    16. Pedro Telhado Pereira & Pedro Silva Martins, 2000. "Does education reduce wage inequality? Quantile regressions evidence from fifteen European countries," Nova SBE Working Paper Series wp379, Universidade Nova de Lisboa, Nova School of Business and Economics.
    17. Omar Arias & Gustavo Yamada & Luis Tejerina, 2004. "Education, family background and racial earnings inequality in Brazil," International Journal of Manpower, Emerald Group Publishing Limited, vol. 25(3/4), pages 355-374, April.
    18. Martin F. Grace & J. Tyler Leverty, 2010. "Political Cost Incentives for Managing the Property‐Liability Insurer Loss Reserve," Journal of Accounting Research, Wiley Blackwell, vol. 48(1), pages 21-49, March.
    19. Nguyen, Huu Manh & Bakry, Walid & Vuong, Thi Huong Giang, 2023. "COVID-19 pandemic and herd behavior: Evidence from a frontier market," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).
    20. David E. Allen & Abhay K. Singh & Robert J. Powell & Michael McAleer & James Taylor & Lyn Thomas, 2013. "Return-Volatility Relationship: Insights from Linear and Non-Linear Quantile Regression," Tinbergen Institute Discussion Papers 13-020/III, Tinbergen Institute.

    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:hal:journl:hal-01127790. 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.