IDEAS home Printed from https://ideas.repec.org/a/kap/annfin/v9y2013i4p589-610.html
   My bibliography  Save this article

A semi-Markov approach to the stock valuation problem

Author

Listed:
  • Guglielmo D’Amico

Abstract

In this paper, a general model is provided to evaluate a stock when the dividend growth rate is a discrete variable. This new dividend valuation model assumes that the dividend growth rate follows a finite state discrete time semi-Markov chain. An important consequence is that prices become duration dependent, i.e. they are influenced not only by the current state of the dividend growth process but also by the elapsed time in this state. This general valuation setting necessitates a more complex solution procedure with respect to the Markovian models. In fact, the valuation procedure of the semi-Markov model requires the solution of a system of first order linear difference equations with variable coefficients. The model is implemented by using experimental data freely available at http://www.econ.yale.edu/shiller/data.htm . The parameters of the model are estimated and the data strongly support the semi-Markov hypothesis of the dividend growth rate process. The paper generalizes previous contributions dealing with pricing firms on the basis of fundamentals. Copyright Springer-Verlag 2013

Suggested Citation

  • Guglielmo D’Amico, 2013. "A semi-Markov approach to the stock valuation problem," Annals of Finance, Springer, vol. 9(4), pages 589-610, November.
    • Handle: RePEc:kap:annfin:v:9:y:2013:i:4:p:589-610
    DOI: 10.1007/s10436-012-0206-1
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10436-012-0206-1
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10436-012-0206-1?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. Isabelle Distinguin & Iftekhar Hasan & Amine Tarazi, 2013. "Predicting rating changes for banks: how accurate are accounting and stock market indicators?," Annals of Finance, Springer, vol. 9(3), pages 471-500, August.
    2. Bradford Cornell & Jakša Cvitanić & Levon Goukasian, 2010. "Beliefs regarding fundamental value and optimal investing," Annals of Finance, Springer, vol. 6(1), pages 83-105, January.
    3. Paul A. Samuelson, 1973. "Proof That Properly Discounted Present Values of Assets Vibrate Randomly," Bell Journal of Economics, The RAND Corporation, vol. 4(2), pages 369-374, Autumn.
    4. repec:zbw:bofrdp:2012_015 is not listed on IDEAS
    5. Robert B. Barsky & J. Bradford De Long, 1993. "Why Does the Stock Market Fluctuate?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 108(2), pages 291-311.
    6. Brooks, Robert & Helms, Billy, 1990. "An N-Stage, Fractional Period, Quarterly Dividend Discount Model," The Financial Review, Eastern Finance Association, vol. 25(4), pages 651-657, November.
    7. Guglielmo D’Amico & Jacques Janssen & Raimondo Manca, 2010. "Initial and Final Backward and Forward Discrete Time Non-homogeneous Semi-Markov Credit Risk Models," Methodology and Computing in Applied Probability, Springer, vol. 12(2), pages 215-225, June.
    8. Donaldson, R Glen & Kamstra, Mark, 1996. "A New Dividend Forecasting Procedure That Rejects Bubbles in Asset Prices: The Case of 1929's Stock Crash," The Review of Financial Studies, Society for Financial Studies, vol. 9(2), pages 333-383.
    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. Guglielmo D'Amico & Riccardo De Blasis, 2020. "A review of the Dividend Discount Model: from deterministic to stochastic models," Papers 2001.00465, arXiv.org.
    2. Vlad Stefan Barbu & Guglielmo D’Amico & Riccardo Blasis, 2017. "Novel advancements in the Markov chain stock model: analysis and inference," Annals of Finance, Springer, vol. 13(2), pages 125-152, May.
    3. Guglielmo D'Amico, 2016. "Generalized semi-Markovian dividend discount model: risk and return," Papers 1605.02472, arXiv.org.
    4. Mark Kamstra, 2003. "Pricing firms on the basis of fundamentals," Economic Review, Federal Reserve Bank of Atlanta, vol. 88(Q1), pages 49-70.
    5. Angelos Kanas & Yue Ma, 2004. "Intrinsic bubbles revisited: evidence from nonlinear cointegration and forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(4), pages 237-250.
    6. Miguel A. Iraola & Manuel S. Santos, 2009. "Long Term Asset Price Volatility and Macroeconomic Fluctuations," Working Papers 2010-1, University of Miami, Department of Economics.
    7. Xiao, Zhijie, 2009. "Quantile cointegrating regression," Journal of Econometrics, Elsevier, vol. 150(2), pages 248-260, June.
    8. D'Amico, Guglielmo & De Blasis, Riccardo, 2024. "Dividend based risk measures: A Markov chain approach," Applied Mathematics and Computation, Elsevier, vol. 471(C).
    9. R. Glen Donaldson & Mark Kamstra, "undated". "Forecasting Fundamental Asset Return Distributions," Computing in Economics and Finance 1997 176, Society for Computational Economics.
    10. Foerster, Stephen R. & Sapp, Stephen G., 2011. "Back to fundamentals: The role of expected cash flows in equity valuation," The North American Journal of Economics and Finance, Elsevier, vol. 22(3), pages 320-343.
    11. Mark Kamstra, 2001. "Rational exuberance: The fundamentals of pricing firms, from blue chip to “dot com”," FRB Atlanta Working Paper 2001-21, Federal Reserve Bank of Atlanta.
    12. Raymond Tse & James Webb, 2008. "Housing markets in China: an empirical evaluation of present-value model," Journal of Chinese Economic and Business Studies, Taylor & Francis Journals, vol. 6(1), pages 67-75.
    13. Chow, Gregory C. & Fan, Zhao-zhi & Hu, Jin-yan, 1999. "Shanghai Stock Prices as Determined by the Present-Value Model," Journal of Comparative Economics, Elsevier, vol. 27(3), pages 553-561, September.
    14. Debdatta Pal & Subrata K. Mitra, 2017. "Diesel and soybean price relationship in the USA: evidence from a quantile autoregressive distributed lag model," Empirical Economics, Springer, vol. 52(4), pages 1609-1626, June.
    15. Bansal, Ravi & Lundblad, Christian, 2002. "Market efficiency, asset returns, and the size of the risk premium in global equity markets," Journal of Econometrics, Elsevier, vol. 109(2), pages 195-237, August.
    16. Rhys Bidder & Ian Dew-Becker, 2016. "Long-Run Risk Is the Worst-Case Scenario," American Economic Review, American Economic Association, vol. 106(9), pages 2494-2527, September.
    17. Robert C. Merton, 2006. "Paul Samuelson and Financial Economics," The American Economist, Sage Publications, vol. 50(2), pages 9-31, October.
    18. Thomas Delcey, 2019. "Samuelson vs Fama on the Efficient Market Hypothesis: The Point of View of Expertise [Samuelson vs Fama sur l’efficience informationnelle des marchés financiers : le point de vue de l’expertise]," Post-Print hal-01618347, HAL.
    19. Miguel Henry & George Judge, 2019. "Permutation Entropy and Information Recovery in Nonlinear Dynamic Economic Time Series," Econometrics, MDPI, vol. 7(1), pages 1-16, March.
    20. Hunt, Julien & Devolder, Pierre, 2011. "Semi Markov regime switching interest rate models and minimal entropy measure," LIDAM Discussion Papers ISBA 2011010, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).

    More about this item

    Keywords

    Fundamental valuation; Reward process; Difference equations; C02; G30;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • G30 - Financial Economics - - Corporate Finance and Governance - - - General

    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:kap:annfin:v:9:y:2013:i:4:p:589-610. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.