IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v21y1973i6p1183-1199.html
   My bibliography  Save this article

The Behavior of Stock-Price Relatives—A Markovian Analysis

Author

Listed:
  • Bruce D. Fielitz

    (Georgia State University, Atlanta, Georgia)

  • T. N. Bhargava

    (Kent Stale University, Kent, Ohio)

Abstract

This paper presents a method of Markovian analysis of changes in the natural logarithms of stock prices over time. It examines 200 stocks from the New York Stock Exchange for the period December 23, 1963, to November 29, 1968, and defines a set of three states (up, down, small change) for the process in terms of the mean absolute deviation of changes in the natural logarithms of prices. This definition of the set of states allows both the magnitude and the direction of change to be incorporated in the analysis. Standard statistical tests for stationarity and dependence in vector and individual-process Markov-chain models are employed for both fixed- and variable-time data (the latter refers to highs for a day or week interval). In addition, a method for testing the homogeneity of the vector Markov chain is given. Empirical results for the vector-process model suggest that price movements appear to be described by a first- or higher-order nonstationary Markov chain. Tests also indicate that the vector-process Markov chain is heterogeneous. Empirical results for the individual-process Markov-chain model suggest that an individual stock has a short-term memory with respect to daily price relatives, i.e., the process is first-or higher-order. However, the corresponding process lacks stationarity. No dependency appears to exist for a weekly time lag.

Suggested Citation

  • Bruce D. Fielitz & T. N. Bhargava, 1973. "The Behavior of Stock-Price Relatives—A Markovian Analysis," Operations Research, INFORMS, vol. 21(6), pages 1183-1199, December.
  • Handle: RePEc:inm:oropre:v:21:y:1973:i:6:p:1183-1199
    DOI: 10.1287/opre.21.6.1183
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.21.6.1183
    Download Restriction: no

    File URL: https://libkey.io/10.1287/opre.21.6.1183?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
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Flavio Ivo Riedlinger & João Nicolau, 2020. "The Profitability in the FTSE 100 Index: A New Markov Chain Approach," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(1), pages 61-81, March.

    More about this item

    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:inm:oropre:v:21:y:1973:i:6:p:1183-1199. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.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.