IDEAS home Printed from https://ideas.repec.org/a/afc/cliome/v5y2011i2p165-186.html
   My bibliography  Save this article

What can price volatility tell us about market efficiency? Conditional heteroscedasticity in historical commodity price series

Author

Listed:
  • Péter Földvári

    (Faculty of Economics and Business Administration, University of Debrecen, Debrecen, Hungary)

  • Bas van Leeuwen

    (Faculty of Humanities, Free University Amsterdam, Amsterdam, The Netherlands)

Abstract

The development in the working of markets has been an important topic in economic history for decades. The volatility of market prices is often used as an indicator of market efficiency in the broadest sense. Yet, the way in which volatility is estimated often makes it difficult to compare price volatility across regions or over time for two reasons. First, if prices are non-stationary, the variance is inflated. Second, the variance of commodity prices contains information on a number of region- and time-specific factors that are not related to market efficiency. Hence, the popular coefficient of variation and related indicators are not adequate measures of the efficiency of markets and are incomparable across regions. As a solution, we suggest using a conditional heteroscedasticity model to estimate the residual (conditional) variance of commodity prices. This measure reflects how markets react to unexpected events and can therefore be seen as a measure of market efficiency. Using this approach on grain prices from the Early Modern Pisa, Paris, Vienna, and Japan, we find that the residual price volatility had declined (and market efficiency increased) in the European markets in the late sixteenth century while it remained stable in Japan.

Suggested Citation

  • Péter Földvári & Bas van Leeuwen, 2011. "What can price volatility tell us about market efficiency? Conditional heteroscedasticity in historical commodity price series," Cliometrica, Journal of Historical Economics and Econometric History, Association Française de Cliométrie (AFC), vol. 5(2), pages 165-186, June.
  • Handle: RePEc:afc:cliome:v:5:y:2011:i:2:p:165-186
    DOI: 10.1007/s11698-010-0055-y
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1007/s11698-010-0055-y
    Download Restriction: Access to full text is restricted to journal subscribers

    File URL: https://libkey.io/10.1007/s11698-010-0055-y?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.

    Citations

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


    Cited by:

    1. Jalilov, Shokhrukh-Mirzo & Rahman, Wakilur & Palash, Salauddin & Jahan, Hasneen & Mainuddin, Mohammed & Ward, Frank A., 2022. "Exploring strategies to control the cost of food security: Evidence from Bangladesh," Agricultural Systems, Elsevier, vol. 196(C).
    2. van Zanden, Jan Luiten & Földvári, Péter & van Leeuwen, Bas, 2011. "Long-run patterns in market efficiency and the genesis of the market economy: Markets around the Mediterranean from Nebuchadnez," CEPR Discussion Papers 8521, C.E.P.R. Discussion Papers.
    3. G. Geoffrey Booth & Sanders S. Chang, 2017. "Domestic exchange rate determination in Renaissance Florence," Cliometrica, Springer;Cliometric Society (Association Francaise de Cliométrie), vol. 11(3), pages 405-445, September.
    4. Rafael, Dobado-González & Alfredo, García-Hiernaux & David, Guerrero-Burbano, 2013. "West versus East: Early Globalization and the Great Divergence," MPRA Paper 48773, University Library of Munich, Germany.

    More about this item

    Keywords

    Market efficiency; Conditional heteroscedasticity; Price volatility; Time-series analysis;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • N73 - Economic History - - Economic History: Transport, International and Domestic Trade, Energy, and Other Services - - - Europe: Pre-1913

    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:afc:cliome:v:5:y:2011:i:2:p:165-186. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/afcccea.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.