IDEAS home Printed from https://ideas.repec.org/p/zbw/sfb373/199947.html
   My bibliography  Save this paper

Weekday dependence of German stock market returns

Author

Listed:
  • Herwartz, Helmut

Abstract

The so-called 'Monday effect ' has been found for various stock markets of the world. The empirical finding that Monday returns are significantly smaller than returns measured for the remaining days of the week calls the efficiency hypothesis for pricing processes operating on stock markets into question. Investigating an index series measured at the Frankfurt stock exchange the paper compares estimation results of parametric and nonparametric autoregressive models with respect to possible weekday dependence of return data. Allowing for heteroskedastic error distributions the wild bootstrap is used to infer against time varying means and correlation of return data in parametric models and to obtain confidence bands for nonparametric estimates. It is shown that time dependence is an important feature describing the dynamics of German stock market returns in the period 1960-79. Within two subsamples obtained from the period 1980-97 the evidence in favour of such effects is mitigated substantially.

Suggested Citation

  • Herwartz, Helmut, 1999. "Weekday dependence of German stock market returns," SFB 373 Discussion Papers 1999,47, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  • Handle: RePEc:zbw:sfb373:199947
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/61702/1/72228120X.pdf
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Hafner, Christian M. & Herwartz, Helmut, 2001. "Option pricing under linear autoregressive dynamics, heteroskedasticity, and conditional leptokurtosis," Journal of Empirical Finance, Elsevier, vol. 8(1), pages 1-34, March.
    2. Fatima Syed & Naimat U. Khan, 2017. "Islamic Calendar Anomalies: Evidence from Pakistan," Business & Economic Review, Institute of Management Sciences, Peshawar, Pakistan, vol. 9(3), pages 104-122, September.

    More about this item

    Keywords

    Periodic models; weekday effects; wild bootstrap; nonparametric autoregression;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:zbw:sfb373:199947. 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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/sfhubde.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.