IDEAS home Printed from https://ideas.repec.org/p/sce/scecf1/123.html
   My bibliography  Save this paper

G@RCH 2.0: An Ox Package for Estimating and Forecasting Various ARCH Models

Author

Listed:
  • S»bastien Laurent and Jean-Philippe Peters

Abstract

This paper discusses and documents G@RCH 2.0, an Ox package dedicated to the estimation and forecasting of various univariate ARCH-type models including the GARCH, EGARCH, GJR, APARCH, IGARCH, FIGARCH, FIEGARCH and FIAPARCH specifications of the conditional variance and an AR(FI)MA specification of the conditional mean. These models can be estimated by approximate (quasi-) maximum likelihood under four assumptions: normal, Student-t, GED, or skewed Student errors. Explanatory variables can enter both the conditional-mean and the conditional-variance equations. One-step-ahead (density) forecasts of both the conditional mean and variance are available as well as some misspecification tests and several graphical techniques.

Suggested Citation

  • S»bastien Laurent and Jean-Philippe Peters, 2001. "G@RCH 2.0: An Ox Package for Estimating and Forecasting Various ARCH Models," Computing in Economics and Finance 2001 123, Society for Computational Economics.
    • Handle: RePEc:sce:scecf1:123
    as

    Download full text from publisher

    File URL: http://www.eaa.egss.ulg.ac.be/rogp/peters/papers.html
    File Function: main text
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    (Density-) Forecasts; GARCH; Asymmetry; Long Memory; Ox; Econometric Software; Financial Time Series;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software

    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:sce:scecf1:123. 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: Christopher F. Baum (email available below). General contact details of provider: https://edirc.repec.org/data/sceeeea.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.