IDEAS home Printed from https://ideas.repec.org/a/bla/jtsera/v26y2005i2p251-278.html
   My bibliography  Save this article

Local Likelihood for non-parametric ARCH(1) models

Author

Listed:
  • Francesco Audrino

Abstract

We propose a non-parametric local likelihood estimator for the log-transformed autoregressive conditional heteroscedastic (ARCH) (1) model. Our non-parametric estimator is constructed within the likelihood framework for non-Gaussian observations: it is different from standard kernel regression smoothing, where the innovations are assumed to be normally distributed. We derive consistency and asymptotic normality for our estimators and show, by a simulation experiment and some real-data examples, that the local likelihood estimator has better predictive potential than classical local regression. A possible extension of the estimation procedure to more general multiplicative ARCH(p) models with p > 1 predictor variables is also described. Copyright 2005 Blackwell Publishing Ltd.

Suggested Citation

  • Francesco Audrino, 2005. "Local Likelihood for non-parametric ARCH(1) models," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(2), pages 251-278, March.
  • Handle: RePEc:bla:jtsera:v:26:y:2005:i:2:p:251-278
    as

    Download full text from publisher

    File URL: http://www.blackwell-synergy.com/servlet/useragent?func=synergy&synergyAction=showTOC&journalCode=jtsa&volume=26&issue=2&year=2005&part=null
    File Function: link to full text
    Download Restriction: Access to full text is restricted to subscribers.

    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. Bauer, Dietmar & Wagner, Martin, 2002. "Estimating cointegrated systems using subspace algorithms," Journal of Econometrics, Elsevier, vol. 111(1), pages 47-84, November.
    2. Kapetanios, George, 2004. "A note on modelling core inflation for the UK using a new dynamic factor estimation method and a large disaggregated price index dataset," Economics Letters, Elsevier, vol. 85(1), pages 63-69, October.
    3. Kascha, Christian & Mertens, Karel, 2009. "Business cycle analysis and VARMA models," Journal of Economic Dynamics and Control, Elsevier, vol. 33(2), pages 267-282, February.
    4. Christian Schumacher, 2007. "Forecasting German GDP using alternative factor models based on large datasets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(4), pages 271-302.
    5. Alfredo García-Hiernaux & José Casals & Miguel Jerez, 2012. "Estimating the system order by subspace methods," Computational Statistics, Springer, vol. 27(3), pages 411-425, September.
    6. Dietmar Bauer, 2005. "Comparing the CCA Subspace Method to Pseudo Maximum Likelihood Methods in the case of No Exogenous Inputs," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(5), pages 631-668, September.
    7. Alfredo García Hiernaux & José Casals Carro & Miguel Jerez, 2005. "Fast estimation methods for time series models in state-space form," Documentos de Trabajo del ICAE 0504, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    8. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    9. Bauer, Dietmar, 2005. "Estimating Linear Dynamical Systems Using Subspace Methods," Econometric Theory, Cambridge University Press, vol. 21(01), pages 181-211, February.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Francesco Audrino & Peter Bühlmann, 2009. "Splines for financial volatility," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(3), pages 655-670.

    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:bla:jtsera:v:26:y:2005:i:2:p:251-278. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0143-9782 .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.