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An EM Algorithm for Conditionally Heteroskedastic Factor Models

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Author Info
Demos, A
Sentana, E

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Abstract

This paper discusses the application of the EM algorithm for maximum likelihood estimation of factor models with conditional heteroskedasticity in the common factors.

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Publisher Info
Paper provided by Centro de Estudios Monetarios Y Financieros- in its series Papers with number 9615.

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Length: 31 pages
Date of creation: 1996
Date of revision:
Handle: RePEc:fth:cemfdt:9615

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Related research
Keywords: STATISTICS;

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Find related papers by JEL classification:
C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation

Cited by:
(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Enrique Sentana & Giorgio Calzolari & Gabriele Fiorentini, 2004. "Indirect Estimation Of Conditionally Heteroskedastic Factor Models," Working Papers wp2004_0409, CEMFI. [Downloadable!]
  2. Gabriele Fiorentini & Enrique Sentana & Neil Shephard, 2004. "Likelihood-based estimation of latent generalised ARCH structures," OFRC Working Papers Series 2004fe02, Oxford Financial Research Centre. [Downloadable!]
    Other versions:
  3. Francis X. Diebold & Jose A. Lopez, 1995. "Measuring Volatility Dynamics," NBER Technical Working Papers 0173, National Bureau of Economic Research, Inc. [Downloadable!] (restricted)
  4. Jon Wongswan, 2003. "Contagion: an empirical test," International Finance Discussion Papers 775, Board of Governors of the Federal Reserve System (U.S.). [Downloadable!]
Statistics
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This page was last updated on 2009-11-20.

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