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An EM Algorithm for Conditionally Heteroskedastic Factor Models

Author

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  • Antonis Demos
  • Enrique Sentana

Abstract

This article discusses the application of the EM algorithm to factor models with dynamic heteroscedasticity in the common factors. It demonstrates that the EM algorithm reduces the computational burden so much that researchers can estimate such models with many series. Two empirical applications with 11 and 266 stock returns are presented, confirming that the EM algorithm yields significant speed gains and that it makes unnecessary the computation of good initial values. Near the optimum, however, it slows down significantly. Then, the best practical strategy is to switch to a first-derivative-based method.
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Suggested Citation

  • Antonis Demos & Enrique Sentana, 1996. "An EM Algorithm for Conditionally Heteroskedastic Factor Models," Working Papers wp1996_9615, CEMFI.
    • Handle: RePEc:cmf:wpaper:wp1996_9615
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    Cited by:

    1. Sentana, Enrique, 1995. "Risk and return in the Spanish stock market," LSE Research Online Documents on Economics 119179, London School of Economics and Political Science, LSE Library.
    2. Gabriele Fiorentini & Alessandro Galesi & Enrique Sentana, 2016. "Fast ML Estimation of Dynamic Bifactor Models: An Application to European Inflation," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 215-282, Emerald Group Publishing Limited.
    3. Antonis Demos & George Vasillelis, 2007. "U.K. Stock Market Inefficiencies and the Risk Premium," Multinational Finance Journal, Multinational Finance Journal, vol. 11(1-2), pages 97-122, March-Jun.
    4. Francis X. Diebold & Jose A. Lopez, 1995. "Measuring Volatility Dynamics," NBER Technical Working Papers 0173, National Bureau of Economic Research, Inc.
    5. Mohamed Saidane & Christian Lavergne, 2009. "Optimal Prediction with Conditionally Heteroskedastic Factor Analysed Hidden Markov Models," Computational Economics, Springer;Society for Computational Economics, vol. 34(4), pages 323-364, November.
    6. Antonis Demos & Sofia Parissi, 1998. "Testing Asset Pricing Models: The Case of Athens Stock Exchange," Multinational Finance Journal, Multinational Finance Journal, vol. 2(3), pages 189-223, September.
    7. Roberto S. Mariano & Yasutomo Murasawa, 2010. "A Coincident Index, Common Factors, and Monthly Real GDP," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(1), pages 27-46, February.
    8. Fiorentini, Gabriele & Galesi, Alessandro & Sentana, Enrique, 2018. "A spectral EM algorithm for dynamic factor models," Journal of Econometrics, Elsevier, vol. 205(1), pages 249-279.
    9. Gabriele Fiorentini & Enrique Sentana & Neil Shephard, 2004. "Likelihood-Based Estimation of Latent Generalized ARCH Structures," Econometrica, Econometric Society, vol. 72(5), pages 1481-1517, September.
    10. Enrique Sentana & Gabriele Fiorentini, 1997. "Identification, Estimation and Testing of Conditionally Heteroskedastic Factor Models.Versión Revisada," Working Papers wp1997_9709, CEMFI.
    11. Sentana, Enrique & Fiorentini, Gabriele, 2001. "Identification, estimation and testing of conditionally heteroskedastic factor models," Journal of Econometrics, Elsevier, vol. 102(2), pages 143-164, June.
    12. Mondher Bellalah & Marc Lavielle, 2002. "A Decomposition of Empirical Distributions with Applications to the Valuation of Derivative Assets," Multinational Finance Journal, Multinational Finance Journal, vol. 6(2), pages 99-130, June.
    13. Bernardi, Mauro & Costola, Michele, 2019. "High-dimensional sparse financial networks through a regularised regression model," SAFE Working Paper Series 244, Leibniz Institute for Financial Research SAFE.
    14. Dunne, Peter G., 1999. "Size and book-to-market factors in a multivariate GARCH-in-mean asset pricing application," International Review of Financial Analysis, Elsevier, vol. 8(1), pages 35-52.
    15. Enrique Sentana & Giorgio Calzolari & Gabriele Fiorentini, 2004. "Indirect Estimation of Conditionally Heteroskedastic Factor Models," Working Papers wp2004_0409, CEMFI.
    16. Jon Wongswan, 2003. "Contagion: an empirical test," International Finance Discussion Papers 775, Board of Governors of the Federal Reserve System (U.S.).

    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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