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Indirect estimation of large conditionally heteroskedastic factor models, with an application to the Dow 30 stocks

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  • Sentana, Enrique
  • Calzolari, Giorgio
  • Fiorentini, Gabriele

Abstract

We derive indirect estimators of conditionally heteroskedastic factor models in which the volatilities of common and idiosyncratic factors depend on their past unobserved values by calibrating the score of a Kalman-filter approximation with inequality constraints on the auxiliary model parameters. We also propose alternative indirect estimators for large-scale models, and explain how to apply our procedures to many other dynamic latent variable models. We analyse the small sample behaviour of our indirect estimators and several likelihood-based procedures through an extensive Monte Carlo experiment with empirically realistic designs. Finally, we apply our procedures to weekly returns on the Dow 30 stocks.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 146 (2008)
Issue (Month): 1 (September)
Pages: 10-25

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Handle: RePEc:eee:econom:v:146:y:2008:i:1:p:10-25

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Web page: http://www.elsevier.com/locate/jeconom

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Keywords: ARCH Idiosyncratic risk Inequality constraints Kalman filter Sequential estimators Simulation estimators Volatility;

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Citations

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Cited by:
  1. Gabriele Fiorentini & Giorgio Calzolari & Enrique Sentana, 2007. "Indirect estimation of large conditionally heteroskedastic factor models, with an application to the Dow 30 stocks," Working Paper Series 40-07, The Rimini Centre for Economic Analysis, revised Jul 2007.
  2. Stelios Arvanitis & Antonis Demos, 2014. "On the Validity of Edgeworth Expansions and Moment Approximations for Three Indirect Inference Estimators," DEOS Working Papers 1406, Athens University of Economics and Business.
  3. Sirio Aramonte & Marius del Giudice Rodriguez & Jason J. Wu, 2011. "Dynamic factor value-at-risk for large, heteroskedastic portfolios," Finance and Economics Discussion Series 2011-19, Board of Governors of the Federal Reserve System (U.S.).
  4. Gabriele Fiorentini & Enrique Sentana, 2012. "Tests For Serial Dependence In Static, Non-Gaussian Factor Models," Working Papers wp2012_1211, CEMFI.
  5. Gabriele Fiorentini & Enrique Sentana, 2009. "Dynamic Specification Tests For Static Factor Models," Working Papers wp2009_0912, CEMFI.
  6. Araújo, Fabio & Issler, João Victor, 2011. "A Stochastic discount factor approach to asset pricing using panel data asymptotics," Economics Working Papers (Ensaios Economicos da EPGE) 717, FGV/EPGE Escola Brasileira de Economia e Finanças, Getulio Vargas Foundation (Brazil).
  7. Francesco Audrino & Fulvio Corsi & Kameliya Filipova, 2010. "Bond Risk Premia Forecasting: A Simple Approach for Extracting¨Macroeconomic Information from a Panel of Indicators," University of St. Gallen Department of Economics working paper series 2010 2010-09, Department of Economics, University of St. Gallen.

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