Factor Stochastic Volatility in Mean Models: A GMM Approach
AbstractThis paper provides a semiparametric framework for modeling multivariate conditional heteroskedasticity. We put forward latent stochastic volatility (SV) factors as capturing the commonality in the joint conditional variance matrix of asset returns. This approach is in line with common features as studied by Engle and Kozicki (1993), and it allows us to focus on identication of factors and factor loadings through first- and second-order conditional moments only. We assume that the time-varying part of risk premiums is based on constant prices of factor risks, and we consider a factor SV in mean model. Additional specification of both expectations and volatility of future volatility of factors provides conditional moment restrictions, through which the parameters of the model are all identied. These conditional moment restrictions pave the way for instrumental variables estimation and GMM inference.
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Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Econometric Reviews.
Volume (Year): 25 (2006)
Issue (Month): 2-3 ()
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- 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.
- Sentana, Enrique & Calzolari, Giorgio & Fiorentini, Gabriele, 2008. "Indirect estimation of large conditionally heteroskedastic factor models, with an application to the Dow 30 stocks," Journal of Econometrics, Elsevier, vol. 146(1), pages 10-25, September.
- M. Hashem Pesaran & Paolo Zaffaroni, 2009. "Optimality and Diversifiability of Mean Variance and Arbitrage Pricing Portfolios," CESifo Working Paper Series 2857, CESifo Group Munich.
- Peter Boswijk, H. & van der Weide, Roy, 2011. "Method of moments estimation of GO-GARCH models," Journal of Econometrics, Elsevier, vol. 163(1), pages 118-126, July.
- Dovonon, Prosper & Renault, Eric, 2011. "Testing for Common GARCH Factors," MPRA Paper 40224, University Library of Munich, Germany.
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