Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/34771
Title: Volatility of stock price as predicted by patent data : an MGARCH perspective
Authors: Chow, WW
Fung, MK 
Keywords: Multivariate GARCH
Reversible jump MCMC
Innovation
Patents
Value-at-risk
Issue Date: 2008
Publisher: North-Holland
Source: Journal of empirical Finance, 2008, v. 15, no. 1, p. 64-79 How to cite?
Journal: Journal of empirical finance 
Abstract: This paper proposes to model stock price volatility and variations in innovation effort using a Multivariate GARCH structure designed to extract information for risk prediction. The salient feature is that the model order, alongside other parameters, is endogenously determined by the estimation procedures. Using stock prices of U.S. computer firms, it is found that the model can pick up the correlation between the two variables and aid in producing accurate Value-at-Risk estimates.
URI: http://hdl.handle.net/10397/34771
ISSN: 0927-5398
DOI: 10.1016/j.jempfin.2006.10.003
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