Economics at your fingertips  

Generalized dynamic factor models and volatilities: recovering the market volatility shocks

Matteo Barigozzi and Marc Hallin ()

Econometrics Journal, 2016, vol. 19, issue 1, C33-C60

Abstract: Decomposing volatilities into a common market‐driven component and an idiosyncratic item‐specific component is an important issue in financial econometrics. However, this requires the statistical analysis of large panels of time series, and hence faces the usual challenges associated with high‐dimensional data. Factor model methods in such a context are an ideal tool, but they do not readily apply to the analysis of volatilities. Focusing on the reconstruction of the unobserved market shocks and the way they are loaded by the various items (stocks) in the panel, we propose an entirely non‐parametric and model‐free two‐step general dynamic factor approach to the problem, which avoids the usual curse of dimensionality. Applied to the Standard & Poor's 100 asset return data set, the method provides evidence that a non‐negligible proportion of the market‐driven volatility of returns originates in the volatilities of the idiosyncratic components of returns.

Date: 2016
References: Add references at CitEc
Citations: View citations in EconPapers (31) Track citations by RSS feed

Downloads: (external link)

Related works:
Working Paper: Generalized dynamic factor models and volatilities: recovering the market volatility shocks (2015) Downloads
Working Paper: Generalized Dynamic Factor Models and Volatilities. Recovering the Market Volatility Shocks (2014) Downloads
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This journal article can be ordered from
http://onlinelibrary ... 1111/(ISSN)1368-423X

Access Statistics for this article

Econometrics Journal is currently edited by Jaap Abbring, Victor Chernozhukov, Michael Jansson and Dennis Kristensen

More articles in Econometrics Journal from Royal Economic Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().

Page updated 2022-01-18
Handle: RePEc:wly:emjrnl:v:19:y:2016:i:1:p:c33-c60