Time-Varying General Dynamic Factor Models and the Measurement of Financial Connectedness

Barigozzi, Matteo and Hallin, Marc and Soccorsi, Stefano and von Sachs, Rainer (2021) Time-Varying General Dynamic Factor Models and the Measurement of Financial Connectedness. Journal of Econometrics, 222 (1). pp. 324-343. ISSN 0304-4076

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We propose a new time-varying Generalized Dynamic Factor Model for high-dimensional, locally stationary time series. Estimation is based on dynamic principal component analysis jointly with singular VAR estimation, and extends to the locally stationary case the one-sided estimation method proposed by Forni et al. (2017) for stationary data. We prove consistency of our estimators of time-varying impulse response functions as both the sample size and the dimension of the time series grow to infinity. This approach is used in an empirical application in order to construct a time-varying measure of financial connectedness for a large panel of adjusted intra-day log ranges of stocks. We show that large increases in long-run connectedness are associated with the main financial turmoils. Moreover, we provide evidence of a significant heterogeneity in the dynamic responses to common shocks in time and over different scales, as well as across industrial sectors.

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Journal Article
Journal or Publication Title:
Journal of Econometrics
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This is the author’s version of a work that was accepted for publication in Journal of Econometrics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Econometrics, 222, 1, 2021 DOI: 10.1016/j.jeconom.2020.07.004
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27 Apr 2020 09:20
Last Modified:
17 Jan 2023 02:16