We propose a new time-varying Generalized Dynamic Factor Model for high-dimensional, locally stationary time series. Estimation is based on dynamic principal component ana- lysis 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 T and the dimension n 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 dierent scales, as well as across industrial sectors.
Matteo Barigozzi, Marc Hallin, Stefano Soccorsi, Rainer von Sachs (2021). Time-Varying General Dynamic Factor Models and the Measurement of Financial Connectedness. JOURNAL OF ECONOMETRICS, 222(Issue 1, Part B,), 324-343 [10.1016/j.jeconom.2020.07.004].
Time-Varying General Dynamic Factor Models and the Measurement of Financial Connectedness
Matteo Barigozzi;
2021
Abstract
We propose a new time-varying Generalized Dynamic Factor Model for high-dimensional, locally stationary time series. Estimation is based on dynamic principal component ana- lysis 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 T and the dimension n 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 dierent scales, as well as across industrial sectors.File | Dimensione | Formato | |
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BHSvS_April15_RvS.pdf
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