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.
2021
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].
Matteo Barigozzi; Marc Hallin; Stefano Soccorsi; Rainer von Sachs
File in questo prodotto:
File Dimensione Formato  
BHSvS_April15_RvS.pdf

Open Access dal 09/08/2022

Tipo: Postprint
Licenza: Licenza per Accesso Aperto. Creative Commons Attribuzione - Non commerciale - Non opere derivate (CCBYNCND)
Dimensione 1.2 MB
Formato Adobe PDF
1.2 MB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/763121
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 34
  • ???jsp.display-item.citation.isi??? 29
social impact