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.
Time-Varying General Dynamic Factor Models and the Measurement of Financial Connectedness / Matteo Barigozzi; Marc Hallin; Stefano Soccorsi; Rainer von Sachs. - In: JOURNAL OF ECONOMETRICS. - ISSN 0304-4076. - STAMPA. - 222:Issue 1, Part B,(2021), pp. 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 | |
---|---|---|---|
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.