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

48 Pages Posted: 14 Feb 2019

See all articles by Matteo Barigozzi

Matteo Barigozzi

London School of Economics and Political Science

Marc Hallin

ECARES, Universite Libre de Bruxelles

Stefano Soccorsi

Department of Economics, Lancaster University Management School

Date Written: February 4, 2019

Abstract

Ripple effects in financial markets associated with crashes, systemic risk and contagion are characterized by non-trivial lead-lag dynamics which is crucial for understanding how crises spread and, therefore, central in risk management. In the spirit of Diebold and Yilmaz (2014), we investigate connectedness among financial firms via an analysis of impulse response functions of adjusted intraday log-ranges to market shocks involving network theory methods. Motivated by overwhelming evidence that the interdependence structure of financial markets is varying over time, we are basing that analysis on the so-called time-varying General Dynamic Factor Model proposed by Eichler et al. (2011), which extends to the locally stationary context the framework developed by Forni et al. (2000) under stationarity assumptions. The estimation methods in Eichler et al. (2011), how- ever, present the major drawback of involving two-sided filters which make it impossible to recover impulse response functions. We therefore introduce a novel approach extending to the time-varying context the one-sided method of Forni et al. (2017). The resulting estimators of time-varying impulse response functions are shown to be consistent, hence can be used in the analysis of (time-varying) connectedness. Our empirical analysis on a large and strongly comoving panel of intraday price ranges of US stocks indicates that large increases in mid to long-run connectedness are associated with the main financial turmoils.

Keywords: dynamic factor models, volatility, financial crises, contagion, financial connectedness, high-dimensional time series, panel data, time-varying models, local stationarity

JEL Classification: C32, C14

Suggested Citation

Barigozzi, Matteo and Hallin, Marc and Soccorsi, Stefano, Time-Varying General Dynamic Factor Models and the Measurement of Financial Connectedness (February 4, 2019). Available at SSRN: https://ssrn.com/abstract=3329445 or http://dx.doi.org/10.2139/ssrn.3329445

Matteo Barigozzi (Contact Author)

London School of Economics and Political Science ( email )

Houghton Street
London, England WC2A 2AE
United Kingdom

Marc Hallin

ECARES, Universite Libre de Bruxelles ( email )

Ave. Franklin D Roosevelt, 50 - C.P. 114
Brussels, B-1050
Belgium
+32 2 650 5886 (Phone)
+32 2 650 5899 (Fax)

Stefano Soccorsi

Department of Economics, Lancaster University Management School ( email )

Lancaster, LA1 4YX
United Kingdom

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