A0439
Title: Global bank network connectedness revisited: What is common, idiosyncratic and when
Authors: Luca Margaritella - Lund University (Sweden) [presenting]
Jonas Krampe - Cornell University (United States)
Abstract: The problem of estimating high-dimensional global bank network connectedness, both in the time and frequency domain, is revisited. Instead of directly regularizing the high-dimensional vector of realized volatilities as in Demirer et al. (2018), we estimate a dynamic factor model with sparse VAR idiosyncratic components. This allows to disentangle: (I) the part of system-wide connectedness (SWC) due to the common component shocks (the banking market), and (II) the part due to the idiosyncratic shocks(the single banks). Via spectral density estimation, SWC, (I) and (II) can be further decomposed into short (S), medium (M), long (L) frequency responses to shocks. We employ both the original dataset as in Demirer et al. (2018) (daily data, 2003-2013), as well as a more recent vintage (2014-2023). For both, we compute SWC due to (I), (II), (I+II) and (S=monthly), (M=quarterly), (L=yearly), providing bootstrap confidence bands. We find SWC to spike upward during global crises, disentangling how this is primarily driven by (I), (S). In normal times instead, SWC is primarily driven by (II), (M).
