Modelling Financial Contagion using High Frequency Data
We develop a methodology for detecting and measuring contagion using high frequency data which combines advances in estimating beta for both continuous and discontinuous price movements and frameworks for modelling the transmission of shocks developed for lower frequency data. We propose a two-stage estimation procedure, and show its satisfactory finite sample properties, especially in the empirically plausible parameter space. The empirical application contributes to the current debate over the role of insurance companies in transmitting financial crises. Using data from two major US banks and two insurers we assess contagion to other financial sector and real economy firms using US equity market data over the period of 2003-2011. The results enable us to reconcile the existing evidence that large banks have stronger contagion effects on the insurers than is evident in reverse, but that at a sectoral level this is difficult to discern. By showing that the contagion effects of a source bank and source insurer on real economy firms are not distinctly different we contribute to the growing literature which supports that the role of banks and insurers should be of interest to regulators tasked with protecting the real economy from systemic problems in the financial sector.
18.06.2015 | 17:00 c.t.
Raum 315, Garystraße 21, Berlin-Dahlem