Modelling Financial Contagion Using High Frequency Data

This paper develops a methodology for detecting and measuring contagion using high frequency data which disentangles continuous and discontinuous price movements. We demonstrate its finite sample properties using Monte-Carlo simulation, focusing on the empirically plausible parameter space. Decisions to extend the role of financial regulation around the world to the supervision of insurers post-GFC has been met with literature which supports both the systemic importance of insurers and contrasting evidence that insurers are rather the 'victims' of shocks transmitted via banks. We contribute to this debate by considering the time-varying evidence for contagion at both the firm level and the sectorial level impacts. A number of insurance companies exhibits bank-like characteristics. Our evidence for contagion effects from banks to the real economy, with similar impact from the insurers, supports the view that financial regulation on banks does need to be extended to the insurance sector