"Linkages between asset classes during the financial crisis, accounting for market microstructure 
noise and non-synchronous trading"

Nathaniel Frank
	Oxford-Man Institute and Department of Economics, University of Oxford
	
Abstract

In this paper we analyse market co-movements during the global financial
crisis. Using high frequency data and accounting for market microstructure
noise and non-synchronous trading, interdependencies between differing as-
set classes such as equity, FX, fixed income, commodity and energy securi-
ties are quantified. To this end multivariate realised kernels and GARCH
models are employed. We find that during the current period of market
dislocations and times of increased risk aversion, assets have become more
correlated when applying these intra-day measures. FX pairs seemingly lead
the other variables, but commodities remain entirely unaffected.

Keywords: Financial crisis, high frequency data, kernel based estimation

JEL Classification Numbers: C32, E44, G01