  In normal times, it is assumed that financial institutions operating in
non-overlapping sectors have complementary and distinct outcomes, typically
reflected in mostly uncorrelated outcomes and asset returns. Such is the
reasoning behind common "free lunches" to be had in investing, like
diversifying assets across equity and bond sectors. Unfortunately, the
recurrence of crises like the Great Financial Crisis of 2007-2008 demonstrate
that such convenient assumptions often break down, with dramatic consequences
for all financial actors. In hindsight, the emergence of systemic risk (as
exemplified by failure in one part of a system spreading to ostensibly
unrelated parts of the system) has been explained by narratives such as
deregulation and leverage. But can we diagnose and quantify the ongoing
emergence of systemic risk in financial systems? In this study, we focus on two
previously-documented measures of systemic risk that require only easily
available time series data (eg monthly asset returns): cross-correlation and
principal component analysis. We apply these tests to daily and monthly returns
on hedge fund indexes and broad-based market indexes, and discuss their
results. We hope that a frank discussion of these simple, non-parametric
measures can help inform legislators, lawmakers, and financial actors of
potential crises looming on the horizon.
