  This paper examines asymmetric and time-varying dependency structures between
financial returns, using a novel approach consisting of a combination of
regime-switching models and the local Gaussian correlation (LGC). We propose an
LGC-based bootstrap test for whether the dependence structure in financial
returns across different regimes is equal. We examine this test in a Monte
Carlo study, where it shows good level and power properties. We argue that this
approach is more intuitive than competing approaches, typically combining
regime-switching models with copula theory. Furthermore, the LGC is a
semi-parametric approach, hence avoids any parametric specification of the
dependence structure. We illustrate our approach using returns from the US-UK
stock markets and the US stock and government bond markets. Using a two-regime
model for the US-UK stock returns, the test rejects equality of the dependence
structure in the two regimes. Furthermore, we find evidence of lower tail
dependence in the regime associated with financial downturns in the LGC
structure. For a three-regime model fitted to US stock and bond returns, the
test rejects equality of the dependence structures between all regime pairs.
Furthermore, we find that the LGC has a primarily positive relationship in the
time period 1980-2000, mostly a negative relationship from 2000 and onwards. In
addition, the regime associated with bear markets indicates less, but
asymmetric dependence, clearly documenting the loss of diversification benefits
in times of crisis.
