This paper investigates the dependency of international stock market interaction on financial volatility. We show in a stylized economic model that volatility-dependent cross-market spillovers can be interpreted in two different ways, as indicating information flow or uncertainty. If higher volatility in one market leads to higher (lower) reactions in another market, volatility reflects information (uncertainty). We apply a simultaneous time-varying coefficient model, where structural ARCH-type variances serve two purposes: governing the time variation of spillovers and ensuring statistical identification. We analyze data of US and further stock markets. Indeed, we find strong nonlinear, volatility-dependent spillovers.

This paper introduces parametric spectrum estimation to the analysis of financial cycles. Our contribution is to formally test properties of financial cycles and to characterize their international interaction in the frequency domain. Existing work argues that the financial cycle is considerably longer in duration and larger in amplitude than the business cycle and that its distinguishing features became more pronounced over time. Also, a global cycle, being driven by US monetary policy, is said to be behind national financial cycles. We provide strong statistical evidence for the US and slightly weaker evidence for the UK validating the hypothesized features of the national financial cycle. In Germany, however, the financial cycle is much less visible. Similarly, a US-driven global financial cycle significantly affects national cycles in the UK but not in Germany.