Nonlinearity and Time-varying Dependence in
Money Markets
Zeynep Senyuz (with Emre Yoldas, Bernd Schlusche and Selva Demiralp)
Abstract: We develop a comprehensive empirical framework to assess the source and
severity of stress in short-term funding markets and to shed light onto their time-varying
dynamics. Our model accounts for nonlinearity in the mean, the volatility, and the
correlation of money market rates. We estimate threshold vector error correction models for
each pair of rates that forms one of the commonly monitored spreads and identify varying
levels of funding stress in different money market segments. We then model time-varying
volatilities and correlations of the rates using dynamic conditional correlation models. The
model estimates are updated in real-time as more data become available to market
participants and policy makers. Our results show that spread thresholds that determine
regimes have become significant in key money market segments at the onset of the crisis.
Dislocations led to lower rate correlations in the aftermath of the crisis, although such
correlations are still sizable.