Autoregressive Conditional Tail Behavior and Results on Government Bond Yield Spreads

Abstract

Previous evidence in empirical finance indicates the potential usefulness of modeling time-variation particularly in the tails of speculative return distributions. Based on results from extreme value theory, the present paper proposes a fixed changepoint Pareto-type autoregressive conditional tail model. Regression-based parameter estimation of the unobservable time-varying tail index is carried out via classical Kalman filtering. A model application highlights the tail index dynamics for daily changes in Government bond yield spreads between the US-Dollar and the Euro zone.

Keywords: Tail index, Pareto-model, autoregressive conditional tail, extreme financial risk, spread risk

JEL Classification: C16, C22, C53, G10