Modeling extreme events: time-varying extreme tail shape

Arbeitspapier

A dynamic semi-parametric framework is proposed to study time variation in tail fatness of sovereign bond yield changes during the 2010--2012 euro area sovereign debt crisis measured at a high (15-minute) frequency. The framework builds on the Generalized Pareto Distribution (GPD) for modeling peaks over thresholds as in Extreme Value Theory, but casts the model in a conditional framework to allow for time-variation in the tail shape parameters. The score-driven updates used improve the expected Kullback-Leibler divergence between the model and the true data generating process on every step even if the GPD only fits approximately and the model is mis-sepcified, as will be the case in any finite sample. This is confirmed in simulations. Using the model, we find the ECB program had a beneficial impact on extreme upper tail quantiles, leaning against the risk of extremely adverse market outcomes while active.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Series: Tinbergen Institute Discussion Paper ; No. TI 2020-076/III

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes ; Portfolio Choice; Investment Decisions
• Subject: dynamic tail risk ; observation-driven models ; extreme value theory ; European Central Bank (ECB) ; Securities Markets Programme (SMP)

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Schwaab, Bernd ; Zhang, Xin ; Lucas, André
• Event: Veröffentlichung
• (who): Tinbergen Institute
• (where): Amsterdam and Rotterdam
• (when): 2020

Further information

• Handle: http://hdl.handle.net/10419/229696
• Last update: 10.03.2025, 11:42 AM CET