Modeling extreme events: Time-varying extreme tail shape

Arbeitspapier

We propose a dynamic semi-parametric framework to study time variation in tail parameters. 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-specified, as will be the case in any finite sample. This is confirmed in simulations. Using the model, we find that Eurosystem sovereign bond purchases during the euro area sovereign debt crisis had a beneficial impact on extreme upper tail quantiles, leaning against the risk of extremely adverse market outcomes while active.

Angaben zum Objekt

• Sprache: Englisch

Verweise und Beziehungen

• Erschienen in: Series: Sveriges Riksbank Working Paper Series ; No. 399

Klassifikation und Themen

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

Beteiligte, Orts- und Zeitangaben

• Ereignis: Geistige Schöpfung
• (wer): Schwaab, Bernd ; Zhang, Xin ; Lucas, André
• Ereignis: Veröffentlichung
• (wer): Sveriges Riksbank
• (wo): Stockholm
• (wann): 2020

Weitere Informationen

• Handle: http://hdl.handle.net/10419/232602
• Letzte Aktualisierung: 10.03.2025, 11:42 MEZ