Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/234078 
Erscheinungsjahr: 
2021
Schriftenreihe/Nr.: 
ECB Working Paper No. 2524
Verlag: 
European Central Bank (ECB), Frankfurt a. M.
Zusammenfassung: 
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.
Schlagwörter: 
dynamic tail risk
observation-driven models
extreme value theory
EuropeanCentral Bank (ECB)
Securities Markets Programme (SMP)
JEL: 
C22
G11
Persistent Identifier der Erstveröffentlichung: 
ISBN: 
978-92-899-4524-0
Dokumentart: 
Working Paper

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