
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-specified, 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.
extreme value theory, ddc:330, observation-driven models, EuropeanCentral Bank (ECB), G11, dynamic tail risk, C22, Securities Markets Programme (SMP), European Central Bank (ECB)
extreme value theory, ddc:330, observation-driven models, EuropeanCentral Bank (ECB), G11, dynamic tail risk, C22, Securities Markets Programme (SMP), European Central Bank (ECB)
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