Automatic threshold selection for extreme value regression models of tail risks

EI-ERIM-OR seminar
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Dr. Julien Hambuckers

Thursday 1 Dec 2022, 12:00 - 13:00
Spoken Language
Theil Building
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We introduce a robust method to simultaneously estimate the tail and the threshold parameters of an extreme value regression model. This model finds its use in finance to assess the effect of market variables on extreme loss distributions of assets or investment vehicles, such as hedge funds.

(joint with A. Usseglio-Carleve and M. Kratz)

Splicing regression model

A major limitation of these models, though, is the need to select ex ante a threshold below which data are discarded, which leads to estimation inefficiency.

To solve this issue, our approach relies on a splicing regression model that extends the extreme value regression model below the threshold, and uses an artificial censoring mechanism of the likelihood contributions in the bulk of the data at the estimation stage to decrease specification issues.

Censoring strategies

We discuss several censoring strategies (both theoretical and data-driven) of the proposed estimator. We illustrate its superiority for tail inference over classical peaks-over-threshold methods in an extensive simulation study. We then investigate the determinants of hedge funds' tail risks over time, using an unbalanced panel of 1,400 long/short equity hedge funds over the period 1995-2021. We find a significant link between hedge funds tail risks and factors such as equity momentum, financial stability indicators and credit spreads.

     Julien Hambuckers

    About Julien Hambucker

    Julien Hambuckers is an associate professor of finance at University of Liège (Belgium), and a faculty member of  HEC Liège (the business school of the university).  From 2016 to 2018 I was a researcher at University of Göttingen (Germany), Chair of Statistics (Business and Economics faculty).

    My research areas are statistics applied to finance, financial econometrics and Extreme Value Theory. I also work on distributional regression models in the time series context, and on solving applied statistical questions (e.g. model selection or endogeneity) in financial economics.


    Maria Grith an Michal Mankowski

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    Secretariat Econometrics
    Phone: +31 (0)10 408 12 59/ 12 64

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