This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 517
Type: Contributed
Date/Time: Wednesday, August 4, 2010 : 10:30 AM to 12:20 PM
Sponsor: Business and Economic Statistics Section
Abstract - #306506
Title: Intensity-Based Estimation of Extreme Loss Event Probability and Value-at-Risk
Author(s): Kam Hamidieh*+ and Stilian Stoev and George Michailidis
Companies: Rice University and University of Michigan and University of Michigan
Address: Rice University, Department of Statistics, Houston, TX, 77251-1892, USA
Keywords: heavy tails ; clustering of extremes ; value at risk ; self-exciting point process ; autoregressive conditional duration ; Generalized Pareto Distribution

We develop methodology for the estimation of Extreme Loss Event Probability and the VaR, that takes into account both the magnitudes and the intensity of the extreme losses. Specifically, the extreme loss magnitudes are modeled with a Generalized Pareto Distribution, while their intensity is captured by an Autoregressive Conditional Duration model, a type of Self-Exciting Point Process. This allows for an explicit interaction between the magnitude of the past losses and the intensity of future extreme losses. The intensity is further used in the estimation of Extreme Loss Event Probability. The method is illustrated and backtested on 10 assets and compared with the established and baseline methods. The results show that our method outperforms the baseline methods, competes with an established method, and provides additional insight and interpretation into the prediction of extremes.

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