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