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Forecasting Expected Shortfall: An Extreme Value Approach

Kjellson, Benjamin (2013) MASY01 20131
Mathematical Statistics
Abstract (Swedish)
We compare estimates of Value at Risk and Expected Shortfall from AR(1)-GARCH(1,1)-type models (standard GARCH, GJR-GARCH, Component GARCH), to estimates produced using the Peak Over Threshold method on the residuals of these models. We find that the conditional volatility model matters less than the choice of distribution for the innovations in the loss process, for which we compare the normal and the t-distribution. The Peak Over Threshold estimates are found to improve upon the estimates of the original models, particularly in the case of normally distributed innovations.
Please use this url to cite or link to this publication:
author
Kjellson, Benjamin
supervisor
organization
course
MASY01 20131
year
type
M2 - Bachelor Degree
subject
language
English
id
3735573
date added to LUP
2013-05-06 14:44:14
date last changed
2013-05-07 14:35:33
@misc{3735573,
  abstract     = {{We compare estimates of Value at Risk and Expected Shortfall from AR(1)-GARCH(1,1)-type models (standard GARCH, GJR-GARCH, Component GARCH), to estimates produced using the Peak Over Threshold method on the residuals of these models. We find that the conditional volatility model matters less than the choice of distribution for the innovations in the loss process, for which we compare the normal and the t-distribution. The Peak Over Threshold estimates are found to improve upon the estimates of the original models, particularly in the case of normally distributed innovations.}},
  author       = {{Kjellson, Benjamin}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Forecasting Expected Shortfall: An Extreme Value Approach}},
  year         = {{2013}},
}