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Expected Shortfall as a Complement to Value at Risk - A study applied to commodities

Gerstädt, Filippa LU and Olander, Maria (2010) NEKM03 20101
Department of Economics
Abstract
Basel II requires Value at Risk (VaR) as a standardized risk measure for calculating market risk. However, the validity of the risk measure has been questioned since it neglects the losses beyond the VaR level. Expected Shortfall (ES) is a response to this limitation, as it is defined as the average of the losses ignored by VaR. This study applies VaR and ES to three commodities; gold, oil and corn by using the models historical simulation, age-weighted HS, volatility-weighted HS, normal distribution, Student-t distribution, log-normal distribution. Also, conditional volatility, structured as a GARCH(1,1) model, is applied to the three distributions. These nine models are evaluated by backtesting procedures for each commodity. Applying... (More)
Basel II requires Value at Risk (VaR) as a standardized risk measure for calculating market risk. However, the validity of the risk measure has been questioned since it neglects the losses beyond the VaR level. Expected Shortfall (ES) is a response to this limitation, as it is defined as the average of the losses ignored by VaR. This study applies VaR and ES to three commodities; gold, oil and corn by using the models historical simulation, age-weighted HS, volatility-weighted HS, normal distribution, Student-t distribution, log-normal distribution. Also, conditional volatility, structured as a GARCH(1,1) model, is applied to the three distributions. These nine models are evaluated by backtesting procedures for each commodity. Applying conditional variance improves the models radically and we conclude that the models Volatility-weighted HS and Student-t GARCH(1,1) are the most accurate models regarding the three commodities. Additionally, estimating ES adds value to this study, even though it is almost perfect positively correlated with VaR. (Less)
Please use this url to cite or link to this publication:
author
Gerstädt, Filippa LU and Olander, Maria
supervisor
organization
course
NEKM03 20101
year
type
H1 - Master's Degree (One Year)
subject
keywords
Value at Risk, Expected Shortfall, nine approaches, backtesting
language
English
id
1613445
date added to LUP
2010-06-10 12:07:28
date last changed
2010-06-10 12:07:28
@misc{1613445,
  abstract     = {{Basel II requires Value at Risk (VaR) as a standardized risk measure for calculating market risk. However, the validity of the risk measure has been questioned since it neglects the losses beyond the VaR level. Expected Shortfall (ES) is a response to this limitation, as it is defined as the average of the losses ignored by VaR. This study applies VaR and ES to three commodities; gold, oil and corn by using the models historical simulation, age-weighted HS, volatility-weighted HS, normal distribution, Student-t distribution, log-normal distribution. Also, conditional volatility, structured as a GARCH(1,1) model, is applied to the three distributions. These nine models are evaluated by backtesting procedures for each commodity. Applying conditional variance improves the models radically and we conclude that the models Volatility-weighted HS and Student-t GARCH(1,1) are the most accurate models regarding the three commodities. Additionally, estimating ES adds value to this study, even though it is almost perfect positively correlated with VaR.}},
  author       = {{Gerstädt, Filippa and Olander, Maria}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Expected Shortfall as a Complement to Value at Risk - A study applied to commodities}},
  year         = {{2010}},
}