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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)
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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},
  keyword      = {Value at Risk,Expected Shortfall,nine approaches,backtesting},
  language     = {eng},
  note         = {Student Paper},
  title        = {Expected Shortfall as a Complement to Value at Risk - A study applied to commodities},
  year         = {2010},
}