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Model vs. Market - A comparison of VaR and ES estimation for sector ETFs using model based IGARCH and market implied volatility in the VWHS framework

Mettävainio, Isak LU and Bergo, Erik LU (2025) NEKN01 20251
Department of Economics
Abstract (Swedish)
Tail risk metrics such as VaR and, especially ES are and have become of great importance to both investors and financial institutions such as banks in determining their amount of loss absorbing capital given the Basel framework. Estimating these metrics have become trivial, but to do it accurately while also taking market conditions such as periods of market stress into account still presents challenges. This thesis evaluates the benefit of using implied volatilities (IVs) in VaR and ES estimation in the Volatility-Weighted Historical Simulation (VWHS) framework for five sector specific ETFs as part of the S&P 500. The findings are compared to the parametric IGARCH-VWHS benchmark model. Empirical results of risk estimates and backtesting... (More)
Tail risk metrics such as VaR and, especially ES are and have become of great importance to both investors and financial institutions such as banks in determining their amount of loss absorbing capital given the Basel framework. Estimating these metrics have become trivial, but to do it accurately while also taking market conditions such as periods of market stress into account still presents challenges. This thesis evaluates the benefit of using implied volatilities (IVs) in VaR and ES estimation in the Volatility-Weighted Historical Simulation (VWHS) framework for five sector specific ETFs as part of the S&P 500. The findings are compared to the parametric IGARCH-VWHS benchmark model. Empirical results of risk estimates and backtesting results point to no clear advantage of including IV in tail risk estimation at medium and long horizons while anticipated market uncertainty may favor the IV-approach. (Less)
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author
Mettävainio, Isak LU and Bergo, Erik LU
supervisor
organization
course
NEKN01 20251
year
type
H1 - Master's Degree (One Year)
subject
keywords
Value-at-Risk, Expected Shortfall, Implied Volatility, IGARCH, VWHS
language
English
id
9195105
date added to LUP
2025-09-12 10:00:19
date last changed
2025-09-12 10:00:19
@misc{9195105,
  abstract     = {{Tail risk metrics such as VaR and, especially ES are and have become of great importance to both investors and financial institutions such as banks in determining their amount of loss absorbing capital given the Basel framework. Estimating these metrics have become trivial, but to do it accurately while also taking market conditions such as periods of market stress into account still presents challenges. This thesis evaluates the benefit of using implied volatilities (IVs) in VaR and ES estimation in the Volatility-Weighted Historical Simulation (VWHS) framework for five sector specific ETFs as part of the S&P 500. The findings are compared to the parametric IGARCH-VWHS benchmark model. Empirical results of risk estimates and backtesting results point to no clear advantage of including IV in tail risk estimation at medium and long horizons while anticipated market uncertainty may favor the IV-approach.}},
  author       = {{Mettävainio, Isak and Bergo, Erik}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Model vs. Market - A comparison of VaR and ES estimation for sector ETFs using model based IGARCH and market implied volatility in the VWHS framework}},
  year         = {{2025}},
}