The Use of GARCH Models in VaR Estimation
By Timotheos Angelidis, Alexandros Benos, Stavros Degiannakis *. 2004
314 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/5f2a00409f48ed4a596a36d6fdee3f82d8624f24
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- Stavros Degiannakis *
- George Filis
- Hossein Hassani
- Manuela Braione
- Carol Alexander
- N. Scholtes
- Elizabeth Sheedy
- Himadri Ghosh
In Finance
- George Filis
- Hossein Hassani
- Stavros Degiannakis *
- Manuela Braione
- Carol Alexander
- N. Scholtes
- Elizabeth Sheedy
- Himadri Ghosh
Citations in the corpus
- Kalman filter-based modelling and forecasting of stochastic volatility with threshold (2015, methodology): “In [1], performance of the GARCH model was evaluated for modelling daily value-at-risk (VaR) of perfectly distributed portfolios in five stock indices using a number of distributional assumptions and sample sizes.”
- Forecasting oil price realized volatility using information channels from other asset classes (2017, background): “(1993) and Angelidis et al. (2004) maintain that the use of restricted samples is capable of capturing changes in the market activity more accurately.”
- Forecasting global stock market implied volatility indices (2018, background): “For example, Angelidis et al. (2004), Degiannakis et al. (2008) and Engle et al. (1993) provide empirical evidence that the use of restricted rolling window samples captures the changes in market activity more effectively6,7.”
- Forecasting Value-at-Risk under Different Distributional Assumptions (2016, methodology): “[3] combine three GARCH specifications with the univariate skew-Student and skew-GED (Generalized Error) distributions to show that these are able to produce superior VaR forecasts compared to the normal.”
- Developing a stress testing framework based on market risk models (2008, methodology): “Giot and Laurent (2003) apply a similar approach in equity markets and Angelidis et al. (2004) apply the simpler tEGARCH model for estimating VaR in equity markets. In an analysis of major currencies, So and Yu (2006) find that the t-GARCH method performs well in VaR estimation for major currency re”