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2008 | 8 | 45--52
Tytuł artykułu

GARCH and SV Models with Application of Extreme Value Theory

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In the scientific research as well as in everyday life we can see a tendency to averaging many of the observed values. However, we could point out many cases where centrality measures are improper. In the case of events with extreme size the Extreme Value Theory (EVT) is appropriate. The methods of estimation in the EVT can be divided into two groups: nonparametric and parametric ones. The subject of further analysis in this paper is the Peaks over Threshold (POT) method, which belongs to the parametric group of the methods. The main aim of this paper is to present the application of the Extreme Value Theory in a risk analysis. We put forward a thesis that GARCH and SV models with application of the EVT can provide better estimation of the risk measures for financial time series, then standard volatility models. (fragment of text)
Rocznik
Tom
8
Strony
45--52
Opis fizyczny
Twórcy
  • Nicolaus Copernicus University in Toruń, Poland
  • Nicolaus Copernicus University in Toruń, Poland
Bibliografia
  • Angelidis, T., Degiannakis, S. (2006), Backtesting VaR Models: An Expected Shortfall Approach, Working Papers, University of Crete, Athens University of Economics and Business.
  • Artzner, P., Delbaen, F., Eber, J. M., Heath, D. (1998), Coherent Measures of Risk, Mathematical Finance, 9, 203-228.
  • Balkema, A. A., De Haan, L. (1974), Residual Life Time at Great Age, Annals of Probability, Vol.2, No. 5, 792-804
  • Beirlant, J., Matthys, G. (2001), Extreme Quantile Estimation for Heavy-Tailed Distributions. Mimeo.
  • Christoffersen, P. F. (1998), Evaluating Interval Forecasts, International Economic Review, Vol. 39, No. 4.
  • Dowd, K. (2002), Measuring Market Risk, John Wiley & Sons Ltd., New York
  • Haas, M. (2001), New Methods in Backtesting, Financial Engineering Research Center, Bonn.
  • McNeil, J. A., Frey, F. (2000), Estimation of Tail-Related Risk Measures for Heteroscedastic Financial Time Series: an Extreme Value Approach, Journal of Empirical Finance, Vol. 7, 271-30.0
  • Osińska, M., Fałdziński, M. (2007), GARCH and SV Models with Application of the Extreme Value Theory, Dynamic Econometric Models, Vol. X, Toruń (in Polish).
  • Pickands, J. (1975), Statistical Inference Using Extreme Order Statistics, Annals of Statistics, Vol. 3, No 1, 119-131.
  • Tasche, D. (2002), Expected Shortfall and Beyond, Journal of Banking & Finance, 26, 1519-1533.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171280671

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