EVALUATION OF THE CAPITAL MARKET RISK WITH THE APPLICATION OF MODIFIED POT METHOD WITH VOLATILITY MODELS
DOI:
https://doi.org/10.12775/AUNC_ECON.2009.043Keywords
extreme value theory, Peaks over Threshold, value-at-risk, expected shortfallAbstract
The main aim of this paper is presentation and empirical analysis of the new approach which combines volatility models with Peaks over Threshold method. The standard volatility models better estimate medium size values of financial times series. The new approach is based on possibility, that extremes are estimated using POT method, and medium values are estimated using standard volatility models. The contribution of this paper is analysis of the value-atrisk and the expected shortfall for this new approach. Financial risk model evaluation of this risk measures is one of the key part of this paper. Conditional tail estimates are obtained by adjusting the unconditional extreme value theory procedure with the returns filtered by standard volatility models (McNeil, Frey, 2000). Additionally, risk measures estimates obtained from volatility models with application of EVT versus those computed, using standard volatility models for financial time series are compared.
References
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. (1997), Thinking Coherently, „Risk”, 10, 68–71.
Artzner P., Delbaen F., Eber J.M., Heath D. (1999), Coherent Measures of Risk, „Mathematical Finance”, 9, 203–228.
Brooks, C., Clare, A.D., Dalle Molle, J.W, Persand, G. (2006), A Comparison of Extreme Value Theory Approaches for Determining Value at Risk, „Journal of Empirical Finance”, 12, 339–352.
Christoffersen P.F. (1998), Evaluating Interval Forecasts, „International Economic Review”, 3, Dowd K. (2002), Measuring Market Risk, John Wiley & Sons Ltd., New York.
Embrechts P., Klüppelberg C., Mikosch T. (2003), Modelling Extremal Events for Insurance and Finance, Springer, Berlin.
Fałdziński M. (2008), Model warunkowej zmienności wartości ekstremalnych, [w:] Zielinski Z. (red.), Współczesne trendy w ekonometrii, Wydawnictwo Wyższej Szkoły Informatyki i Ekonomii, Olsztyn.
Fałdziński M. (2009), Usefulness of the Spectral Risk Measures with Extreme Value Theory approach, Forecasting Financial Markets and Economic Decision-Making FindEcon, Łódź, submitted.
Haas M. (2001), New Methods in Backtesting, Financial Engineering Research Center, Bonn Harmantzis, F.C., Miao L., Chien Y. (2006), Empirical Study of Value-at-Risk and Expected Shortfall Models with Heavy Tails, „Journal of Risk Finance”, 7(2), 117–126.
Kuester, K., Mittnik, S., Paolella, M.S. (2006), Value-at-Risk Prediction: A Comparison of Alternative Strategies, „Journal of Financial Econometrics”, 4(1), 53–89.
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”, 7, 271–300.
Osińska M., Fałdziński M. (2007), Modele GARCH i SV z zastosowaniem teorii wartości ekstremalnych, nr X, [w:] Zielinski Z. (red.), Dynamiczne Modele Ekonometryczne, UMK, Toruń.
Downloads
Published
How to Cite
Issue
Section
License
Autorzy, których teksty zostaną przyjęte do publikacji, po uzyskaniu pozytywnych recenzji wydawniczych oraz zaakceptowaniu do publikacji przez Komitet Redakcyjny, podpisują umowę licencyjną.
Stats
Number of views and downloads: 724
Number of citations: 0
