Gabrielsen, A. and Zagaglia, Paolo and Kirchner, A. and Liu, Z. (2012): Forecasting ValueatRisk with timevarying variance, skewness and kurtosis in an exponential weighted moving average framework.

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Abstract
This paper provides an insight to the timevarying dynamics of the shape of the distribution of financial return series by proposing an exponential weighted moving average model that jointly estimates volatility, skewness and kurtosis over time using a modified form of the GramCharlier density in which skewness and kurtosis appear directly in the functional form of this density. In this setting VaR can be described as a function of the timevarying higher moments by applying the CornishFisher expansion series of the first four moments. An evaluation of the predictive performance of the proposed model in the estimation of 1day and 10day VaR forecasts is performed in comparison with the historical simulation, filtered historical simulation and GARCH model. The adequacy of the VaR forecasts is evaluated under the unconditional, independence and conditional likelihood ratio tests as well as Basel II regulatory tests. The results presented have significant implications for risk management, trading and hedging activities as well as in the pricing of equity derivatives.
Item Type:  MPRA Paper 

Original Title:  Forecasting ValueatRisk with timevarying variance, skewness and kurtosis in an exponential weighted moving average framework 
English Title:  Forecasting ValueatRisk with timevarying variance, skewness and kurtosis in an exponential weighted moving average framework 
Language:  English 
Keywords:  exponential weighted moving average; timevarying higher moments; CornishFisher expansion; GramCharlier density; risk management; ValueatRisk 
Subjects:  C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C51  Model Construction and Estimation C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C53  Forecasting and Prediction Methods ; Simulation Methods C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C52  Model Evaluation, Validation, and Selection G  Financial Economics > G1  General Financial Markets > G15  International Financial Markets 
Item ID:  39294 
Depositing User:  Paolo Zagaglia 
Date Deposited:  07 Jun 2012 01:39 
Last Modified:  14 Oct 2016 02:17 
References:  Alizadeh, A., and Gabrielsen, A., (2011), “Modelling the Dynamics of Credit Spreads of European Corporate Bond Indices”, Forthcoming. Angelidis, T., A. Benos, and Degiannakis, S.A., (2004), “The Use of GARCH Models in VaR Estimation”, Statistical Methodology, 1(12), pp 105128. Angelidis, T., Benos, A. and Degiannakis, S.A., (2007), “A Robust VaR Model under Different Time Periods and Weighting Schemes”, Review of Quantitative Finance and Accounting, 28(2), pp 187201. Anson, M., J., P., Fabozzi, F., J., Choudhry, M., Chen, R., R., (2004) Credit Derivatives Instruments, Applications and Pricing. Wiley Finance. Apergis, N., and Gabrielsen, A., (2012), “Optimal Hedge Ratio Estimation during the Credit Crisis: An Application of Higher Moments”, Frontiers in Finance and Economics. BASEL II, (2005), International Convergence of Capital Measurement and Capital Standards, Basel Committee on Banking Supervision. 
URI:  https://mpra.ub.unimuenchen.de/id/eprint/39294 