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Value at Risk with time varying variance, skewness and kurtosis--the NIG-ACD model

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  • Anders Wilhelmsson

Abstract

A new model for financial returns with time varying variance, skewness and kurtosis based on the Normal Inverse Gaussian (NIG) distribution is proposed. The new model and two previously suggested NIG models are evaluated by their Value at Risk (VaR) forecasts on a long series of daily Standard and Poor's 500 returns. All three models perform very well compared with extant models and clearly outperform a Gaussian GARCH model. Moreover, the results show that only the new model cannot be rejected as providing correct conditional VaR forecasts. Copyright The Author(s). Journal compilation Royal Economic Society 2009

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Bibliographic Info

Article provided by Royal Economic Society in its journal Econometrics Journal.

Volume (Year): 12 (2009)
Issue (Month): 1 (03)
Pages: 82-104

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Handle: RePEc:ect:emjrnl:v:12:y:2009:i:1:p:82-104

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Cited by:
  1. A. Gabrielsen & P. Zagaglia & A. Kirchner & Z. Liu, 2012. "Forecasting Value-at-Risk with Time-Varying Variance, Skewnessn and Kurtosis in an Exponential Weighted Moving Average Framework," Working Papers wp831, Dipartimento Scienze Economiche, Universita' di Bologna.
  2. Stanislav Anatolyev & Natalia Kryzhanovskaya, 2009. "Directional Prediction of Returns under Asymmetric Loss: Direct and Indirect Approaches," Working Papers w0136, Center for Economic and Financial Research (CEFIR).
  3. Matteo Grigoletto & Francesco Lisi, 2011. "Practical implications of higher moments in risk management," Statistical Methods and Applications, Springer, vol. 20(4), pages 487-506, November.
  4. Alexios Ghalanos & Eduardo Rossi & Giovanni Urga, 2012. "Independent Factor Autoregressive Conditional Density Model," DEM Working Papers Series 021, University of Pavia, Department of Economics and Management.
  5. Bruno Feunou & Mohammad R. Jahan-Parvar & Roméo Tedongap, 2013. "Which Parametric Model for Conditional Skewness?," Working Papers 13-32, Bank of Canada.

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