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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

Suggested Citation

  • Anders Wilhelmsson, 2009. "Value at Risk with time varying variance, skewness and kurtosis--the NIG-ACD model," Econometrics Journal, Royal Economic Society, vol. 12(1), pages 82-104, March.
  • Handle: RePEc:ect:emjrnl:v:12:y:2009:i:1:p:82-104
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    Citations

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    Cited by:

    1. Alexandros Gabrielsen & Axel Kirchner & Zhuoshi Liu & Paolo Zagaglia, 2015. "Forecasting Value-At-Risk With Time-Varying Variance, Skewness And Kurtosis In An Exponential Weighted Moving Average Framework," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 10(01), pages 1-29.
    2. Dark Jonathan Graeme, 2010. "Estimation of Time Varying Skewness and Kurtosis with an Application to Value at Risk," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(2), pages 1-50, March.
    3. Matteo Grigoletto & Francesco Lisi, 2011. "Practical implications of higher moments in risk management," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 20(4), pages 487-506, November.
    4. repec:taf:eurjfi:v:22:y:2016:i:13:p:1237-1271 is not listed on IDEAS
    5. 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).
    6. Lucas, André & Zhang, Xin, 2016. "Score-driven exponentially weighted moving averages and Value-at-Risk forecasting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 293-302.
    7. Bujar Huskaj & Marcus Nossman, 2013. "A Term Structure Model for VIX Futures," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 33(5), pages 421-442, May.
    8. Alexios Ghalanos & Eduardo Rossi & Giovanni Urga, 2015. "Independent Factor Autoregressive Conditional Density Model," Econometric Reviews, Taylor & Francis Journals, vol. 34(5), pages 594-616, May.
    9. Gong, Xiaoli & Zhuang, Xintian, 2017. "Measuring financial risk and portfolio reversion with time changed tempered stable Lévy processes," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 148-159.
    10. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    11. repec:eee:finlet:v:21:y:2017:i:c:p:10-20 is not listed on IDEAS
    12. Alizadeh, Amir H. & Gabrielsen, Alexandros, 2013. "Dynamics of credit spread moments of European corporate bond indexes," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3125-3144.
    13. Slim, Skander & Koubaa, Yosra & BenSaïda, Ahmed, 2017. "Value-at-Risk under Lévy GARCH models: Evidence from global stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 46(C), pages 30-53.
    14. Bruno Feunou & Mohammad R. Jahan-Parvar & Roméo Tédongap, 2016. "Which parametric model for conditional skewness?," The European Journal of Finance, Taylor & Francis Journals, vol. 22(13), pages 1237-1271, October.
    15. repec:rmk:rmkjrc:v:4:y:2017:i:1:p:31-41 is not listed on IDEAS

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