On the Normal Inverse Gaussian Stochastic Volatility Model
AbstractIn this article, the normal inverse Gaussian stochastic volatility model of Barndorf-Nielsen is extended. The resulting model has a more flexible lag structure than the original one. In addition, the second- and fourth-order moments, important properties of a volatility model, are derived. The model can be considered either as a generalized autoregressive conditional heteroscedasticity model with nonnormal errors or as a stochastic volatility model with an inverse Gaussian distributed conditional variance. A simulation study is made to investigate the performance of the maximum likelihood estimator of the model. Finally, the model is applied to stock returns and exchange-rate movements. Its fit to two stylized facts and its forecasting performance is compared with two other volatility models.
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Bibliographic InfoArticle provided by American Statistical Association in its journal Journal of Business and Economic Statistics.
Volume (Year): 19 (2001)
Issue (Month): 1 (January)
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- Rehim Kilic, 2011. "A conditional variance tale from an emerging economy's freely floating exchange rate," Applied Economics, Taylor & Francis Journals, vol. 43(19), pages 2465-2480.
- Nakajima, Jouchi & Omori, Yasuhiro, 2012.
"Stochastic volatility model with leverage and asymmetrically heavy-tailed error using GH skew Student’s t-distribution,"
Computational Statistics & Data Analysis,
Elsevier, vol. 56(11), pages 3690-3704.
- Jouchi Nakajima & Yasuhiro Omori, 2010. "Stochastic Volatility Model with Leverage and Asymmetrically Heavy-Tailed Error Using GH Skew Student?s t-Distribution," CARF F-Series CARF-F-215, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
- Jouchi Nakajima & Yasuhiro Omori, 2009. "Stochastic volatility model with leverage and asymmetrically heavy-tailed error using GH skew Student's t-distribution," CARF F-Series CARF-F-199, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
- Jouchi Nakajima & Yasuhiro Omori, 2009. "Stochastic Volatility Model with Leverage and Asymmetrically Heavy-Tailed Error Using GH Skew Student's t-Distribution," CIRJE F-Series CIRJE-F-701, CIRJE, Faculty of Economics, University of Tokyo.
- Jouchi Nakajima & Yasuhiro Omori, 2010. "Stochastic Volatility Model with Leverage and Asymmetrically Heavy-tailed Error Using GH Skew Student's t-distribution," Global COE Hi-Stat Discussion Paper Series gd09-124, Institute of Economic Research, Hitotsubashi University.
- Shiyi Chen & Wolfgang K. Härdle & Kiho Jeong, 2010. "Forecasting volatility with support vector machine-based GARCH model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(4), pages 406-433.
- Lars Forsberg & Anders Eriksson, 2004. "The Mean Variance Mixing GARCH (1,1) model," Econometric Society 2004 Australasian Meetings 323, Econometric Society.
- Ruiz, Esther & Veiga, Helena, 2008.
"Modelling long-memory volatilities with leverage effect: A-LMSV versus FIEGARCH,"
Computational Statistics & Data Analysis,
Elsevier, vol. 52(6), pages 2846-2862, February.
- Esther Ruiz & Helena Veiga, 2006. "Modelling Long-Memory Volatilities With Leverage Effect: Almsv Versus Fiegarch," Statistics and Econometrics Working Papers ws066016, Universidad Carlos III, Departamento de Estadística y Econometría.
- Malmsten, Hans & Teräsvirta, Timo, 2004. "Stylized Facts of Financial Time Series and Three Popular Models of Volatility," Working Paper Series in Economics and Finance 563, Stockholm School of Economics, revised 03 Sep 2004.
- Lars Stentoft, 2008.
"American Option Pricing Using GARCH Models and the Normal Inverse Gaussian Distribution,"
Journal of Financial Econometrics,
Society for Financial Econometrics, vol. 6(4), pages 540-582, Fall.
- Lars Stentoft, 2008. "American Option Pricing using GARCH models and the Normal Inverse Gaussian distribution," CREATES Research Papers 2008-41, School of Economics and Management, University of Aarhus.
- Lars Forsberg & Tim Bollerslev, 2002. "Bridging the gap between the distribution of realized (ECU) volatility and ARCH modelling (of the Euro): the GARCH-NIG model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 535-548.
- Homm, Ulrich & Pigorsch, Christian, 2012. "Beyond the Sharpe ratio: An application of the Aumann–Serrano index to performance measurement," Journal of Banking & Finance, Elsevier, vol. 36(8), pages 2274-2284.
- Pentti Saikkonen & Markku Lanne, 2004. "A Skewed GARCH-in-Mean Model: An Application to U.S. Stock Returns," Econometric Society 2004 North American Summer Meetings 469, Econometric Society.
- Walter Krämer & Philip Mess, 2012. "Structural Change and Spurious Persistence in Stochastic Volatility," Ruhr Economic Papers 0310, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
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