On the Normal Inverse Gaussian Stochastic Volatility Model

Jonas Andersson

Journal of Business & Economic Statistics, 2001, vol. 19, issue 1, 44-54

Abstract: In 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.

Date: 2001
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Persistent link: https://EconPapers.repec.org/RePEc:bes:jnlbes:v:19:y:2001:i:1:p:44-54

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