The NIG-S&ARCH model: a fat-tailed, stochastic, and autoregressive conditional heteroskedastic volatility model
This paper examines the capabilities of the Normal Inverse Gaussian distribu-tion as a model for stock returns. We extend the model of Barndorff-Nielsen (1997) to allow for a richer volatility structure and compare with the existing GARCH-type models. We conclude that the proposed model outperforms some of the most praised GARCH-M models. In particular, we make a big gain in modelling the skewness of equity returns.
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Volume (Year): 4 (2001)
Issue (Month): 2 ()
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