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The NIG-S&ARCH model: a fat-tailed, stochastic, and autoregressive conditional heteroskedastic volatility model

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Author Info
MORTEN B. JENSEN ()
ASGER LUNDE ()

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Abstract

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

Volume (Year): 4 (2001)
Issue (Month): 2 ()
Pages: 10
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Handle: RePEc:ect:emjrnl:v:4:y:2001:i:2:p:10

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Related research
Keywords: Normal Inverse Gaussian distribution; Observation driven model; Nonlinear state space model; Filtering.;

Cited by:
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  1. 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. [Downloadable!]
    Other versions:
  2. Fajardo, J. & Farias, A., 2003. "Generalized Hyperbolic Distributions and Brazilian Data," Finance Lab Working Papers flwp_57, Finance Lab, Ibmec São Paulo. [Downloadable!]
    Other versions:
  3. Lars Stentoft, 2008. "Option Pricing using Realized Volatility," CREATES Research Papers 2008-13, School of Economics and Management, University of Aarhus. [Downloadable!]
  4. Rehim Kiliç, 2007. "Conditional Volatility and Distribution of Exchange Rates: GARCH and FIGARCH Models with NIG Distribution," Studies in Nonlinear Dynamics & Econometrics, Berkeley Electronic Press, vol. 11(3). [Downloadable!]
  5. Nilsson, Birger & Hansson, Björn, 2004. "A Two-State Capital Asset Pricing Model with Unobservable States," Working Papers 2004:28, Lund University, Department of Economics. [Downloadable!]
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