The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Autoregressive Conditional Kurtosis
Open accessAbstract
This article proposes a new model for autoregressive conditional heteroscedasticity and kurtosis. Via a time-varying degrees of freedom parameter, the conditional variance and conditional kurtosis are permitted to evolve separately. The model uses only the standard Student’s t-density and consequently can be estimated simply using maximum likelihood. The method is applied to a set of four daily financial asset return series comprising U.S. and U.K. stocks and bonds, and significant evidence in favor of the presence of autoregressive conditional kurtosis is observed. Various extensions to the basic model are proposed, and we show that the response of kurtosis to good and bad news is not significantly asymmetric.
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Citations
Cites
Engle, R. F. (1982) · Econometrica · doi:10.2307/1912773 · Cited by 20,795
Cited by
GENERALIZED AUTOREGRESSIVE SCORE MODELS WITH APPLICATIONS
Creal, D., Koopman, S. J., & Lucas, A. (2013) · Journal of Applied Econometrics · doi:10.1002/jae.1279 · Cited by 981
Metadata
- Authors
- Brooks, C.
- Venue
- Journal of Financial Econometrics
- Publisher
- Oxford University Press (OUP)
- Published
- 2005-07-01
- Volume
- 3
- Issue
- 3
- Pages
- 399-421
- ISSN
- 1479-8409 (ISSN-L)
- 1479-8417
- OpenAlex
- W2163600634
- Cited by
- 168
- References
- 1
- FWCI
- 15.90
- Type
- journal article
- Language
- en
- Open access
- green
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- Brooks, C. (2005). Autoregressive Conditional Kurtosis. Journal of Financial Econometrics. https://doi.org/10.1093/jjfinec/nbi018
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
