The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
What good is a volatility model?
Open accessAbstract
A volatility model must be able to forecast volatility; this is the central requirement in almost all financial applications. In this paper we outline some stylized facts about volatility that should be incorporated in a model: pronounced persistence and mean-reversion, asymmetry such that the sign of an innovation also affects volatility and the possibility of exogenous or pre-determined variables influencing volatility. We use data on the Dow Jones Industrial Index to illustrate these stylized facts, and the ability of GARCH-type models to capture these features. We conclude with some challenges for future research in this area.
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Citations
Cites
Engle, R. F. (1982) · Econometrica · doi:10.2307/1912773 · Cited by 20,795
Self-citation
Cited by
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A forecast comparison of volatility models: does anything beat a GARCH(1,1)?
Hansen, P. R., & Lunde, A. (2005) · Journal of Applied Econometrics · doi:10.1002/jae.800 · Cited by 1,773
The Sum of All FEARS Investor Sentiment and Asset Prices
Da, Z., Engelberg, J., & Gao, P. (2015) · Review of Financial Studies · doi:10.1093/rfs/hhu072 · Cited by 1,379
Neglecting parameter changes in GARCH models
Hillebrand, E. (2005) · Journal of Econometrics · doi:10.1016/j.jeconom.2004.09.005 · Cited by 320
Metadata
- Authors
- Engle, R. F., & Patton, A. J.
- Venue
- Quantitative Finance
- Publisher
- Informa UK Limited
- Published
- 2001-02
- Volume
- 1
- Issue
- 2
- Pages
- 237-245
- ISSN
- 1469-7688 (ISSN-L)
- 1469-7696
- OpenAlex
- W2117019869
- Cited by
- 688
- References
- 1
- FWCI
- 30.58
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Engle, R. F., & Patton, A. J. (2001). What good is a volatility model? Quantitative Finance. https://doi.org/10.1088/1469-7688/1/2/305
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.
