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Cited by 785

The DOI matches its Crossref record; 100 of the 100 references it cites were found in a registry or an index.

ARCH MODELS: PROPERTIES, ESTIMATION AND TESTING

Bera, Anil K., Higgins, Matthew L.·1993·Journal of Economic Surveys

Abstract

Abstract.The aim of this survey paper is to provide an account of some of the important developments in the autoregressive conditional heteroskedasticity (ARCH) model since its inception in a seminal paper by Engle (1982). This model takes account of many observed properties of asset prices, and therefore, various interpretations can be attributed to it. We start with the basic ARCH models and discuss their different interpretations. ARCH models have been generalized in different directions to accommodate more and more features of the real world. We provide a comprehensive treatment of many of the extensions of the original ARCH model. Next we discuss estimation and testing for ARCH models and note that these models lead to some interesting and unique problems. There have been numerous applications and we mention some of these as we present different models. The paper includes a glossary of the acronyms for the models we describe.

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Crossref · 10.1111/j.1467-6419.1993.tb00170.x

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Metadata

Authors
Bera, A. K., & Higgins, M. L.
Venue
Journal of Economic Surveys
Publisher
Wiley
Published
1993-12
Volume
7
Issue
4
Pages
305-366
ISSN
  • 0950-0804 (ISSN-L)
  • 1467-6419
OpenAlex
W2152804254
Cited by
785
References
100
FWCI
21.82
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: ARCH MODELS: PROPERTIES, ESTIMATION AND TESTING. https://app.cochat.ai/papers/10.1111/j.1467-6419.1993.tb00170.x
The paper
Bera, A. K., & Higgins, M. L. (1993). ARCH MODELS: PROPERTIES, ESTIMATION AND TESTING. Journal of Economic Surveys. https://doi.org/10.1111/j.1467-6419.1993.tb00170.x

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.