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
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity
White, H. (1980) · Econometrica · doi:10.2307/1912934 · Cited by 25,861
Generalized autoregressive conditional heteroskedasticity
Bollerslev, T. (1986) · Journal of Econometrics · doi:10.1016/0304-4076(86)90063-1 · Cited by 22,254
Engle, R. F. (1982) · Econometrica · doi:10.2307/1912773 · Cited by 20,795
Large Sample Properties of Generalized Method of Moments Estimators
Hansen, L. P. (1982) · Econometrica · doi:10.2307/1912775 · Cited by 13,467
Conditional Heteroskedasticity in Asset Returns: A New Approach
Nelson, D. B. (1991) · Econometrica · doi:10.2307/2938260 · Cited by 10,236
Time Series Analysis: Forecasting and Control
Kleiner, B. (1977) · Technometrics · doi:10.1080/00401706.1977.10489562 · Cited by 6,446
A Simple Test for Heteroscedasticity and Random Coefficient Variation
Breusch, T. S., & Pagan, A. R. (1979) · Econometrica · doi:10.2307/1911963 · Cited by 5,647
The Variation of Certain Speculative Prices
Mandelbrot, B. (1963) · The Journal of Business · doi:10.1086/294632 · Cited by 4,747
Multivariate Simultaneous Generalized ARCH
Engle, R. F., & Kroner, K. F. (1995) · Econometric Theory · doi:10.1017/s0266466600009063 · Cited by 4,487
The variation of certain speculative prices
Mandelbrot, B. B. (1997) · Fractals and Scaling in Finance · doi:10.1007/978-1-4757-2763-0_14 · Cited by 4,468
Cited by
Forecasting Volatility in Financial Markets: A Review
Poon, S., & Granger, C. W. J. (2003) · Journal of Economic Literature · doi:10.1257/002205103765762743 · Cited by 1,315
Value‐at‐risk for long and short trading positions
Giot, P., & Laurent, S. (2003) · Journal of Applied Econometrics · doi:10.1002/jae.710 · Cited by 373
Maximum entropy autoregressive conditional heteroskedasticity model
Park, S. Y., & Bera, A. K. (2009) · Journal of Econometrics · doi:10.1016/j.jeconom.2008.12.014 · Cited by 218
Self-citation
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- 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.