The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Autoregressive Conditional Skewness
Abstract
We present a new methodology for estimating time-varying conditional skewness. Our model allows for changing means and variances, uses a maximum likelihood framework with instruments, and assumes a non-central t distribution. We apply this method to daily, weekly, and monthly stock returns, and find that conditional skewness is important. In particular, we show that the evidence of asymmetric variance is consistent with conditional skewness. Inclusion of conditional skewness also impacts the persistence in conditional variance.
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Cites
Engle, R. F. (1982) · Econometrica · doi:10.2307/1912773 · Cited by 20,795
Cited by
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Chen, J., Hong, H., & Stein, J. C. (2001) · Journal of Financial Economics · doi:10.1016/s0304-405x(01)00066-6 · Cited by 1,907
Maxing out: Stocks as lotteries and the cross-section of expected returns
Bali, T. G., Cakici, N., & Whitelaw, R. F. (2011) · Journal of Financial Economics · doi:10.1016/j.jfineco.2010.08.014 · Cited by 1,624
Asymmetric correlations of equity portfolios
Ang, A., & Chen, J. (2002) · Journal of Financial Economics · doi:10.1016/s0304-405x(02)00068-5 · Cited by 1,522
Expected Idiosyncratic Skewness
Boyer, B., Mitton, T., & Vorkink, K. (2010) · Review of Financial Studies · doi:10.1093/rfs/hhp041 · Cited by 833
What good is a volatility model?
Engle, R. F., & Patton, A. J. (2001) · Quantitative Finance · doi:10.1088/1469-7688/1/2/305 · Cited by 688
Metadata
- Authors
- Harvey, C. R., & Siddique, A.
- Venue
- The Journal of Financial and Quantitative Analysis
- Publisher
- JSTOR
- Published
- 1999-12
- Volume
- 34
- Issue
- 4
- Pages
- 465
- ISSN
- 0022-1090 (ISSN-L)
- OpenAlex
- W3124570132
- Cited by
- 752
- References
- 1
- FWCI
- 16.41
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
