The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
An Extreme Value Approach to Estimating Volatility and Value at Risk*
Abstract
This article determines the type of asymptotic distribution for the extreme changes in U.S. Treasury yields. The thin‐tailed Gumbel and exponential distributions are strongly rejected against the fat‐tailed Frechet and Pareto distributions. The empirical results indicate that the volatility of maximal and minimal changes in interest rates declines as time‐to‐maturity rises, yielding a downward‐sloping volatility curve for the extremes. The article proposes an extreme value approach to estimating value at risk and shows that the statistical theory of extremes provides a more accurate approach for risk management and value at risk (VaR) calculations than the standard models.
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Citations
Cites
Engle, R. F. (1982) · Econometrica · doi:10.2307/1912773 · Cited by 20,795
Embrechts, P., Klüppelberg, C., & Mikosch, T. (1997) · doi:10.1007/978-3-642-33483-2 · Cited by 4,402
Cited by
Does Systemic Risk in the Financial Sector Predict Future Economic Downturns?
Allen, L., Bali, T. G., & Tang, Y. (2012) · Review of Financial Studies · doi:10.1093/rfs/hhs094 · Cited by 438
Self-citationIs There an Intertemporal Relation between Downside Risk and Expected Returns?
Bali, T. G., Demirtas, K. O., & Levy, H. (2009) · Journal of Financial and Quantitative Analysis · doi:10.1017/s0022109009990159 · Cited by 286
Self-citationSystemic risk: The impact of COVID-19
Rizwan, M. S., Ahmad, G., & Ashraf, D. (2020) · Finance Research Letters · doi:10.1016/j.frl.2020.101682 · Cited by 282
Tomar, S., & Kadaverugu, R. (2025) · Disaster Resilience and Green Growth · doi:10.1007/978-981-95-1588-2_5 · Cited by 2
Metadata
- Authors
- Bali, T. G.
- Venue
- The Journal of Business
- Publisher
- University of Chicago Press
- Published
- 2003-01
- Volume
- 76
- Issue
- 1
- Pages
- 83-108
- ISSN
- 0021-9398 (ISSN-L)
- 1537-5374
- OpenAlex
- W2083233882
- Cited by
- 188
- References
- 2
- FWCI
- 15.46
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
