The DOI matches its Crossref record.
Value at Risk
Abstract
This article is a self-contained introduction to the concept and methodology of value at risk (VAR), a recently developed tool for measuring an entity's exposure to market risk. We explain the concept of VAR and then describe in detail the three methods for computing it—historical simulation, the delta-normal method, and Monte Carlo simulation. We also discuss the advantages and disadvantages of the three methods for computing VAR. Finally, we briefly describe stress testing and two alternative measures of market risk.
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Cited by
Empirical prediction intervals improve energy forecasting
Kaack, L. H., Apt, J., Morgan, M. G., & McSharry, P. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1619938114 · Cited by 43
Metadata
- Authors
- Linsmeier, T. J., & Pearson, N. D.
- Venue
- Financial Analysts Journal
- Publisher
- Informa UK Limited
- Published
- 2000-03
- Volume
- 56
- Issue
- 2
- Pages
- 47-67
- ISSN
- 0015-198X (ISSN-L)
- 1938-3312
- OpenAlex
- W2107434174
- Cited by
- 313
- References
- 0
- FWCI
- 6.62
- Type
- journal article
- Language
- en
- Open access
- closed
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How to cite
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- CoChat. (2026). Citation check: Value at Risk. https://app.cochat.ai/papers/10.2469/faj.v56.n2.2343
- The paper
- Linsmeier, T. J., & Pearson, N. D. (2000). Value at Risk. Financial Analysts Journal. https://doi.org/10.2469/faj.v56.n2.2343
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.
