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A Simplified Model for Portfolio Analysis
Abstract
This paper describes the advantages of using a particular model of the relationships among securities for practical applications of the Markowitz portfolio analysis technique. A computer program has been developed to take full advantage of the model: 2,000 securities can be analyzed at an extremely low cost—as little as 2% of that associated with standard quadratic programming codes. Moreover, preliminary evidence suggests that the relatively few parameters used by the model can lead to very nearly the same results obtained with much larger sets of relationships among securities. The possibility of low-cost analysis, coupled with a likelihood that a relatively small amount of information need be sacrificed make the model an attractive candidate for initial practical applications of the Markowitz technique.
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Citations
Cited by
An Engine, Not a Camera: How Financial Models Shape Markets
MacKenzie, D. (2006) · doi:10.7551/mitpress/9780262134606.001.0001 · Cited by 1,766
Risk, The Pricing of Capital Assets, and The Evaluation of Investment Portfolios
Jensen, M. C. (1969) · The Journal of Business · doi:10.1086/295182 · Cited by 942
The role of bitcoin in well diversified portfolios: A comparative global study
Kajtazi, A., & Moro, A. (2019) · International Review of Financial Analysis · doi:10.1016/j.irfa.2018.10.003 · Cited by 271
Metadata
- Authors
- Sharpe, W. F.
- Venue
- Management Science
- Published
- 1963-01
- Volume
- 9
- Issue
- 2
- Pages
- 277-293
- ISSN
- 0025-1909 (ISSN-L)
- 1526-5501
- OpenAlex
- W2090874083
- Cited by
- 2,719
- References
- 0
- FWCI
- 5.97
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A Simplified Model for Portfolio Analysis. https://app.cochat.ai/papers/10.1287/mnsc.9.2.277
- The paper
- Sharpe, W. F. (1963). A Simplified Model for Portfolio Analysis. Management Science. https://doi.org/10.1287/mnsc.9.2.277
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.
