The DOI matches its Crossref record.
The Markowitz Optimization Enigma: Is ‘Optimized’ Optimal?
Abstract
This presentation comes from the Improving Portfolio Performance With Quantitative Models conference held in New York on April 13, 1989.
Overview
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Citations
Cited by
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DeMiguel, V., Garlappi, L., & Uppal, R. (2009) · Review of Financial Studies · doi:10.1093/rfs/hhm075 · Cited by 3,199
A well-conditioned estimator for large-dimensional covariance matrices
Ledoit, O., & Wolf, M. (2004) · Journal of Multivariate Analysis · doi:10.1016/s0047-259x(03)00096-4 · Cited by 3,046
An Engine, Not a Camera: How Financial Models Shape Markets
MacKenzie, D. (2006) · doi:10.7551/mitpress/9780262134606.001.0001 · Cited by 1,766
Portfolio Selection with Parameter and Model Uncertainty: A Multi-Prior Approach
Garlappi, L., Wang, T., & Uppal, R. (2004) · SSRN Electronic Journal · doi:10.2139/ssrn.671981 · Cited by 264
Deep Reinforcement Learning for Trading
Zhang, Z., Zohren, S., & Roberts, S. (2020) · The Journal of Financial Data Science · doi:10.3905/jfds.2020.1.030 · Cited by 227
Metadata
- Authors
- Michaud, R. O.
- Venue
- Financial Analysts Journal
- Publisher
- Informa UK Limited
- Published
- 1989-01
- Volume
- 45
- Issue
- 1
- Pages
- 31-42
- ISSN
- 0015-198X (ISSN-L)
- 1938-3312
- OpenAlex
- W3125435015
- Cited by
- 1,328
- References
- 0
- FWCI
- 1.78
- Type
- journal article
- Language
- en
- Open access
- closed
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
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- CoChat. (2026). Citation check: The Markowitz Optimization Enigma: Is ‘Optimized’ Optimal? https://app.cochat.ai/papers/10.2469/faj.v45.n1.31
- The paper
- Michaud, R. O. (1989). The Markowitz Optimization Enigma: Is ‘Optimized’ Optimal? Financial Analysts Journal. https://doi.org/10.2469/faj.v45.n1.31
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.
