The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
On Portfolio Optimization: Forecasting Covariances and Choosing the Risk Model
Open accessAbstract
We evaluate the performance of models for the covariance structure of stock returns, focusing on their use for optimal portfolio selection. We compare the models' forecasts of future covariances and the optimized portfolios' out-of-sample performance. A few factors capture the general covariance structure. Portfolio optimization helps for risk control, and a three-factor model is adequate for selecting the minimum-variance portfolio. Under a tracking error volatility criterion, which is widely used in practice, larger differences emerge across the models. In general more factors are necessary when the objective is to minimize tracking error volatility.
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Cites
Common risk factors in the returns on stocks and bonds
Fama, E. F., & French, K. R. (1993) · Journal of Financial Economics · doi:10.1016/0304-405x(93)90023-5 · Cited by 25,754
Cited by
Optimal Versus Naive Diversification: How Inefficient is the 1/ N Portfolio Strategy?
DeMiguel, V., Garlappi, L., & Uppal, R. (2009) · Review of Financial Studies · doi:10.1093/rfs/hhm075 · Cited by 3,199
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
Metadata
- Authors
- Chan, L. K. C., Karceski, J., & Lakonishok, J.
- Venue
- Review of Financial Studies
- Publisher
- Oxford University Press (OUP)
- Published
- 1999-10
- Volume
- 12
- Issue
- 5
- Pages
- 937-974
- ISSN
- 0893-9454 (ISSN-L)
- 1465-7368
- OpenAlex
- W2890402023
- Cited by
- 569
- References
- 1
- FWCI
- 14.36
- Type
- journal article
- Language
- en
- Open access
- green
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- Chan, L. K. C., Karceski, J., & Lakonishok, J. (1999). On Portfolio Optimization: Forecasting Covariances and Choosing the Risk Model. Review of Financial Studies. https://doi.org/10.1093/rfs/12.5.937
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