The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Sparse and stable Markowitz portfolios
Open accessAbstract
We consider the problem of portfolio selection within the classical Markowitz mean-variance framework, reformulated as a constrained least-squares regression problem. We propose to add to the objective function a penalty proportional to the sum of the absolute values of the portfolio weights. This penalty regularizes (stabilizes) the optimization problem, encourages sparse portfolios (i.e., portfolios with only few active positions), and allows accounting for transaction costs. Our approach recovers as special cases the no-short-positions portfolios, but does allow for short positions in limited number. We implement this methodology on two benchmark data sets constructed by Fama and French. Using only a modest amount of training data, we construct portfolios whose out-of-sample performance, as measured by Sharpe ratio, is consistently and significantly better than that of the naïve evenly weighted portfolio.
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An iterative thresholding algorithm for linear inverse problems with a sparsity constraint.
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Self-citationOptimal Versus Naive Diversification: How Inefficient is the 1/ N Portfolio Strategy?
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Cited by
Sparse Models and Methods for Optimal Instruments With an Application to Eminent Domain
(2012) · Econometrica · doi:10.3982/ecta9626 · Cited by 889
DC formulations and algorithms for sparse optimization problems
Gotoh, J.-Y., Takeda, A., & Tono, K. (2018) · Mathematical Programming · doi:10.1007/s10107-017-1181-0 · Cited by 184
Metadata
- Authors
- Brodie, J., Daubechies, I., De Mol, C., Giannone, D., & Loris, I.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2009-07-28
- Volume
- 106
- Issue
- 30
- Pages
- 12267-12272
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2105630053
- Cited by
- 481
- References
- 16
- FWCI
- 19.39
- Type
- journal article
- Language
- en
- Open access
- green
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