Robust CCMV model with short selling and risk-neutral interest rate

Khodamoradi, Tahereh; Salahi, Maziar; Najafi, Ali Reza

doi:10.1016/j.physa.2020.124429

Cited by 11 publications

(5 citation statements)

References 33 publications

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“…Second, it is not easy for portfolio managers and investors to use portfolio optimization model to obtain stable and high returns. The extension of our model with return forecasting methods in Dai and Zhu (2020); Dai, Dong, Kang, and Hong (2020); Dai, Zhu, and Kang (2021); Dai, Zhuo, Kang, and Wen (2021) and other constraints such as short selling, risk‐neutral interest rate in Khodamoradi, Salahi, and Najafi (2020) can be considered as future research directions.…”

Section: Discussionmentioning

confidence: 99%

Some new efficient mean–variance portfolio selection models

Dai

Kang

2021

Int. J Fin Econ

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The poor out‐of‐sample performance of mean–variance portfolio model is mainly caused by estimation errors in the covariance matrix and the mean return, especially the mean return vector. Meanwhile, in financial practice, what most investors actually like is to hold a few stocks in their portfolio. The goal of this paper is to propose some new efficient mean–variance portfolio selection models by considering the following aspects: (i) use the L1‐regularization in objective function to obtain sparse portfolio; (ii) use the shrinkage method of Ledoit and Wolf, Journal of Economics Financial, 2003, 10, 603–621 to estimate the covariance matrix; (iii) use the robust optimization method to mitigate the estimation errors of the expected return. Finally, empirical analysis demonstrates that the proposed strategies have better out‐of‐sample performance.

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Section: Discussionmentioning

confidence: 99%

Some new efficient mean–variance portfolio selection models

Dai

Kang

2021

Int. J Fin Econ

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“…where r L and r U are, respectively, the lower and upper bounds of assets returns and Q L and Q U are the lower and the upper bounds of the covariance matrix elements while stipulating also that Q must remain positive semi-definite. It has been shown that, with these uncertainty sets, the robust counterparts could be tractably formulated as min Khodamoradi et al (2020) used similar uncertainty sets for a cardinality-constrained mean-variance PSP that allows short selling. However, Chen & Tan (2009) argued that many parameters like the return of assets are not symmetric which means the upside deviation is different from the downside deviation.…”

Section: Classical Uncertainty Sets For the Mean-variance Pspmentioning

confidence: 99%

Robust Portfolio Selection Problems: A Comprehensive Review

Ghahtarani¹,

Ahmed²,

Ghasemi³

2021

Preprint

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In this paper, we provide a comprehensive review of recent advances in robust portfolio selection problems and their extensions, from both operational research and financial perspectives. A multi-dimensional classification of the models and methods proposed in the literature is presented, based on the types of financial problems, uncertainty sets, robust optimization approaches, and mathematical formulations. Several open questions and potential future research directions are identified.

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“…0}, where µ L ∈ R n and µ U ∈ R n are the lower and upper bounds of mean vector µ, Σ L ∈ R n×n and Σ U ∈ R n×n are the lower and the upper bounds of the covariance matrix Σ, respectively, and Σ is positive semi-definite. Khodamoradi et al [22] used box uncertainty sets for a cardinal-constrained mean-variance portfolio problem which allows short selling. Swain and Ojha [10] analyzed the robust version of the mean-variance portfolio problem and mean-semi-variance portfolio problem with box uncertainty sets.…”

Section: Introductionmentioning

confidence: 99%

Robust and Sparse Portfolio: Optimization Models and Algorithms

Zhao,

Jiang,

Yang

2023

Mathematics

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The robust and sparse portfolio selection problem is one of the most-popular and -frequently studied problems in the optimization and financial literature. By considering the uncertainty of the parameters, the goal is to construct a sparse portfolio with low volatility and decent returns, subject to other investment constraints. In this paper, we propose a new portfolio selection model, which considers the perturbation in the asset return matrix and the parameter uncertainty in the expected asset return. We define three types of stationary points of the penalty problem: the Karush–Kuhn–Tucker point, the strong Karush–Kuhn–Tucker point, and the partial minimizer. We analyze the relationship between these stationary points and the local/global minimizer of the penalty model under mild conditions. We design a penalty alternating-direction method to obtain the solutions. Compared with several existing portfolio models on seven real-world datasets, extensive numerical experiments demonstrate the robustness and effectiveness of our model in generating lower volatility.

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Robust CCMV model with short selling and risk-neutral interest rate

Cited by 11 publications

References 33 publications

Some new efficient mean–variance portfolio selection models

Some new efficient mean–variance portfolio selection models

Robust Portfolio Selection Problems: A Comprehensive Review

Robust and Sparse Portfolio: Optimization Models and Algorithms

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