Portfolio optimization has always been a challenging proposition in finance and
management. Portfolio optimization facilitates in selection of portfolios in a volatile market …

Robust portfolio optimization refers to finding an asset allocation strategy whose behavior
under the worst possible realizations of the uncertain inputs, eg, returns and covariances, is …

This paper reviews recent advances in robust portfolio selection problems and their
extensions, from both operational research and financial perspectives. A multi-dimensional …

Cardinality-constrained portfolio optimization aims at determining the investment weights on
given assets using the historical data. This problem typically requires three constraints …

Traditional mean-variance (MV) models, considered effective in stable conditions, often
prove inadequate in uncertain market scenarios. Therefore, there is a need for more robust …

Portfolios employing a (factor) risk model are usually constructed using a two step process:
first, the risk model parameters are estimated, then the portfolio is constructed. Recent works …

Portfolio management is an important financial task, which helps to activate the capital
market and boost investor confidence by finding a long-term profitable policy. Reinforcement …

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 …

The cardinality-constrained mean-variance portfolio problem has garnered significant
attention within contemporary finance due to its potential for achieving low risk while …

Inspired by sparse learning, the Markowitz mean-variance model with a sparse
regularization term is popularly used in sparse portfolio optimization. However, in penalty …