We propose $\ell_1 $ norm regularized quadratic surface support vector machine models for
binary classification in supervised learning. We establish their desired theoretical properties …

Portfolio selection is a fundamental problem in finance with challenges of dimensionality
and market complexities. This paper focuses on the prevalent strategy of passive portfolio …

Designed as remedies for uncertain parameters and tiny optimal weights in the portfolio
selection problem, we consider a class of distributionally robust portfolio optimization …

The short-term sparse portfolio optimization (SSPO) models are dedicated to constructing
sparse portfolio in each short period. In this paper, we discuss some existing SSPO model …

In recent years, distributionally robust optimization (DRO) has received a lot of interest due
to its ability to reduce the worst-case risk when there is a perturbation to the data-generating …

We address the problem of partial index tracking, replicating a benchmark index using a
small number of assets. Accurate tracking with a sparse portfolio is extensively studied as a …

Index tracking is a well-established financial strategy for passive investing. Typical index
tracking models are single period in nature, deriving an optimal tracking portfolio based on …

Multiobjective index tracking models optimize portfolios considering investors' desire to
replicate or outperform a market index. It is possible to search for the best portfolio in the …

In this paper, a class of smooth penalty functions is proposed for constrained optimization
problem. It is put forward based on L p, a smooth function of a class of exact penalty function …

This paper provides a solution to the customer portfolio for a given fixed desired expected
rate of return under constraints based. We restrict the solution to a class of finite, ergodic …