In this paper, we propose formulations and algorithms for robust portfolio optimization under both aleatory uncertainty (i.e., natural variability) and epistemic uncertainty (i.e., imprecise probabilistic information) arising from interval data. Epistemic uncertainty is represented using two approaches: (1) moment bounding approach and (2) likelihood-based approach. This paper first proposes a ...

As many data-driven fields, finance is rich in problems requiring high computational power and intelligent systems techniques. In particular, the problem of selecting an optimal financial portfolio can be conveniently represented as a constrained optimization problem or a decisionmaking problem. The aim of this paper is to show how to express the optimal portfolio selection problem from a decis...

return maximization or risk minimization is goal in portfolio optimization based on mean variance theory. the structure of correlation matrices and individual variance of each asset are two main factors in optimization with risk minimization object. it’s necessary to use appropriate variance and correlation coefficient for time series with clustering volatilities feature, too. in this research,...

Abstract Project selection for a portfolio is pivotal decision in the pharmaceutical industry. In this paper, we study optimization problem companies considering uncertainty of cost each phase drug development and specific value annual budget. The presented model suitable to make investment decisions multi-phase projects stochastic approach applied handle model. Post-optimality analysis budget ...

The past decade has seen a growing interest in inverse optimization. It has been shown that duality yields very efficient algorithms for solving inverse linear programming problems. In this paper, we consider a special class of conic programs that admits a similar duality and show that the corresponding inverse optimization problems are efficiently solvable. We discuss the applications of inver...

index tracking is the process of developing a portfolio that reproduces the performance of an index. the tracker portfolio has relatively good diversity and low turnover and low transaction costs. in this paper we applied a binary programming model for index tracking problem. in this model the number of assets for portfolio construction is defined by portfolio manager. the robust optimization f...

We develop an optimization method for constructing investment portfolios that dominate a given benchmark portfolio in terms of third-degree stochastic dominance. Our approach relies on the properties of the semivariance function, a refinement of an existing ‘super-convex’ dominance condition and quadratic constrained programming. We apply our method to historical stock market data using an indu...