Alireza Ghahtarani

University of Toronto | U of T · Department of Mechanical and Industrial engineering

Asset-liability management (ALM) is a challenging task faced by pension funds due to the uncertain nature of future asset returns and interest rates. To address this challenge, this paper presents a new mathematical model that uses a Worst-case Conditional Value-at-Risk (WCVaR) constraint to ensure that the funding ratio remains above a regulator-m...

The K-adaptability problem is a special case of adaptive robust optimization with discrete recourse that aims to prepare solutions under uncertainty, and select among them upon full knowledge of the realized scenario. We propose a novel approach to solve K-adaptability problems with linear objective and constraints, binary first-stage decision vari...

We propose a novel approach to solve K-adaptability problems with convex objective and constraints and integer first-stage decisions. A logic-based Benders decomposition is applied to handle the first-stage decisions in a master problem, thus the sub-problem becomes a min-max-min robust combinatorial optimization problem that is solved via a double...

This paper reviews 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, a...

In this paper, a new mathematical formulation of a portfolio selection problem is developed. This model is based on the difference between fundamental value and market value of assets. The proposed model is especially applicable in bubble conditions. Input data of the developed model are subjected to uncertainty. To consider data uncertainty, the Z...

A portfolio selection model is developed in this study, using a new risk measure. The proposed risk measure is based on the fundamental value of stocks. For this purpose, a mathematical model is developed and transformed into an integer linear programming. In order to analyze the model's efficiency, the actual data of the Tehran Stock Exchange mark...

In this research, we identify factors influencing the behavior of knowledge sharing and customer purchasing intention based on two theories of social capital and social interaction. The conceptual model, designed based on theoretical foundations, includes the dimensions of these two theories. Moreover, knowledge/information sharing is considered as...

In this paper, mathematical modeling is developed for portfolio selection problem under uncertainty circumstances with regard to a robust stochastic variable. Two popular and common approaches in the area of modeling uncertainty are robust optimization and stochastic programming. These two methods are used with different considerations in mathemati...

The portfolio selection problem is one of the main investment management problems. In the portfolio selection problem, robustness is sought against uncertainty or variability in the value of the parameters of the problem. In this paper, an extended mean absolute deviation model named the m-MAD model is applied to construct a new robust portfolio se...

This paper proposes a robust optimization approach for bi-objective portfolio selection problem. We propose mean-CVaR as a bi-objective model and in this model we consider parameter uncertainty. We use Bertsimas and sim approach to consider uncertainty in the model and we try to use ideal and anti-ideal compromise programming to solve model. This s...

This paper develops a bi-objective portfolio selection problem that maximizes returns and minimizes a risk measure called conditional Drawdown (CDD). The drawdown measures include the maximal Drawdown and Average Drawdown as its limiting case. The CDD family of risk functional is similar to conditional value at Risk (CVaR). In this paper, the fuzzy...