A stochastic programming approach to multicriteria portfolio optimization

Sakar, Ceren Tuncer
Köksalan, Mustafa Murat
We study a stochastic programming approach to multicriteria multi-period portfolio optimization problem. We use a Single Index Model to estimate the returns of stocks from a market-representative index and a random walk model to generate scenarios on the possible values of the index return. We consider expected return, Conditional Value at Risk and liquidity as our criteria. With stocks from Istanbul Stock Exchange, we make computational studies for the two and three-criteria cases. We demonstrate the tradeoffs between criteria and show that treating these criteria simultaneously yields meaningful efficient solutions. We provide insights based on our experiments.


An evolutionary algorithm for multiple criteria problems
Soylu, Banu; Köksalan, Murat; Department of Industrial Engineering (2007)
In this thesis, we develop an evolutionary algorithm for approximating the Pareto frontier of multi-objective continuous and combinatorial optimization problems. The algorithm tries to evolve the population of solutions towards the Pareto frontier and distribute it over the frontier in order to maintain a well-spread representation. The fitness score of each solution is computed with a Tchebycheff distance function and non-dominating sorting approach. Each solution chooses its own favorable weights accordin...
An Efficient Metaheuristic Algorithm for Engineering Optimization: SOPT
Hasançebi, Oğuzhan (2012-06-01)
Metaheuristic algorithms are well-known optimization tools which have been employed for solving a wide range of optimization problems so far. In the present study, a simple optimization (SOPT) algorithm with two main steps; namely exploration and exploitation, is provided for practical applications. Aside from a reasonable rate of convergence attained, the ease in its implementation and dependency on few parameters only are among the advantageous characteristics of the proposed SOPT algorithm. The efficienc...
An Advanced evolutionary programming method for mechanical system design: feasibility enhanced particle swarm optimization
Hasanoğlu, Mehmet Sinan; Dölen, Melik; Department of Mechanical Engineering (2019)
Constrained optimization problems constitute an important fraction of optimization problems in mechanical engineering domain. It is not rare for these problems to be highly-constrained where a specialized approach that aims to improve constraint satisfaction level of the whole population as well as finding the optimum is deemed useful especially when the objective functions are very costly. This dissertation introduces a new algorithm titled Feasibility Enhanced Particle Swarm Optimization (FEPSO) to handle...
Effective optimization with weighted automata on decomposable trees
Ravve, E. V.; Volkovich, Z.; Weber, Gerhard Wilhelm (Informa UK Limited, 2014-01-02)
In this paper, we consider quantitative optimization problems on decomposable discrete systems. We restrict ourselves to labeled trees as the description of the systems and we use weighted automata on them as our computational model. We introduce a new kind of labeled decomposable trees, sum-like weighted labeled trees, and propose a method, which allows us to reduce the solution of an optimization problem, defined in a fragment of Weighted Monadic Second Order Logic, on such a tree to the solution of effec...
Optimum design of steel frames using stochastic search techniques based on natural phenomena: A review
Saka, M. P. (2007-09-21)
Recent developments in optimization techniques that deal with finding the solution of combinatorial optimization problems has provided steel designers with new capabilities. These new optimization techniques use nature as a source of inspiration to develop new procedures for solving complex engineering problems. Among these, evolutionary algorithms mimic evolutionary biology and make use of the principle of the survival of the fittest to establish a numerical search algorithm. In the immune system algorithm...
Citation Formats
C. T. Sakar and M. M. Köksalan, “A stochastic programming approach to multicriteria portfolio optimization,” JOURNAL OF GLOBAL OPTIMIZATION, pp. 299–314, 2013, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/51522.