Forming the stock optimized portfolio using model Grey based on C5 and the Shuffled frog leap algorithm

Abstract

The classic approach of the portfolio optimization is solvable by the classic models of mathematic planning when the number of assets able to investment and the available constraints in the market are limited. However, when considering the terms and constraints of real world, the classic approach of portfolio optimization is not easily solvable using the classical methods of mathematical optimization. It is why, using the methods Meta-heuristic and the evolutionary algorithms in portfolio optimization has been of the most Important issues recently. The main objective of present research is to present an appropriate practical approach to select the optimal stock portfolio. On this regard, a multi-objective mathematical programming model has been designed based on Grey Relational Analysis and C5 algorithm, and then to solve this model and in order to achieve the optimized combination of the rank and risk, the Shuffled Frog-Leaping Algorithm was used. The presented methodology was used in Tehran Stock Exchange.

Keywords:

• Grey Relational Analysis
• C5 Algorithm
• Shuffled Frog Leap Algorithm
• Portfolio Selection
• Data Mining