Abstract:

In order to achieve portfolio optimization, it is necessary to determine when and to what extent securities should be included in the portfolio. As being a model carried out to realize this purpose, game theory aims to create the highest yielding portfolio that can occur at the given lowest risk level with the minimax principle. Modern portfolio theory, on the other hand, intends to create portfolios that provide the highest return at a certain risk level or the lowest risk at a certain level of return. In the study, it was aimed to create optimum portfolios for each month by solving 12 separate linear programming models within the scope of the game theory minimax principle and 12 separate quadratic programming models within the scope of modern portfolio theory. The analyses are performed on a data set of 200 stocks, which have had the highest trading volume and continuous trading every month between 2013 and 2021 in Borsa Istanbul. The performances of the portfolios derived from both theories compared with each other and also with alternative investment instruments’ returns. The findings indicate that the portfolios offered by the modern portfolio theory have better ex-post results, whereas ex-ante returns of the portfolios suggested by the game theory are superior.

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