Solving a Non-Linear Constrained Portfolio Optimization Problem; Applications of Lagrange Kuhn-Tucker Method
Solving a Non-Linear Constrained Portfolio Optimization Problem; Applications of Lagrange Kuhn-Tucker Method

Summary/Abstract: Individual or corporate investors try to create a portfolio that minimizes risk and maximizes returns when investing in stocks. One of the most beautiful models that make portfolio selection according to these conditions is Markowitz's mean–variance model. By using this model, we constitute optimal portfolios from 30 stocks strongest capitals in Turkey. The aim of this study is to find the weight of the stocks to be invested in the optimum portfolio that is created, that is, to calculate how much investment should be made to which stock. In this case, as it is expected, the problem of non-linear constrained portfolio optimization with single-objective function is obtained. In this paper, the weights of the stocks that make up the optimal portfolios are solved by using the Kuhn-Tucker method and Matlab programming language rather than the traditional methods.

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