The application of model predictive control on stock portfolio optimization without loan

A stock portfolio is a collection of assets owned by investors, such as companies or individuals. The determination of the optimal stock portfolio is an important issue for the investors. Management of investors’ capital in portfolio investment can be regarded as a dynamic optimal control problem. In this research, we propose Model Predictive Control (MPC) as a management strategy to solve the portfolio optimization problem. A basic explanation of the control theory and its application to the management problem is described. The management strategy of this research considers: constraints of the portfolio assets and the cost of transactions. Subsequently, a practical application of the solution is implemented on 3 company’s stocks. The simulation results show that the performance of proposed controller satisfies the state and control constraints. The amount of capital owned by the investor as the output of system shows a significant increase.A stock portfolio is a collection of assets owned by investors, such as companies or individuals. The determination of the optimal stock portfolio is an important issue for the investors. Management of investors’ capital in portfolio investment can be regarded as a dynamic optimal control problem. In this research, we propose Model Predictive Control (MPC) as a management strategy to solve the portfolio optimization problem. A basic explanation of the control theory and its application to the management problem is described. The management strategy of this research considers: constraints of the portfolio assets and the cost of transactions. Subsequently, a practical application of the solution is implemented on 3 company’s stocks. The simulation results show that the performance of proposed controller satisfies the state and control constraints. The amount of capital owned by the investor as the output of system shows a significant increase.