Portfolio optimization problems with linear programming models
نویسندگان
چکیده
In this paper, we discuss four models proposed by Konno, Cai, Teo and Markowitz respectively. Two groups of data (one from 33 securities over 72 months, the other from 63 securities over 120 months) are used to examine these models. Efficient frontiers are presented. The utility levels in the four models do not decrease at the same rate with the change of the risk-aversion factor. Cai’s model provides the highest utility value and Markowitz’s provides the lowest one in most cases. When the expected returns are confronted with the true ones at the end of a 10-month period, Markowitz’s and Konno’s models seem to have similar tendencies while Cai’s and Teo’s models seem to have similar tendencies, and the four models get higher true wealth compared with Nikkei 225 and Nikkei 500 index respectively in most cases.
منابع مشابه
Solving Linear Semi-Infinite Programming Problems Using Recurrent Neural Networks
Linear semi-infinite programming problem is an important class of optimization problems which deals with infinite constraints. In this paper, to solve this problem, we combine a discretization method and a neural network method. By a simple discretization of the infinite constraints,we convert the linear semi-infinite programming problem into linear programming problem. Then, we use...
متن کاملLexicographic goal programming approach for portfolio optimization
This paper will investigate the optimum portfolio for an investor, taking into account 5 criteria. The mean variance model of portfolio optimization that was introduced by Markowitz includes two objective functions; these two criteria, risk and return do not encompass all of the information about investment; information like annual dividends, S&P star ranking and return in later years which is ...
متن کاملStochastic Models for Portfolio Management with Minimum Transaction Lots
In this paper, we consider the problem of a decision maker who is concerned with the management of a portfolio over a finite horizon. The portfolio optimization problem involves portfolio rebalancing decisions in response to new information on market future prices of the risky assets. Rebalancing decisions are manifested in the revision of holdings through sales and purchases of assets. We assu...
متن کاملA nonlinear multi objective model for the product portfolio optimization: An integer programming
Optimization of the product portfolio has been recognized as a critical problem in industry, management, economy and so on. It aims at the selection of an optimal mix of the products to offer in the target market. As a probability function, reliability is an essential objective of the problem which linear models often fail to evaluate it. Here, we develop a multiobjective integer nonlinear cons...
متن کاملApplying Scenario Optimization to Portfolio Credit Risk
Standard market risk optimization tools, based on assumptions of normality, are ineffective for credit risk. In this paper, we develop three scenario optimization models for portfolio credit risk. We first create the trade risk profile and find the best hedge position for a single asset or obligor. The second model adjusts all positions simultaneously to minimize the regret of the portfolio sub...
متن کاملPrimal and dual robust counterparts of uncertain linear programs: an application to portfolio selection
This paper proposes a family of robust counterpart for uncertain linear programs (LP) which is obtained for a general definition of the uncertainty region. The relationship between uncertainty sets using norm bod-ies and their corresponding robust counterparts defined by dual norms is presented. Those properties lead us to characterize primal and dual robust counterparts. The researchers show t...
متن کامل