Possibilistic Decision-Making Models for Portfolio Selection Problems
The basic assumption for using probabilistic decision-making models for portfolio selection problems, such as Markowitz’s model, is that the situation of stock markets in future can be correctly reflected by security data in the past, that is, the mean and covariance of securities in future is similar to the past one. It is hard to ensure this kind of assumption for the real ever-changing stock markets. Possibilistic decision-making models for portfolio selection problems are based on possibility distributions, which are used to characterize experts’ knowledge. A possibility distribution is identified using the returns of securities associated with possibility grades provided by experts. Based on the obtained possibility distribution, we construct a possibilistic portfolio selection decision-making model as a quadratic programming problem. Because experts’ knowledge is very valuable, it is reasonable that possibilistic decision-making models are useful in real investment environment.
KeywordsStock Market Portfolio Selection Portfolio Return Possibility Distribution Portfolio Selection Problem
Unable to display preview. Download preview PDF.
- 5.Guo, P., Zeng, D., Shishido, H.: Group decision with inconsistent knowledge. IEEE Transactions on SMC, Part A 32, 670–679 (2002)Google Scholar
- 6.Guo, P., Tanaka, H.: Possibilistic data analysis and its application to portfolio selection problems. Fuzzy Economic Review 3/2, 3–23 (1998)Google Scholar
- 13.Markowitz, H.M.: Portfolio Selection: Efficient Diversification of Investments. John Wiley, New York (1959)Google Scholar
- 15.Ortí, J.J., Sáez, J., Terceño, A.: On the treatment of uncertainty in portfolio selection. Fuzzy Economic Review 7, 59–80 (2002)Google Scholar