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- Title
Portfolio Robust Optimization Model and Its Application.
- Authors
Ying Gao; Yiou Li; Xiaoyuan Huang
- Abstract
Classical formulations of the portfolio optimization, such as mean-variance or Value-at-Risk(VaR) approaches, can result in a portfolio extremely sensitive to errors in the date, such as mean and covariance matrix. In this paper we propose a way to alleviate this problem in a tractable manner. We proposed a robust portfolio optimization model, which can be solved by using linear matrix inequalities (LMI) .To substantiate the conclusion we cite an empirical analysis which adopts correlated data from Shanghai Stock Exchange. The result indicates that the robust model of portfolio is efficient and feasible.
- Subjects
INVESTMENTS; ROBUST optimization; FINANCIAL risk; RANDOM variables; STOCK exchanges; LINEAR programming
- Publication
Journal of Systems Science & Information, 2007, Vol 5, Issue 1, p81
- ISSN
1478-9906
- Publication type
Article