In this paper, we studied the problem of risky portfolio selection under uncertainty. Different from risk-return analytical methodology, we formulated a model under maximum minimal criterion of uncertain decision-making theory. If the investor had no any distribution information of the returns and (s)he knew the variation scopes of the returns by his/her knowledge of the market information or experts’ evaluations of the alternative risky assets, then we showed that the optimal portfolio strategy of the model under maximal minimal criterion could be obtained by solving linear programming. If the returns were known to be normal distributed, the investor’s optimal portfolio strategy could be obtained by solving a nonlinear programming. The paper also provided an algorithm to solve this programming. At last, the paper compared this model with Markowitz’s mean-varience (M-V) model and Young’s minmax model, and pointed out the distinctions and similarities between our model and the other two.
Quality & Quantity – Springer Journals
Published: Jul 19, 2005
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
All the latest content is available, no embargo periods.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud