Fuzzy multi-attribute information fusion approach for finance investment selection with the expert reliability

Abstract

Finance investment selection is important for an investment company in financial decision making. Multiple experts should be invited to make investment selection. The dependability of the investment results can be affected by the original decision information and the experts’ reliability. However, experts are not all knowledgeable and express their opinions with different forms of preference. In order to consider the influences of experts and keep the original information in the information aggregation process, this paper proposes a fuzzy information fusion approach with the expert reliability for investment selection. First, we analyze the influence of the reliability of the experts and constructed the experts’ reliability based on the similarity between experts. Second, power average operator combined with experts’ reliability is used to integrate the experts’ preference. The original information could be preserved under the greatest extent. Then, a fuzzy information fusion approach is developed for investment selection with the aim of demonstrating its effectiveness by retaining experts’ original views and risk preference information based the expert reliability. Finally, an investment selection example is applied to confirm in advance whether the decision maker selected is reliable and suitable for scheme selection. Moreover, it demonstrates the effectiveness of the proposed approach and applicability of it.