Application of Portfolio Using Fuzzy Logic

Abstract

ABSTRACT
A portfolio has to match the portfolio of long-term liabilities with the portfolio of assets. Key instruments in strategic asset liability management (ALM) are the adjustment of investments with respective policies and their interest rate analogous with the scenario of the market. We have given mathematical formulation of the investment problem in terms of stochastic problem (SP) and finally represented it in terms of Fuzzy Inference Engine by providing a fuzzy rule base. Extracting fuzzy rules from data allows relationships in the data to be modeled by “if-then” rules that are easy to understand, verify, and extend. This paper presents methods for extracting fuzzy rules by using fuzzy inference engine. The rule extraction methods are based on estimating clusters in the data; each cluster obtained corresponds to a fuzzy rule that relates a region in the input space to an output region. In various public sector banks, people are going to invest money under the heading of Portfolio in order to obtain maximum return on investment. Now, the bank has to decide in which policy to invest the money so that it gives maximum return with less time period by considering all the influencing factors.

Keywords: ALM, investment problem, stochastic formulation, fuzzy rule classification, fuzzy inference engine