Please use this identifier to cite or link to this item: http://umt-ir.umt.edu.my:8080/handle/123456789/9646
Title: Predicting performance of unit trust by using artificial neural fuzzy inference system
Authors: Kenard Tan Peng Loong
Keywords: Kenard Tan Peng Loong
LP 11 FST 2 2009
Issue Date: 2009
Publisher: Universiti Malaysia Terengganu
Abstract: An Artificial Intelligence model is successful in scientific fields such as medicine and engineering field. In this paper Artificial Neural Fuzzy Inference System (ANFIS) is developed for unit trust prediction. ANFIS are learning a relationship between inputs and outputs and it is dependent on the data to achieve a highly nonlinear mapping and it is superior to common linear methods in reproducing nonlinear time series. ANFIS have been used to predict the performance of three types of fund in Prudential Management fund based on the net asset value. ANFIS is used to forecast the future prices so investor can know how well each unit trust does perform and it is useful to help investor in making decision to invest in unit trust.
URI: http://umt-ir.umt.edu.my:8080/xmlui/handle/123456789/9646
Appears in Collections:Fakulti Sains dan Teknologi

Files in This Item:
File Description SizeFormat 
LP 11 FST 2 2009 Abstract.pdf494.85 kBAdobe PDFView/Open
LP 11 FST 2 2009 Full text.pdf
  Restricted Access
4.88 MBAdobe PDFView/Open Request a copy


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.