Title: Predicting the net asset value of mutual fund: an extended literature review

Authors: Shikha Singla; Gaurav Gupta

Addresses: Department of Computer Science and Engineering, Punjabi University, Patiala (Pb), India ' Department of Computer Science and Engineering, Punjabi University, Patiala (Pb), India

Abstract: Mutual funds have emerged as the most dynamic segment of the Indian financial system. With its potential to provide higher return by investment in diversified securities, mutual funds emerge as one of the most promising investments in uncertain markets. With a variety of mutual funds competing in the present scenario market, it becomes a challenging decision for the investor to balance risk and return trade-off on the portfolio to maximise returns. Therefore, the important aspect for portfolio manager is to predict the net asset value (NAV) of mutual funds. Various methods and techniques in the field of economics and computer science have been used in the quest to gain insights into NAV prediction. The aim of the paper is to provide an extended literature review of different techniques in different areas of computer science in order to explore the future possibilities. This paper explores the past research work and proposes the future roadmap to predict the NAV of mutual funds by using different techniques with greater accuracy.

Keywords: net asset value; NAV; radial basis function; RBF; functional link artificial neural network; FLANN; mutual fund.

DOI: 10.1504/IJAIS.2021.117841

International Journal of Adaptive and Innovative Systems, 2021 Vol.3 No.1, pp.14 - 24

Received: 18 Mar 2019
Accepted: 07 Feb 2020
Published online: 04 Oct 2021 *

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