Title: A literature survey on the performance prediction of mutual funds

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 are excellent medium for investors to invest, who do not have much know-how about financial markets. Investors generally take fund's historical performance and their funds rating as harbinger for its performance prediction. This myopic selection and prediction criterion sometimes lead to wrong funds allocation and hence poor portfolio performance. Performance prediction depends upon number of internal factors like GDP growth, inflation, business sentiments and external factors too like fed rates, political stability, world growth, currency fluctuations, etc., which are very difficult to predict precisely. However, in past, there had been many studies in India as well as abroad which tried to predict the performance by using various statistical techniques. This review paper covers such studies and various techniques used to check the fund's performance. Through this survey it is observed that performance analysis of mutual funds needs an extensive in-depth analysis of various factors and further study can be done to improve the predictability and volatility of mutual fund performance. In end, this paper gives a brief literature review of mutual funds' performance prediction models used domestically and internationally.

Keywords: mutual fund; performance evaluation; net asset value; NAV; data envelopment analysis; DEA; backpropagation network; BPN.

DOI: 10.1504/IJCSYSE.2020.109130

International Journal of Computational Systems Engineering, 2020 Vol.6 No.1, pp.46 - 51

Received: 18 Mar 2019
Accepted: 12 Feb 2020
Published online: 21 Aug 2020 *

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