• ISSN: 2010-023X
    • Frequency: Bimonthly
    • DOI: 10.18178/IJTEF
    • Editor-in-Chief: Prof.Tung-Zong (Donald) Chang
    • Executive Editor: Ms. Cherry L. Chen
    • Abstracting/ Indexing: Engineering & Technology Digital Library, ProQuest, Crossref, Electronic Journals Library, DOAJ , EBSCO, and Ulrich's Periodicals Directory
    • E-mail: ijtef@ejournal.net
IJTEF 2012 Vol.3(5): 347-350 ISSN: 2010-023X
DOI: 10.7763/IJTEF.2012.V3.225

A Comparative Analysis for forecasting the NAV’s of Indian Mutual Fund using Multiple Regression Analysis and Artificial Neural Networks

E. Priyadarshini and A. Chandra Babu
Abstract—Regression analysis is one of the popular method used for prediction and forecasting. Regression analysis is also used to understand which among the independent variables are related to the dependent variable, and to explore the forms of these relationships. In recent times, Artificial Neural Network has been successfully used in modeling financial time series due to its ability to model easily any type of parametric or nonparametric process and automatically and optimally transform the input data. In this paper ,the interaction effects of the various economic factors influencing the Net Asset Values of the Indian Mutual Funds was evaluated and the future NAV’s were forecasted for the following years using Regression Analysis and Artificial Neural Network and the performance of the two methods were compared based on standard statistical measures such as MAPE, RMSE, etc. Validity of the models were tested and the future NAV values of the mutual fund has been forecasted.

Index Terms—Prediction, time series. Multiple Regression Analysis, Artificial Neural Networks.

E. Priyadarshini is with Sathyabama University, Chennai, India. She is at present doing her research in Sathyabama University. (email:priyaeb@gmail.com).
A. Chandrababu is with Noorul Islam, University, Kumarakoil, India. (email: chandrababu_a@yahoo.co.in).

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Cite:E. Priyadarshini and A. Chandra Babu, "A Comparative Analysis for forecasting the NAV’s of Indian Mutual Fund using Multiple Regression Analysis and Artificial Neural Networks," International Journal of Trade, Economics and Finance vol.3, no.5, pp. 347-350, 2012.

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