—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
—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.
A. Chandrababu is with Noorul Islam, University, Kumarakoil, India.
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.