Forecasting of Net Asset Value of Indian Mutual Funds Using Firefly Algorithm-Based Neural Network Model

Mutual funds are considered as the simpler and hassle-free investment mechanism in India. The performance of various mutual funds is analysed by the investors before investing their money. Out of the different performance indicators of mutual funds, net asset value (NAV) happens to be one of them. The NAV data are nonlinear in nature. In this paper, the FLANN model is used for the 1-day and 5-day ahead NAV forecasting of two Indian mutual funds. The weights of the FLANN model are optimized using one of the bio-inspired algorithm, i.e. firefly algorithm. The prediction performance of the FLANN-FA model and basic FLANN are compared using RMSE and MAPE as evaluation measures. The simulation results indicate that the proposed model outperformed the basic FLANN model.