Abstract

: Financial forecasting which includes the financial data such as interest rate, exchange rate, stock market, mutual fund asset value and bankruptcy is the hottest topic for the researcher due to its importance in financial and managerial decision making. Survey of existing literature disclose that there is a demand for efficient forecasting capability model involving less computational load and fast forecasting capability. This paper fulfills this objective by developing functional link artificial neural network (FLANN) based forecasting model involving nonlinear inputs. Simulation study exhibits, the predicting model is effective and applicable in mutual fund NAV forecasting.

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