Leveraging Cuckoo Search for Extreme Learning Machine for Mutual Fund Forecasting

A mutual fund is a key financial tool that pools funds from diverse investors, strategically investing them in various markets and securities based on predefined objectives. This study introduces an innovative hybrid model, combining ELM and cuckoo search to forecast the mutual fund’s net asset value (NAV), including UTI equity and SBI magnum equity, over 15, 30, and 45 days. The hybrid model is rigorously compared with ELM, BPNN, and FLANN, using test data and metrics like RMSE, ARV, MAPE, Theil’s U and MAE statistic. Results highlight the hybrid model’s robustness in predicting NAV fluctuations, demonstrating high accuracy even in the presence of influential factors. This resilience positions the ELM-CS model as a promising tool for informed mutual fund investment decisions, offering a forward-looking perspective in the dynamic financial landscape.