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An empirical net asset value forecasting model based on optimised ANN using elephant herding strategy

Author

Listed:
  • Sarbeswara Hota
  • Kuhoo
  • Debahuti Mishra
  • Srikanta Patnaik

Abstract

Net asset value (NAV) prediction of mutual funds is one of the promising tasks of financial time series data forecasting. It enables the investors to choose the desired mutual fund for investing. Artificial neural network (ANN) is well suited for NAV prediction as the NAV data are nonlinear in nature. This paper proposes the ANN model hybridised with elephant herding optimisation (EHO) algorithm to predict the NAV of different interval days ahead for two of the Indian mutual funds. The prediction performance of ANN-EHO model is compared with ANN, ANN-GA, ANN-PSO and ANN-DE. The results implicate that ANN-EHO model is superior to other four models.

Suggested Citation

  • Sarbeswara Hota & Kuhoo & Debahuti Mishra & Srikanta Patnaik, 2020. "An empirical net asset value forecasting model based on optimised ANN using elephant herding strategy," International Journal of Management and Decision Making, Inderscience Enterprises Ltd, vol. 19(1), pages 118-132.
    • Handle: RePEc:ids:ijmdma:v:19:y:2020:i:1:p:118-132
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