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Treating return of mudharabah time deposit as investment instrument: A utilization of artificial neural networks (ANNs)

  • Computer Science
  • Economics


Purpose – The purpose of this paper is to propose the development of return forecasting model for mudharabah time deposit product in Islamic bank based on artificial neural networks (ANNs). Design/methodology/approach – The analysis consists of two main elements. First element is the identification and selection of significant macroeconomic variables that determine return volatility of mudharabah time deposit in Indonesian Islamic bank industry. Second element is the implementation of appropriate ANNs model according to neural networks properties, and model evaluation based on simulated return predictions of mudharabah time deposit product in Bank Syariah Mandiri (RR-BSM). Findings – It is shown that monthly changes of return can be predicted quite well. The model provides a satisfactory result in forecasting RR-BSM for 12 months ahead with 95.22 per cent accuracy. These results suggest that the ANNs can be applied as an adequate tool to help depositors in predicting future return of mudharabah time deposit product. Originality/value – There is believed to be no other empirical study of Islamic banks that exclusively examines the utilization of ANNs to forecast time deposit return as well as return from other investment instruments.

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