Deep learning with small and big data of symmetric volatility information for predicting daily accuracy improvement of jkii prices

HIGHLIGHTS

• who: Mohammed Ayoub Ledhem and colleagues from the Department of Economics, University Centre of Maghnia, Maghnia, Algeria have published the paper: Deep learning with small and big data of symmetric volatility information for predicting daily accuracy improvement of JKII prices, in the Journal: (JOURNAL) of 12/07/2021
• what: The aim of this paper is to predict the daily accuracy improvement for the Jakarta Islamic Index (JKII) prices using deep learning (DL) with small and big data of symmetric volatility information. Since this research is focussing on the factor of volatility in the JKII, Irsalinda . . .
  

   

  

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