skip to main content
Language:
Search Limited to: Search Limited to: Resource type Show Results with: Show Results with: Search type Index

Deep State-Space Model for Predicting Cryptocurrency Price

Information sciences, 2023-11 [Peer Reviewed Journal]

Attribution ;ISSN: 0020-0255 ;EISSN: 1872-6291

Digital Resources/Online E-Resources

Citations Cited by
  • Title:
    Deep State-Space Model for Predicting Cryptocurrency Price
  • Author: Sharma, Shalini ; Majumdar, Angshul ; Chouzenoux, Emilie ; Elvira, Víctor
  • Subjects: Engineering Sciences
  • Is Part Of: Information sciences, 2023-11
  • Description: Our work presents two fundamental contributions. On the application side, we tackle the challenging problem of predicting day-ahead crypto-currency prices. On the methodological side, a new dynamical modeling approach is proposed. Our approach keeps the probabilistic formulation of the state-space model, which provides uncertainty quantification on the estimates, and the function approximation ability of deep neural networks. We call the proposed approach the deep state-space model. The experiments are carried out on established cryptocurrencies (obtained from Yahoo Finance). The goal of the work has been to predict the price for the next day. Benchmarking has been done with both state-of-the-art and classical dynamical modeling techniques. Results show that the proposed approach yields the best overall results in terms of accuracy.
  • Publisher: Elsevier
  • Language: English
  • Identifier: ISSN: 0020-0255
    EISSN: 1872-6291
  • Source: Hyper Article en Ligne (HAL) (Open Access)
Back to results list
Go to Previous pagePrevious Result  7 NextGo to Next page
INSPIRE LIBRARY - TON DUC THANG UNIVERSITY (84-028) 37 755 057 Feedback
19 Nguyen Huu Tho St. Dist.7, HCM thuvien@tdtu.edu.vn

Copyright © 2017 INSPIRE LIBRARY - TON DUC THANG UNIVERSITY

Searching Remote Databases, Please Wait