Deep State-Space Model for Predicting Cryptocurrency Price - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Article Dans Une Revue Information Sciences Année : 2023

Deep State-Space Model for Predicting Cryptocurrency Price

Résumé

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.
Fichier principal
Vignette du fichier
Decrypt.pdf (1.6 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04358461 , version 1 (21-12-2023)

Licence

Paternité

Identifiants

  • HAL Id : hal-04358461 , version 1

Citer

Shalini Sharma, Angshul Majumdar, Emilie Chouzenoux, Víctor Elvira. Deep State-Space Model for Predicting Cryptocurrency Price. Information Sciences, In press. ⟨hal-04358461⟩
15 Consultations
5 Téléchargements

Partager

Gmail Facebook X LinkedIn More