Probabilistic forecasting of high-frequency realized cryptocurrency volatility via CEEMDAN-integrated autoregressive recurrent neural network

Physica A Statistical Mechanics and its Applications 2026

View at publisher
Authors: Yosep Na, Jun Young Byun, Jungyoon Song, Jungyoon Song, Jae Wook Song, Jae Wook Song
DOI: 10.1016/j.physa.2026.131364
Cited by: 1
References: 55

Fields of Study & Subjects

Blockchain Technology Applications and Security Stock Market Forecasting Methods Financial Risk and Volatility Modeling

Publication details

Journal / source
Physica A Statistical Mechanics and its Applications
Publisher
Elsevier BV
Volume
686
Pages
131364–131364
Publication date
4 February 2026
Language
EN