Prediction accuracy improvement for Bitcoin market prices based on symmetric volatility information using artificial neural network approach

• Main Authors: Othman, Anwar Hasan Abdullah, Kassim, Salina, Rosman, Romzie, Redzuan, Nur Harena
• Format: Article
• Language: English; English
• Published: Springer Nature 2020
• Subjects: HB131 Methodology.Mathematical economics. Quantitative methods; HB221 Price
• Online Access: http://irep.iium.edu.my/78301/1/78301-Prediction%20accuracy%20improvement%20for%20Botcoin%20market%20prices...%20-%20scopus.pdf; http://irep.iium.edu.my/78301/2/78301-%20Prediction%20accuracy%20improvement%20for%20Bitcoin%20market%20prices.pdf; http://irep.iium.edu.my/78301/; https://link.springer.com/epdf/10.1057/s41272-020-00229-3?author_access_token=L2DMxsXLPVIsJmH_5IOjuVxOt48VBPO10Uv7D6sAgHtSnGVFWNTxpwE4wrOv6_erM2oJhoPCSYSF6fjDTV9fqKqZE9oiGh_WUomMvvP80X8HVDUwwwsKc4KL4uXIVv777KmpMpZhT8k9TM33s6cmEw%3D%3D; https://doi.org/10.1057/s41272-020-00229-3

Generally, information is the fundamental driver of assets pricing volatility in the financial market. This information can enter into the market either symmetrically or asymmetrically. The financial literature shows that Bitcoin market volatility is symmetrically informative and has a long memory t...