Realised volatility prediction of high-frequency data with jumps based on machine learning

Asset price jumps are very common in financial markets, and they are essential to accurately predict volatility. This article focuses on 50 randomly selected stocks from the Chinese stock market, utilising high-frequency data to construct two jump models, the heterogeneous autoregressive quarticity...

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Bibliographic Details
Main Authors: Gao Yuyan, He di, Mu Yan, Zhao Hongmin
Format: Article
Language:English
Published: Taylor & Francis Group 2023-12-01
Series:Connection Science
Subjects:
Online Access:http://dx.doi.org/10.1080/09540091.2023.2210265