A hybrid GARCH and deep learning method for volatility prediction

DOI10.1155/2024/6305525zbMATH Open1541.62277MaRDI QIDQ6577868

Tesfahun Berhane, Hailabe T. Araya, Jane A. Aduda

Publication date: 24 July 2024

Published in: Journal of Applied Mathematics (Search for Journal in Brave)

zbMATH Keywords

volatilityhybrid modeldeep learningGARCH-family models

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05)

Cites Work

• Generalized autoregressive conditional heteroscedasticity
• Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation
• Threshold heteroskedastic models
• A new look at the statistical model identification
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: A hybrid GARCH and deep learning method for volatility prediction