Volatility forecasting for stock market incorporating macroeconomic variables based on GARCH-MIDAS and deep learning models
Year of publication: |
2023
|
---|---|
Authors: | Song, Yuping ; Tang, Xiaolong ; Wang, Hemin ; Ma, Zhiren |
Published in: |
Journal of forecasting. - New York, NY : Wiley Interscience, ISSN 1099-131X, ZDB-ID 2001645-1. - Vol. 42.2023, 1, p. 51-59
|
Subject: | deep learning model | GARCH-MIDAS model | macroeconomic variables | realized volatility forecasting | Volatilität | Volatility | Prognoseverfahren | Forecasting model | Theorie | Theory | ARCH-Modell | ARCH model | Aktienmarkt | Stock market | Lernprozess | Learning process | Zeitreihenanalyse | Time series analysis |
-
Ghani, Maria, (2022)
-
Forecasting the Asian stock market volatility : evidence from WTI and INE oil futures
Ghani, Maria, (2024)
-
Predicting the long-term stock market volatility : a GARCH-MIDAS model with variable selection
Fang, Tong, (2020)
- More ...
-
Song, Yuping, (2023)
-
Song, Yuping, (2024)
-
Volatility forecasting for crude oil based on text information and deep learning PSO-LSTM model
Jiao, Xingrui, (2022)
- More ...