Influencing Factors Analysis of Crude Oil Futures Price Volatility Based on Mixed-Frequency Data
This article takes into account the form of mixed data as well as the peak and thick tail characteristics contained in the data characteristics, expands the GARCH-MIDAS (Generalized Autoregressive Conditional Heteroskedasticity-Mixed Data Sampling) model, establishes a new GARCH-MIDAS model with the...
Main Authors: | Congxin Wu, Xinyu Wang, Shan Luo, Jing Shan, Feng Wang |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-11-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/10/23/8393 |
Similar Items
-
Identifying the Determinants of Crude Oil Market Volatility by the Multivariate GARCH-MIDAS Model
by: O-Chia Chuang, et al.
Published: (2022-04-01) -
Volatility predictability in crude oil futures: Evidence based on OVX, GARCH and stochastic volatility models
by: Zheng Zhang, et al.
Published: (2023-11-01) -
Do Crude Oil Price Levels Or Its Volatility Matter In Global Food Commodity Price Change?
by: Ibrahim A Onour
Published: (2021-10-01) -
Forecasting the volatility of EUA futures with economic policy uncertainty using the GARCH-MIDAS model
by: Jian Liu, et al.
Published: (2021-10-01) -
Forecasting Crude Oil Future Volatilities with a Threshold Zero-Drift GARCH Model
by: Tong Liu, et al.
Published: (2022-08-01)