Forecasting Oil Price by Hierarchical Shrinkage in Dynamic Parameter Models
Joint Authors
Liu, Yuntong
Wei, Yu
Liu, Yi
Li, Wenjuan
Source
Discrete Dynamics in Nature and Society
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-03
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
The aim of this paper is to forecast monthly crude oil price with a hierarchical shrinkage approach, which utilizes not only LASSO for predictor selection, but a hierarchical Bayesian method to determine whether constant coefficient (CC) or time-varying parameter (TVP) predictive regression should be employed in each out-of-sample forecasting step.
This newly developed method has the advantages of both model shrinkage and automatic switch between CC and TVP forecasting models; thus, this may produce more accurate predictions of crude oil prices.
The empirical results show that this hierarchical shrinkage model can outperform many commonly used forecasting benchmark methods, such as AR, unobserved components stochastic volatility (UCSV), and multivariate regression models in forecasting crude oil price on various forecasting horizons.
American Psychological Association (APA)
Liu, Yuntong& Wei, Yu& Liu, Yi& Li, Wenjuan. 2020. Forecasting Oil Price by Hierarchical Shrinkage in Dynamic Parameter Models. Discrete Dynamics in Nature and Society،Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1153315
Modern Language Association (MLA)
Liu, Yuntong…[et al.]. Forecasting Oil Price by Hierarchical Shrinkage in Dynamic Parameter Models. Discrete Dynamics in Nature and Society No. 2020 (2020), pp.1-12.
https://search.emarefa.net/detail/BIM-1153315
American Medical Association (AMA)
Liu, Yuntong& Wei, Yu& Liu, Yi& Li, Wenjuan. Forecasting Oil Price by Hierarchical Shrinkage in Dynamic Parameter Models. Discrete Dynamics in Nature and Society. 2020. Vol. 2020, no. 2020, pp.1-12.
https://search.emarefa.net/detail/BIM-1153315
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1153315