CAViaR-based Forecast for Oil Price Risk
Publication Type
Journal Article
Publication Date
7-2009
Abstract
As a benchmark for measuring market risk, value-at-risk (VaR) reduces the risk associated with any kind of asset to just a number (amount in terms of a currency), which can be well understood by regulators, board members, and other interested parties. This paper employs a new VaR approach due to Engle and Manganelli [Engle, R.F., Manganelli, S., 2004. CAViaR: Conditional Autoregressive Value at Risk by Regression Quantiles. Journal of Business and Economic Statistics 22, 367–381] to forecasting oil price risk. In doing so, we provide two original contributions by introducing a new exponentially weighted moving average CAViaR model and developing a mixed data regression model for multi-period VaR prediction.
Keywords
VaR; CAViaR; Oil price risk; Mixed data regression
Discipline
Agribusiness | Finance and Financial Management
Research Areas
Finance
Publication
Energy Economics
Volume
31
Issue
4
First Page
511
Last Page
518
ISSN
0140-9883
Identifier
10.1016/j.eneco.2008.12.006
Publisher
Elsevier
Citation
Dashan HUANG; YU, Baimin; FABOZZI, Frank; and FUKUSHIMA, Masao.
CAViaR-based Forecast for Oil Price Risk. (2009). Energy Economics. 31, (4), 511-518.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/4780
Additional URL
https://doi.org/10.1016/j.eneco.2008.12.006