Forecasting crude oil price intervals and return volatility via autoregressive conditional interval models
文献类型：期刊论文
| 作者 | He, Yanan5; Han, Ai2,3,4; Hong, Yongmiao1,3,4; Sun, Yuying1,3,4; Wang, Shouyang1,3,4 |
| 刊名 | ECONOMETRIC REVIEWS
 |
| 出版日期 | 2021-07-03 |
| 卷号 | 40期号:6页码:584-606 |
| ISSN号 | 0747-4938 |
| 关键词 | ACI model interval-valued crude oil prices range trading strategy volatility forecast |
| DOI | 10.1080/07474938.2021.1889202 |
| 英文摘要 | Crude oil prices are of vital importance for market participants and governments to make energy policies and decisions. In this paper, we apply a newly proposed autoregressive conditional interval (ACI) model to forecast crude oil prices. Compared with the existing point-based forecasting models, the interval-based ACI model can capture the dynamics of oil prices in both level and range of variation in a unified framework. Rich information contained in interval-valued observations can be simultaneously utilized, thus enhancing parameter estimation efficiency and model forecasting accuracy. In forecasting the monthly West Texas Intermediate (WTI) crude oil prices, we document that the ACI models outperform the popular point-based time series models. In particular, ACI models deliver better forecasts than univariate ARMA models and the vector error correction model (VECM). The gain of ACI models is found in out-of-sample monthly price interval forecasts as well as forecasts for point-valued highs, lows, and ranges. Compared with GARCH and conditional autoregressive range (CARR) models, ACI models are also superior in volatility (conditional variance) forecasts of oil prices. A trading strategy that makes use of the monthly high and low forecasts is further developed. This trading strategy generally yields more profitable trading returns under the ACI models than the point-based VECM. |
| 资助项目 | China NNSF[71703156] ; China NNSF[72073126] ; China NNSF[72091212] ; China NNSF[71403231] ; China NNSF[71671183] ; China NNSF[71988101] |
| WOS研究方向 | Business & Economics ; Mathematics ; Mathematical Methods In Social Sciences |
| 语种 | 英语 |
| 出版者 | TAYLOR & FRANCIS INC |
| WOS记录号 | WOS:000681583400003 |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/59029]  |
| 专题 | 中国科学院数学与系统科学研究院 |
| 通讯作者 | Hong, Yongmiao; Sun, Yuying |
| 作者单位 | 1.Univ Chinese Acad Sci, Sch Econ & Management, Beijing, Peoples R China 2.JD Com, Beijing, Peoples R China 3.Chinese Acad Sci, Ctr Forecasting Sci, Beijing, Peoples R China 4.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China 5.Xiamen Univ, Wang Yannan Inst Studies Econ, Xiamen, Peoples R China |
| 推荐引用方式 GB/T 7714 | He, Yanan,Han, Ai,Hong, Yongmiao,et al. Forecasting crude oil price intervals and return volatility via autoregressive conditional interval models[J]. ECONOMETRIC REVIEWS,2021,40(6):584-606. |
| APA | He, Yanan,Han, Ai,Hong, Yongmiao,Sun, Yuying,&Wang, Shouyang.(2021).Forecasting crude oil price intervals and return volatility via autoregressive conditional interval models.ECONOMETRIC REVIEWS,40(6),584-606. |
| MLA | He, Yanan,et al."Forecasting crude oil price intervals and return volatility via autoregressive conditional interval models".ECONOMETRIC REVIEWS 40.6(2021):584-606. |
入库方式： OAI收割
来源：数学与系统科学研究院
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。