Forecasting oil prices: New approaches

被引：17

作者：

de Medeiros, Rennan Kertlly ^{[1
]}

Besarria, Cassio da Nobrega ^{[1
]}

de Jesus, Diego Pitta ^{[1
]}

de Albuquerquemello, Vinicius Phillipe ^{[2
]}

机构：

[1] Grad Program Appl Econ, Recife, PE, Brazil

[2] UFPE PIMES, Grad Program Econ, Recife, PE, Brazil

来源：

ENERGY | 2022年 / 238卷

关键词：

Forecasting oil prices; Time series; Econometrics; MIDAS model; Sentiment index; CRUDE-OIL; TIME-SERIES; MIDAS REGRESSIONS; OUTPUT GROWTH; UNIT-ROOT; MACROECONOMICS; MOVEMENTS; SHOCKS;

D O I：

10.1016/j.energy.2021.121968

中图分类号：

O414.1 [热力学];

学科分类号：

摘要：

This paper proposes alternative methodologies for oil price forecasting using mixed-frequency data and a textual sentiment indicator. The latter variable was extracted from oil market reports issued by the Energy Information Administration. We used the root mean square error (RMSE) to evaluate the forecasting accuracy of the econometric models. Compared with other econometric models, the mixed data sampling (MIDAS) model with high-frequency financial indicators and the sentiment index as explanatory variables performs better for forecasting crude oil prices. (c) 2021 Elsevier Ltd. All rights reserved.

引用

页数：11

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