Do high-frequency stock market data help forecast crude oil prices? Evidence from the MIDAS models

被引：99
作者：
Zhang, Yue-Jun [1 ]
Wang, Jin-Li [1 ,2 ]
机构：
[1] Hunan Univ, Sch Business, Changsha 410082, Hunan, Peoples R China
[2] Hunan Univ, Ctr Resource & Environm Management, Changsha 410082, Hunan, Peoples R China
来源：
ENERGY ECONOMICS | 2019年 / 78卷
基金：
中国国家自然科学基金;
关键词：
Stock market; Crude oil price forecast; MIDAS model; High frequency data; OUTPUT GROWTH; VOLATILITY SPILLOVERS; SUPPLY SHOCKS; RETURNS; RISK; REGRESSIONS; COMMODITY; MOVEMENT; DEMAND;
D O I：
10.1016/j.eneco.2018.11.015
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
Extensive studies have used stock market information to forecast crude oil prices, and stock market can more easily derive high-frequency data than crude oil market due to no revisions, which raises a question that whether high-frequency stock market data can improve the forecast performance of crude oil prices. Therefore, this paper employs the MIDAS model and the high-frequency data of four stock market indices to forecast WTI and Brent crude oil prices at lower frequency. The results indicate that the high-frequency stock market indices have certain advantage over the lower-frequency data in forecasting monthly crude oil prices, and the MIDAS model using high-frequency data proves superior to the ordinary model. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码：192 / 201
页数：10
相关论文
共 55 条
[41]   Forecasting crude oil prices by a semiparametric Markov switching model: OPEC, WTI, and Brent cases [J].
Nademi, Arash ;
Nademi, Younes .
ENERGY ECONOMICS, 2018, 74 :757-766
[42]   Forecasting US real GDP using oil prices: A time-varying parameter MIDAS model [J].
Pan, Zhiyuan ;
Wang, Qing ;
Wang, Yudong ;
Yang, Li .
ENERGY ECONOMICS, 2018, 72 :177-187
[43]   The relationships between petroleum and stock returns: An asymmetric dynamic equi-correlation approach [J].
Pan, Zhiyuan ;
Wang, Yudong ;
Liu, Li .
ENERGY ECONOMICS, 2016, 56 :453-463
[44]  
Stock J.H., 2008, The Methodology and Practice of Econometrics, P173
[45]   Combination forecasts of output growth in a seven-country data set [J].
Stock, JH ;
Watson, MW .
JOURNAL OF FORECASTING, 2004, 23 (06) :405-430
[46]  
Timmermann A, 2006, HBK ECON, V24, P135, DOI 10.1016/S1574-0706(05)01004-9
[47]   Crude oil and world stock markets: volatility spillovers, dynamic correlations, and hedging [J].
Wang, Yudong ;
Liu, Li .
EMPIRICAL ECONOMICS, 2016, 50 (04) :1481-1509
[48]   Forecasting the real prices of crude oil under economic and statistical constraints [J].
Wang, Yudong ;
Liu, Li ;
Diao, Xundi ;
Wu, Chongfeng .
ENERGY ECONOMICS, 2015, 51 :599-608
[49]   Oil price shocks and stock market activities: Evidence from oil-importing and oil-exporting countries [J].
Wang, Yudong ;
Wu, Chongfeng ;
Yang, Li .
JOURNAL OF COMPARATIVE ECONOMICS, 2013, 41 (04) :1220-1239
[50]   GAUSSIAN LIKELIHOOD OF CONTINUOUS-TIME ARMAX MODELS WHEN DATA ARE STOCKS AND FLOWS AT DIFFERENT FREQUENCIES [J].
ZADROZNY, P .
ECONOMETRIC THEORY, 1988, 4 (01) :108-124
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