Predicting the volatility of crude oil futures: The roles of leverage effects and structural changes

被引:6
作者
Gong, Xu [1 ]
Lin, Boqiang [1 ]
机构
[1] Xiamen Univ, China Inst Studies Energy Policy, Collaborat Innovat Ctr Energy Econ & Energy Polic, Sch Management, Xiamen 361005, Peoples R China
基金
中国国家自然科学基金;
关键词
HAR models; leverage effects; realized volatility; structural changes; volatility forecasting; ECONOMIC-POLICY UNCERTAINTY; REALIZED VOLATILITY; LONG-MEMORY; STOCHASTIC VOLATILITY; PRICE VOLATILITY; FORECASTING VOLATILITY; DYNAMIC CORRELATIONS; BREAKS; GARCH; MODEL;
D O I
10.1002/ijfe.2171
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
This paper investigates whether leverage effects and structural changes have positive effects on the volatility prediction of crude oil futures. On the basis of existing HAR models, this paper proposes three classes of new HAR models by considering leverage effects, structural changes, or both. The in-sample and out-of-sample results show that leverage effects and structural changes contain significant information for predicting oil volatility. In most cases, structural changes have more in-sample and out-of-sample incremental information than leverage effect, whereas leverage effects have more out-of-sample information for predicting 1-day volatility. In addition, HAR models with leverage effects and structural changes have better in-sample and out-of-sample performances than the corresponding other three classes of HAR models. The above results mean that leverage effects and structural changes should be considered while modelling and forecasting oil volatility.
引用
收藏
页码:610 / 640
页数:31
相关论文
共 69 条
[1]   Analytical evaluation of volatility forecasts [J].
Andersen, TG ;
Bollerslev, T ;
Meddahi, N .
INTERNATIONAL ECONOMIC REVIEW, 2004, 45 (04) :1079-1110
[2]   Answering the skeptics: Yes, standard volatility models do provide accurate forecasts [J].
Andersen, TG ;
Bollerslev, T .
INTERNATIONAL ECONOMIC REVIEW, 1998, 39 (04) :885-905
[3]   Modeling and forecasting realized volatility [J].
Andersen, TG ;
Bollerslev, T ;
Diebold, FX ;
Labys, P .
ECONOMETRICA, 2003, 71 (02) :579-625
[4]   Roughing it up: Including jump components in the measurement, modeling, and forecasting of return volatility [J].
Andersen, Torben G. ;
Bollerslev, Tim ;
Diebold, Francis X. .
REVIEW OF ECONOMICS AND STATISTICS, 2007, 89 (04) :701-720
[5]   A reduced form framework for modeling volatility of speculative prices based on realized variation measures [J].
Andersen, Torben G. ;
Bollerslev, Tim ;
Huang, Xin .
JOURNAL OF ECONOMETRICS, 2011, 160 (01) :176-189
[6]   Forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models [J].
Arouri, Mohamed El Hedi ;
Lahiani, Amine ;
Levy, Aldo ;
Duc Khuong Nguyen .
ENERGY ECONOMICS, 2012, 34 (01) :283-293
[7]   Asymmetry and Long Memory in Volatility Modeling [J].
Asai, Manabu ;
McAleer, Michael ;
Medeiros, Marcelo C. .
JOURNAL OF FINANCIAL ECONOMETRICS, 2012, 10 (03) :495-512
[8]  
Barndorff-Nielsen O.E., 2010, VOLATILITY TIME SERI, DOI DOI 10.1093/ACPROF:OSO/9780199549498.003.0007
[9]  
Barndorff-Nielsen OleE., 2006, Journal of financial Econometrics, V4, p1. 1, DOI DOI 10.1093/JJFINEC/NBI022
[10]   Jumps and stochastic volatility in crude oil futures prices using conditional moments of integrated volatility [J].
Baum, Christopher F. ;
Zerilli, Paola. .
ENERGY ECONOMICS, 2016, 53 :175-181