Modelling general dependence between commodity forward curves
AbstractThis study proposes a novel framework for the joint modelling of commodity forward curves. Its key contribution is twofold. First, dynamic correlation models are applied in this context as part of the modelling scheme. Second, we introduce a family of dynamic conditional correlation models based on hierarchical Archimedean copulae (HAC DCC), which are flexible, but parsimonious instruments that capture a wide range of dynamic dependencies. The conducted analysis allows us to obtain precise out-of-sample forecasts of the distribution of the returns of various commodity futures portfolios. The Value-at-Risk analysis shows that HAC DCC models outperform other introduced benchmark models on a consistent basis.
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Bibliographic InfoPaper provided by Sonderforschungsbereich 649, Humboldt University, Berlin, Germany in its series SFB 649 Discussion Papers with number SFB649DP2012-060.
Length: 37 pages
Date of creation: Oct 2012
Date of revision:
commodity forward curves; multivariate GARCH; hierarchical Archimedean copula; Value-at-Risk;
Find related papers by JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-10-20 (All new papers)
- NEP-ECM-2012-10-20 (Econometrics)
- NEP-FOR-2012-10-20 (Forecasting)
- NEP-RMG-2012-10-20 (Risk Management)
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