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Analyzing Oil Futures with a Dynamic Nelson-Siegel Model

Author

Listed:
  • Niels S. Hansen

    (Aarhus University and CREATES)

  • Asger Lunde

    (Aarhus University and CREATES)

Abstract

In this paper we are interested in the term structure of futures contracts on oil. The objective is to specify a relatively parsimonious model which explains data well and performs well in a real time out of sample forecasting. The dynamic Nelson-Siegel model is normally used to analyze and forecast interest rates of different maturities. The structure of oil futures resembles the structure of interest rates and this motivates the use of this model for our purposes. The data set is vast and the dynamic Nelson-Siegel model allows for a significant dimension reduction by introducing three factors. By performing a series of cross-section regressions we obtain time series for these factors and we focus on modeling their joint distribution. Using copula decomposition we can set up a model for each factor individually along with a model for their dependence structure. When a reasonable model for the factors has been specified it can be used to forecast prices of futures contracts with different maturities. The outcome of this exercise is a class of models which describes the observed futures contracts well and forecasts better than conventional benchmarks. We carry out a real time value at risk analysis and show that our class of models performs well.

Suggested Citation

  • Niels S. Hansen & Asger Lunde, 2013. "Analyzing Oil Futures with a Dynamic Nelson-Siegel Model," CREATES Research Papers 2013-36, Department of Economics and Business Economics, Aarhus University.
  • Handle: RePEc:aah:create:2013-36
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    Cited by:

    1. van Huellen, Sophie, 2020. "Too much of a good thing? Speculative effects on commodity futures curves," Journal of Financial Markets, Elsevier, vol. 47(C).
    2. Bredin, Don & O'Sullivan, Conall & Spencer, Simon, 2021. "Forecasting WTI crude oil futures returns: Does the term structure help?," Energy Economics, Elsevier, vol. 100(C).

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    More about this item

    Keywords

    Oil futures; Nelson-Siegel; Normal Inverse Gaussian; GARCH; Copula.;
    All these keywords.

    JEL classification:

    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods

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