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Modelling and forecasting the volatility of petroleum futures prices

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  • Seong-Min Yoon
  • Sang Hoon Kang

Abstract

We investigate volatility models and their forecasting abilities for three types of petroleum futures contracts traded on the New York Mercantile Exchange (West Texas Intermediate crude oil, heating oil #2, and unleaded gasoline) and suggest some stylized facts about the volatility of these futures markets, particularly in regard to volatility persistence (or long-memory properties). In this context, we examine the persistence of market returns and volatility simultaneously using the following ARFIMA-GARCH-class models: ARFIMA-GARCH, ARFIMA-IGARCH, and ARFIMA-FIGARCH. Although the ARFIMA-FIGARCH model better captures long-memory properties of returns and volatility, the out-of-sample analysis indicates no unique model for all three types of petroleum futures contracts, suggesting that investors should be careful when measuring and forecasting the volatility (risk) of petroleum futures markets.

Suggested Citation

  • Seong-Min Yoon & Sang Hoon Kang, 2012. "Modelling and forecasting the volatility of petroleum futures prices," EcoMod2012 3944, EcoMod.
  • Handle: RePEc:ekd:002672:3944
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    More about this item

    Keywords

    US; Finance; Energy and environmental policy;
    All these keywords.

    JEL classification:

    • 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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General

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