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Modeling and forecasting extreme commodity prices: A Markov-Switching based extreme value model

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  • Herrera, Rodrigo
  • Rodriguez, Alejandro
  • Pino, Gabriel

Abstract

We propose a Markov-Switching Multifractal Peaks-Over-Threshold (MSM-POT) model to capture the dynamic behavior of the random occurrences of extreme events exceeding a high threshold in time series of returns. This approach allows introducing changes of regimes in the conditional mean function of the inter-exceedance times (i.e., the time between two consecutive extreme events) in order to admit the presence of short- and long-term memory patterns. Further, through its multifractal structure, the MSM-POT approach is able to capture the typical stylized facts of extreme events observed in financial time series, such as temporal clustering of the size of exceedances and temporal behavior of tail thickness.

Suggested Citation

  • Herrera, Rodrigo & Rodriguez, Alejandro & Pino, Gabriel, 2017. "Modeling and forecasting extreme commodity prices: A Markov-Switching based extreme value model," Energy Economics, Elsevier, vol. 63(C), pages 129-143.
  • Handle: RePEc:eee:eneeco:v:63:y:2017:i:c:p:129-143
    DOI: 10.1016/j.eneco.2017.01.012
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    References listed on IDEAS

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    Keywords

    Commodity markets; Extreme value theory; Value at risk; Markov-Switching Multifractal; Self-exciting point process;

    JEL classification:

    • C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Bayesian Analysis: General
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

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