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A Markov switching long memory model of crude oil price return volatility

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  • Di Sanzo, Silvestro

Abstract

I propose a time series model that simultaneously captures long memory and Markov switching dynamics to analyze and forecast oil price return volatility. I compare the fit and forecasting performance of the model to that of a range of linear and nonlinear GARCH models widely adopted in the literature. Complexity-penalized likelihood criteria show that the Markov switching long memory model improves the description of the data. The out-of-sample results at several time horizons show that the model produces superior forecasts over those obtained from the selected GARCH competitors. Results are obtained using Patton's robust loss functions and the Hansen's superior predictive ability test. I conclude that the proposed model provides a useful alternative to the usually employed GARCH models.

Suggested Citation

  • Di Sanzo, Silvestro, 2018. "A Markov switching long memory model of crude oil price return volatility," Energy Economics, Elsevier, vol. 74(C), pages 351-359.
  • Handle: RePEc:eee:eneeco:v:74:y:2018:i:c:p:351-359
    DOI: 10.1016/j.eneco.2018.06.015
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    3. Halkos, George & Tzirivis, Apostolos, 2018. "Effective energy commodities’ risk management: Econometric modeling of price volatility," MPRA Paper 90781, University Library of Munich, Germany.
    4. Abdollahi, Hooman, 2020. "A novel hybrid model for forecasting crude oil price based on time series decomposition," Applied Energy, Elsevier, vol. 267(C).
    5. Lin, Yu & Xiao, Yang & Li, Fuxing, 2020. "Forecasting crude oil price volatility via a HM-EGARCH model," Energy Economics, Elsevier, vol. 87(C).
    6. Long Hai Vo & Duc Hong Vo, 2019. "Application of Wavelet-Based Maximum Likelihood Estimator in Measuring Market Risk for Fossil Fuel," Sustainability, MDPI, Open Access Journal, vol. 11(10), pages 1-19, May.
    7. Xiao, Yang, 2020. "The risk spillovers from the Chinese stock market to major East Asian stock markets: A MSGARCH-EVT-copula approach," International Review of Economics & Finance, Elsevier, vol. 65(C), pages 173-186.
    8. Pablo Cansado-Bravo & Carlos Rodríguez-Monroy, 2018. "Persistence of Oil Prices in Gas Import Prices and the Resilience of the Oil-Indexation Mechanism. The Case of Spanish Gas Import Prices," Energies, MDPI, Open Access Journal, vol. 11(12), pages 1-17, December.

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    More about this item

    Keywords

    Crude oil volatility; Long memory; Markov switching; GARCH modelling; Volatility forecast;
    All these keywords.

    JEL classification:

    • Q47 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy Forecasting
    • 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

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