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Forecasting Volatility and Co-volatility of Crude Oil and Gold Futures: Effects of Leverage, Jumps, Spillovers, and Geopolitical Risks

Author

Listed:
  • Manabu Asai

    () (Faculty of Economics, Soka University, Japan)

  • Rangan Gupta

    () (Department of Economics, University of Pretoria, Pretoria, South Africa)

  • Michael McAleer

    (Department of Finance, Asia University, Taiwan; Discipline of Business Analytics, University of Sydney Business School, Australia; Econometric Institute, Erasmus School of Economics, Erasmus University Rotterdam, The Netherlands; Department of Economic Analysis and ICAE Complutense University of Madrid, Spain and Institute of Advanced Sciences, Yokohama National University, Japan)

Abstract

For purposes of forecasting the covariance matrix for the returns of crude oil and gold futures, this paper examines the effects of leverage, jumps, spillovers, and geopolitical risks, using their respective realized covariance matrices. In order to guarantee the positive definiteness of the forecasts, we consider the full BEKK structure on the conditional Wishart model. By the specification, we can divide flexibly the direct and spillover effects of volatility feedback, negative returns, and jumps. The empirical analysis indicates the benefits in accommodating the spillover effects of negative returns and the geopolitical risks indicator for modelling and forecasting the future covariance matrix.

Suggested Citation

  • Manabu Asai & Rangan Gupta & Michael McAleer, 2019. "Forecasting Volatility and Co-volatility of Crude Oil and Gold Futures: Effects of Leverage, Jumps, Spillovers, and Geopolitical Risks," Working Papers 201951, University of Pretoria, Department of Economics.
  • Handle: RePEc:pre:wpaper:201951
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    References listed on IDEAS

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    More about this item

    Keywords

    Commodity Markets; Co-volatility; Forecasting; Geopolitical Risks; Jumps; Leverage Effects; Spillover Effects; Realized Covariance;

    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
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market

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