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Dynamic connectedness and portfolio strategies: Energy and metal markets

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  • Evrim Mandacı, Pınar
  • Cagli, Efe Çaglar
  • Taşkın, Dilvin

Abstract

In this paper, we investigate the volatility spillover effect among the global commodity futures (including both energy and metal futures; global stock markets (covering both Developed and Emerging Markets); the US bond market and the US Dollar index by employing the dynamic connectedness approach of (Diebold and Yilmaz, 2012, 2014) based on the time-varying parameter vector autoregressive (TVP-VAR) model and using daily data for the period from January 3, 1992 to December 27, 2019. Our results indicate a moderate connectedness among the volatilities changing over time and approaching its peak level during 2007/08 global financial crises. In addition, we determine the optimal hedge ratios and portfolio weights for the commodity investors and portfolio managers. Our results indicate that for the equity market volatility investors, the highest hedging effectiveness can be reached by taking short positions in energy futures (such as natural gas), on the other hand for both the US bond and US Dollar volatility investors it can be reached by taking short positions in metal futures (such as gold).

Suggested Citation

  • Evrim Mandacı, Pınar & Cagli, Efe Çaglar & Taşkın, Dilvin, 2020. "Dynamic connectedness and portfolio strategies: Energy and metal markets," Resources Policy, Elsevier, vol. 68(C).
    • Handle: RePEc:eee:jrpoli:v:68:y:2020:i:c:s0301420720301008
    DOI: 10.1016/j.resourpol.2020.101778
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    Keywords

    Connectedness; Volatility spillover; Hedging; Commodity markets; Market linkage;
    All these keywords.

    JEL classification:

    • Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics
    • Q02 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General - - - Commodity Market
    • C - Mathematical and Quantitative Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • 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
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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