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Economic significance of commodity return forecasts from the fractionally cointegrated VAR model

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  • Sepideh Dolatabadi
  • Paresh Kumar Narayan
  • Morten Ørregaard Nielsen
  • Ke Xu

Abstract

We model and forecast commodity spot and futures prices using fractionally cointegrated vector autoregressive (FCVAR) models generalizing the well‐known (non‐fractional) CVAR model to accommodate fractional integration. In our empirical analysis to daily data on 17 commodity markets, the fractional model is statistically superior in terms of in‐sample fit and out‐of‐sample forecasting. We analyze economic significance of the forecasts through dynamic (mean‐variance) trading strategies, leading to statistically significant and economically meaningful profits in most markets. We generally find that the fractional model generates higher profits on average, especially in the futures markets.

Suggested Citation

  • Sepideh Dolatabadi & Paresh Kumar Narayan & Morten Ørregaard Nielsen & Ke Xu, 2018. "Economic significance of commodity return forecasts from the fractionally cointegrated VAR model," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(2), pages 219-242, February.
    • Handle: RePEc:wly:jfutmk:v:38:y:2018:i:2:p:219-242
    DOI: 10.1002/fut.21866
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    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
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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