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

Sepideh Dolatabadi, Paresh Kumar Narayan, Morten Nielsen () and Ke Xu

Journal of Futures Markets, 2018, vol. 38, issue 2, 219-242

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.

Date: 2018
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https://doi.org/10.1002/fut.21866

Related works:
Working Paper: Economic significance of commodity return forecasts from the fractionally cointegrated VAR model (2017) Downloads
Working Paper: Economic Significance Of Commodity Return Forecasts From The Fractionally Cointegrated Var Model (2017) Downloads
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