Economic significance of commodity return forecasts from the fractionally cointegrated VAR model
Paresh Kumar Narayan,
Morten Nielsen () and
Journal of Futures Markets, 2018, vol. 38, issue 2, 219-242
We model and forecast commodity spot and futures prices using fractionally cointegrated vector autoregressive (FCVAR) models generalizing the wellâ€ known (nonâ€ 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 inâ€ sample fit and outâ€ ofâ€ sample forecasting. We analyze economic significance of the forecasts through dynamic (meanâ€ 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.
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Working Paper: Economic significance of commodity return forecasts from the fractionally cointegrated VAR model (2017)
Working Paper: Economic Significance Of Commodity Return Forecasts From The Fractionally Cointegrated Var Model (2017)
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