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Economic significance of commodity return forecasts from the fractionally cointegrated VAR model
journal contributionposted on 2017-01-01, 00:00 authored by S Dolatabadi, Paresh Narayan, MØ Nielsen, K Xu
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.