Improving the Forecast Accuracy of Oil-Stock Nexus in GCC Countries

摘要

This paper renders new insights into the predictability of GCC stock returns using crude oil prices using the approach of [1] [2] that accounts for salient features of the predictor. The results show superior performance of the oil-based stock model over time-series models (namely, AR, MA, ARMA, and ARFIMA) for both in-sample and out-of-sample forecasts. The results are robust to different oil price series (Brent and WTI prices) and forecast horizons (30 and 60 days).