Modelling Return and Volatility of Oil Price using Dual Long Memory Models
This paper investigates the dynamic properties of both return and volatility of the oil price. The analysis is carried out using a set of double long memory specifications incorporating several features such as long range dependence, asymmetry in conditional variances and time varying correlations. The in-sample diagnostic tests as well as the out-of-sample forecasting results show the performance of the ARFIMA-FIAPARCH model.
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