Forecasting volatility of oil price using an artificial neural network-GARCH model

作者：

Highlights：

• A hybrid model is analyzed to predict oil price return volatility.

• The hybrid model used is an ANN-GARCH model.

• The ANN improves forecasting accuracy over the GARCH and ARFIMA model prediction.

• The precision of the price return volatility forecasting increases by 30%.

• The main financial variables to improve the forecast were determined.

摘要

•A hybrid model is analyzed to predict oil price return volatility.•The hybrid model used is an ANN-GARCH model.•The ANN improves forecasting accuracy over the GARCH and ARFIMA model prediction.•The precision of the price return volatility forecasting increases by 30%.•The main financial variables to improve the forecast were determined.

论文关键词：Oil price volatility,Artificial neural network,GARCH models

论文评审过程：Received 11 January 2016, Revised 10 August 2016, Accepted 11 August 2016, Available online 17 August 2016, Version of Record 24 August 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.08.045