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

Werner Kristjanpoller, Marcel C. Minutolo

Research output: Contribution to journalArticle

55 Citations (Scopus)

Abstract

© 2016 This paper builds on previous research and seeks to determine whether improvements can be achieved in the forecasting of oil price volatility by using a hybrid model and incorporating financial variables. The main conclusion is that the hybrid model increases the volatility forecasting precision by 30% over previous models as measured by a heteroscedasticity-adjusted mean squared error (HMSE) model. Key financial variables included in the model that improved the prediction are the Euro/Dollar and Yen/Dollar exchange rates, and the DJIA and FTSE stock market indexes.
Original languageEnglish
Pages (from-to)233-241
Number of pages9
JournalExpert Systems with Applications
DOIs
Publication statusPublished - 15 Dec 2016

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