Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6855470 | Expert Systems with Applications | 2016 | 30 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Werner Kristjanpoller, Marcel C. Minutolo,