Time series and neural networks comparison on gold, oil and the euro

Gold, oil, and the euro are three very important economic markets that have been studied individually by numerous authors. But certain basic questions about their inter-relationships since the year 2000 remain unaddressed. Gold has been an important commodity for several centuries. Oil´s importance grew during the 20th century, and the euro has become important during the 21st. Standard economic analysis allows us to hypothesize about a specific relationship and test for it, and a neural network gives us the ability to identify important variables in a forecast without forming a prior hypothesis about the relationship of each variable to the target. This paper analyzes the inter-relationships among the price behavior of gold, oil and the euro using a standard time series methodology then employs neural networks to build a forecast for each of the three variables. We then compare the results of the neural network to those implied by the time series tests. The statistical evidence of time series analysis demonstrates that both short-term and long-term relationships exist between the three variables. Both the time series and neural network results indicate that the series move together though they identify slightly different relationships. The time series results imply that oil adjusts to gold, the euro and oil have equal affects on each other, and the weakest relationship is between gold and the euro. The neural network indicates that oil impacts gold more than gold impacts oil, oil´s affect on the euro is greater than the euro´s effect on oil and last, gold´s impact on the euro is greater and faster than the euro´s impact on gold.