Title

Technical Papers Parallel Session-IV: Determining the relationship between speculative activity and crude oil price volatility, using artificial neural networks

Abstract/Description

The impact of speculative activity in commodity markets has been a matter of controversy for quite some time. It has become even more contagious as the financialization of commodities has attracted more interest to this matter, by both academics and practitioners. In this paper we adopt a different approach to study the relationship between speculative activity and volatility. We employ artificial neural networks (ANNs) to forecast crude oil returns volatility, using an information set of market variables for training. One of these variables is a measure of speculative activity. If the speculative activity did impact crude oil return volatility, we would expect that the information content of the speculative activity variable used in training the artificial neural networks, would improve the quality of forecast. However, the results show that the speculative activity variable did not improve the quality of the forecast. We therefore do not find evidence that speculative activity impacts crude oil price volatility.

Location

Theatre 1, Aman Tower

Session Theme

Technical Papers Parallel Session-IV: Artificial Intelligence

Session Type

Parallel Technical Session

Session Chair

Dr. Syeda Saleha Raza

Start Date

31-12-2017 2:40 PM

End Date

31-12-2017 3:00 PM

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Dec 31st, 2:40 PM Dec 31st, 3:00 PM

Technical Papers Parallel Session-IV: Determining the relationship between speculative activity and crude oil price volatility, using artificial neural networks

Theatre 1, Aman Tower

The impact of speculative activity in commodity markets has been a matter of controversy for quite some time. It has become even more contagious as the financialization of commodities has attracted more interest to this matter, by both academics and practitioners. In this paper we adopt a different approach to study the relationship between speculative activity and volatility. We employ artificial neural networks (ANNs) to forecast crude oil returns volatility, using an information set of market variables for training. One of these variables is a measure of speculative activity. If the speculative activity did impact crude oil return volatility, we would expect that the information content of the speculative activity variable used in training the artificial neural networks, would improve the quality of forecast. However, the results show that the speculative activity variable did not improve the quality of the forecast. We therefore do not find evidence that speculative activity impacts crude oil price volatility.