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.
Keywords
Oils, Indexes, Artificial neural networks, Forecasting, Input variables, Training
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
Recommended Citation
Khan, S., Hasanabadi, H. S., & Mayorga, R. (2017). Technical Papers Parallel Session-IV: Determining the relationship between speculative activity and crude oil price volatility, using artificial neural networks. International Conference on Information and Communication Technologies. Retrieved from https://ir.iba.edu.pk/icict/2017/2017/24
COinS
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.
