This study aims to introduce an ideal model for forecasting crude oil price volatility. For this purpose, the ‘predictability’ hypothesis was tested using the variance ratio test, BDS<link href="#opec12030-note-0007"/> test and the chaos analysis. Structural analyses were also carried out to identify possible non-linear...

Substituting crude oil exports with value-added petrochemical products is one of the main strategies for policy makers in oil-driven economies to isolating the real sectors of economy from oil price volatility. This policy inclination has led to a body of literature in energy economics in recent...

Substituting crude oil exports with value-added petrochemical products is one of the main strategies for policy makers in oil-driven economies to isolating the real sectors of economy from oil price volatility. This policy inclination has led to a body of literature in energy economics in recent...

This study aims to introduce an ideal model for forecasting crude oil price volatility. For this purpose, the ‘predictability’ hypothesis was tested using the variance ratio test, BDS test and the chaos analysis. Structural analyses were also carried out to identify possible nonlinear...

The main purpose of the present study was to investigate the capabilities of two generations of models such as those based on dynamic neural network (e.g., Nonlinear Neural network Auto Regressive or NNAR model) and a regressive (Auto Regressive Fractionally Integrated Moving Average model which...

This study is an attempt to review the theory and applications of autoregressive fractionally integrated moving average (ARFIMA) and fractionally integrated generalized autoregressive conditional heteroskedasticity (FIGARCH) models, mainly for the purpose of the description of the observed...

The design of models for time series forecasting has found a solid foundation on statistics and mathematics. On this basis, in recent years, using intelligence-based techniques for forecasting has proved to be extremely successful and also is an appropriate choice as approximators to model and...

The design of models for time series forecasting has found a solid foundation on statistics and mathematics. On this basis, in recent years, using intelligence-based techniques for forecasting has proved to be extremely successful and also is an appropriate choice as approximators to model and...

Examining energy as a strategic commodity in the world and analysis of the effect of changes in its price on key economic factors has been always considered as significant. The importance of this issue is twofold in Iran: first, policies in this country, as one of the great possessors of energy...

This study attempts to introduce an appropri¬¬ate model for modeling and forecasting Iran’s crude oil price volatility. Therefore, this hypothesis will be tested about whether long memory feature matters in forecasting the price of this commodity. For this purpose, using the Iran’s weekly...