This paper provides a method to forecast day-ahead electricity prices based on autoregressive integrated moving average (ARIMA) and generalized autoregressive conditional heteroskedastic (GARCH) models. In the competitive power market environment, electricity price forecasting is an essential...

Throughout the history man has considered gold as a precious metal and its forcast has always been important. Traditional methods of forcast, e.g.Regresion, ARIMA, Exponential Smoothing, Moving Average, and methods of this kind have been applied. Only recently Artificial Intelligence, Neural...

This paper investigates the impact of the crude oil price uncertainty on the growth of Industry and Mine sector in Iran over the period of 1367:1 to 1389:4. We applied Exponential Generalized Autoregressive Conditional Heteroskedasticity (EGARCH) Model to generate the crude oil price uncertainty...

In this research, the DCC model is estimated to calculate dynamic correlation series between crude oil price and growth of Industry and Mine sector during 1367:1-1392:4. Then, Macroeconomic variables which can explain the dynamic correlation are analyzed as variables of contagion. So, the...

This paper evaluates dynamic correlation between growth of Industry and Mine sector and crude oil price in Iran over the period of 1367:1 to 1389:4, with emphasis on the origin of oil price shocks. We apply Dynamic Conditional Correlation (DCC) model to estimate dynamic correlation. Our results...