Energy Economics
Mojtaba Pourghorban; Siab Mamipour
Abstract
The restructuring of Iranian electricity industry allowed electricity price to be determined through market forces in 2005. The main purpose of this paper is to present a method for modeling and forecasting the electricity prices based on complex features such as instability, nonlinear conditions, and ...
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The restructuring of Iranian electricity industry allowed electricity price to be determined through market forces in 2005. The main purpose of this paper is to present a method for modeling and forecasting the electricity prices based on complex features such as instability, nonlinear conditions, and high fluctuations in Iran during the spring 2013 and winter 2018. For this purpose, time-series data of the daily average electricity price was decomposed into one approximation series (low frequency) and four details series (high frequency) utilizing the wavelet transform technique. The approximation and details series are estimated and predicted by ARIMA and GARCH models, respectively. Then, the electricity price is predicted by reconstructing and composing the forecasted values of different frequencies as a proposed method (Wavelet-ARMA-GARCH). The results demonstrated that the proposed method has higher predictive power and can forecast volatility of electricity prices more accurately by taking into consideration different domains of the time-frequency; although, more errors are produced if the wavelet transform process is not used. The mean absolute percentage error values of the proposed method during spring 2017 to winter 2018 are significantly less than that of the alternative method, and the proposed method can better and more accurately capture the complex features of electricity prices.
Saeed Samadi; Amin Haghnejad
Abstract
This paper investigates the asymmetry in volatility of returns for the Iranian stock market using the daily closing values of the Tehran exchange price index (TEPIX) covering the period from March 25, 2001 to July 25, 2012, with a total of 2743 observations. To this end, two sets of tests have been employed: ...
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This paper investigates the asymmetry in volatility of returns for the Iranian stock market using the daily closing values of the Tehran exchange price index (TEPIX) covering the period from March 25, 2001 to July 25, 2012, with a total of 2743 observations. To this end, two sets of tests have been employed: the first set is based on the residuals derived from a symmetric GARCH (1,1) model. The second set is based on the asymmetric GARCH models, including EGARCH (1,1), GJR-GARCH(1,1), and APARCH(1,1) models. To capture the stylized fact that the returns series are fat-tailed distributed, in addition to classic Gaussian assumption, the innovations are also assumed to have t-student distribution and GED (Generalized Error Distribution). The results indicate that there is no evidence of the leverage effects in the Iranian stock market, meaning that negative and positive shocks of the same magnitude have the same impacts on the future volatility level. This result is in contrast with the results of most empirical studies, where an asymmetry in volatility of stock returns has been found. This seems to be the result of the governmental or quasi-governmental nature of many companies listed on the Tehran Stock Exchange.
