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:: Volume 0, Issue 1 (spring 2013) ::
2013, 0(1): 59-76 Back to browse issues page
Modeling Energy Price in Iran, Using Markov Switching Auto Regressive and Neural Network Models
Minoo Nazifi *, Shahram Fatahi, Dr Saeed Samadi
Abstract:   (18317 Views)
Reforms of pricing the energy transformers are one of the most important debates for FDI experts, in Iran. this pricing is directly in contact with some subjects such as the effect of long run subsidies on price diffusion in economy, sources waist, decreasing the resistance of Energy part in Iran and finally the effect of acceleration in energy consume growth rate .so it appear necessary to doing more study about energy and pricing and also energy transformers. In this study we model the volatility of Electric energy price according to energy transformers, financial markets and also energy demand. fir this purpose we use two methods for modeling first is Markov switching regression and the second is artificial neural network. Both are nonlinear methods. The switching model has ability to model the shocks on response variable and it can make two regimes with different volatility. But neural network has the ability to estimate and forecasting. The period of this study is1367-1387.
Keywords: ANN, Switching Regression, Markov Chain, Volatility of Energy Price, Financial Markets
Full-Text [PDF 533 kb]   (1645 Downloads)    
Type of Study: Research | Subject: General
Received: 2014/03/18 | Accepted: 2014/03/18 | Published: 2014/03/18
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Nazifi M, Fatahi S, Samadi D S. Modeling Energy Price in Iran, Using Markov Switching Auto Regressive and Neural Network Models. Quarterly Journal of Energy Policy and Planning Research. 2013; 0 (1) :59-76
URL: http://epprjournal.ir/article-1-30-en.html

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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Volume 0, Issue 1 (spring 2013) Back to browse issues page
مجله پژوهش های برنامه ریزی و سیاستگذاری انرژی Journal of Energy Planning And Policy Research
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