Modeling Energy Price in Iran, Using Markov Switching Auto Regressive and Neural Network Models

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.