1 2228-6454 Kharazmi University 667 انرژی، منابع و محیط زیست Comparing the performance of GARCH model and gravitational search algorithm (GSA) in modeling and forecasting of spot oil price of Iran (adaptive expectations approach) memarzadeh abbass b emami meibodi ali c amadeh hamid d ghasemi nejad amin e b allame tabatabie university c allame tabatabie university d allame tabatabie university e shahid bahonar kerman 1 12 2013 4 14 1 23 10 02 2013 06 10 2013 Abstract Forecasting of crude oil price plays a crucial role in optimization of production, marketing and market strategies. Furthermore, it plays a significant role in government’s policies, because the government sets and implements its policies not only according to the current situation but also according to short run and long run predictions of important economic variables like oil price. The main purpose of this study is modeling and forecasting spot oil price of Iran by using GARCH model and A Gravitational Search Algorithm. Performed forecasts of this study are based in static and out-of-sample forecasting and each subseries data is divided in to two parts: data for estimation and data for forecasting. The forecast horizon is next leading period and its length is one month. In this study the selected models for forecasting spot oil of Iran are GARCH(2,1) and a Cobb Douglas function which is functional of prices of 5 days ago. Finally, the performances of these models are compared. For comparison of these models MSE, RMSE, MAE, and MAPE criteria are used and the results indicate that except in MAPE criterion, the mentioned criteria are smaller for GARCH model in comparison to GSA algorithm.
565 انرژی، منابع و محیط زیست Assessing the price gap model for Brent’s crude oil and gasoline implementing econometrics methods, neural networks and wavelet transformation Najar Firouz Jayi mohammad Oryani Bahare g Zolfaqari Mahdi g Institute for trade studies and researchCommerce department 1 12 2013 4 14 25 58 19 10 2012 16 11 2013 This report investigates the dominant factors influencing the price gap and the symmetry principle’s evaluation between the crude oil’s price and gasoline. In this regard, the Brent’s crude oil price, gasoline price in six European countries and the fluctuations of the euro vs. US dollar’s exchange rate over the period of 1/1/1999 to 8/25/2011 in weekly intervals are studied. For this purpose, linear models and nonlinear models, such as artificial neural network and wavelet transformation, are implemented. The results indicate insignificant impact of the mentioned parameters in short period price gap both for linear and nonlinear simulations, but nonlinear modeling explicates 92% of long period fluctuations in price gap. According to linear/nonlinear models the symmetry principle is accepted for short period fluctuations in crude oil’s price, but not for long periods. 687 انرژی، منابع و محیط زیست The Behavior of Iranian Electricity Market in Supply Function Equilibrium Framework 1 12 2013 4 14 59 83 09 03 2013 27 10 2013 The Iranian electricity industry has been restructured following the global experiences. The main objective of restructuring is transition from natural monopoly towards competition in order to improve efficiency. Currently, the Iranian electricity market is performing as imperfect competition and Pay-as-Bid (PAB) auctions are the major trade mechanism in this market. This paper proves that Supply Function Equilibrium (SFE) is an appropriate approach to analyze behavior of the Iranian electricity market. Isfahan electricity market has been considered as a case study in which SFE is applied (regarding marginal cost estimation as well as demand uncertainty). The derived SFE indicates that there is major difference between SFE and Nash equilibrium. 521 پولی و مالی Modeling nonlinear effects of the changes in real exchange rate and crude oil prices on Tehran stock exchange (The Markov Switching approach) 1 12 2013 4 14 85 109 01 08 2012 16 01 2013 ABSTRACT Considering the major impact which changes in the real exchange rate and crude oil prices have on various sectors of Iran's economy and the importance of the financial markets role in economic growth and development, this paper aimed to investigate the effects of the changes in real exchange rate and crude oil prices on Tehran stock exchange using the Markov-Switching's nonlinear models. To this end, daily data which belonged to the following periods were used: 20:03: 2005 - 13:10:2010 The result of the estimations obtained through the Markov Switching Models indicated that MSIAH model with two regimes out of the various MS model are the most suitable ones. The result of the research showed that the changes in the exogenous variable of real exchange rate and the crude oil price have lagging positive effect on the Stock Exchange Index. Moreover, the effects of these changes with two lagging time intervals are significant and negative. The practical implications of these findings could be beneficial to the investors and policy makers who need to be aware of the exact nature of the effects which changes in the exchange rate and crude oil prices have on the stock exchange index. 577 انرژی، منابع و محیط زیست Forecasting natural gas spot price with Nonparametric Nonlinear Model Salehnia Narges p Falahi Mohamad Ali Seifi Ahmad Mahdavi Adeli Mohammad Hossein p Ferdowsi University of Mashhad (FUM) Ferdowsi University of Mashhad (FUM) Ferdowsi University of Mashhad (FUM) Ferdowsi University of Mashhad (FUM) 1 12 2013 4 14 111 150 02 11 2012 02 06 2013 Developing models for accurate natural gas spot price forecasting is critical because these forecasts are useful in determining a range of regulatory decisions covering both supply and demand of natural gas or for market participants. A price forecasting modeler needs to use trial and error to build mathematical models (such as ANN) for different input combinations. This is very time consuming since the modeler needs to calibrate and test different model structures with all the likely input combinations. In addition, there is no guidance about how many data points should be used in the calibration and what accuracy the best model is able to achieve. In this study, the Gamma Test has been used for the first time as a mathematically nonparametric nonlinear smooth modeling tool to choose the best input combination before calibrating and testing models. Then, several nonlinear models have been developed efficiently with the aid of the Gamma test, including regression models Local Linear Regression (LLR), Dynamic Local Linear Regression (DLLR) and Artificial Neural Networks (ANN) models. We used daily, weekly and monthly spot prices in Henry Hub from Jan 7, 1997 to Mar 20, 2012 for modeling and forecasting. Comparing the results of regression models show that DLLR model yields higher correlation coefficient and lower MSError than LLR and will make steadily better predictions. The calibrated ANN models specify the shorter the period of forecasting, the more accurate results will be. Therefore, the forecasting model of daily spot prices with ANN can interpret a fine view. Moreover, the ANN models have superior performance compared with LLR and DLLR. Although ANN models present a close up view and a high accuracy of natural gas spot price trend forecasting in different timescales, its ability in forecasting price shocks of the market is not notable. 725 انرژی، منابع و محیط زیست Designing a Dynamic Model for Iran Gas Industry: A System Dynamics Approach samadi ali hosein eydizadeh shahram shiraz university shiraz university 1 12 2013 4 14 151 181 06 05 2013 23 09 2013 This study aims to evaluate the status of Iranian gas industry and to formulate appropriate policies in order to attain the objectives of Iran’s Vision 2025. A dynamic model including exploration, production, consumption and demand sub-systems is designed based on the system dynamics approach and is simulated for the period 2010-2025. In this model, factors affecting natural gas exploration, demand and consumption as well as production, export and import of all other fuels in energy supply are identified and their dynamic interactions are investigated. The results of solving the basic model indicated that except for a 75 % share of gas consumption, none of Vision’s objectives would be attained, if current policies were followed. Accordingly, new policies are formulated and included in the model in the form of some scenarios. The results of simulating such scenarios suggest that other than coordinating the subdivisions of gas industry, production and exploration rates should be increased and significant technological exploration and production advances should be made in order to attain the objectives considered in the gas industry. Furthermore, clean energies such as water, wind and solar resources should be utilized increasingly in order to supply a part of domestic consumption. The results of model validation tests indicate the validity of the model as acceptable. 607 پولی و مالی Design and application of Error Correction Filters to Calculation the Value of Shares of Electricity Utilities, the Case of Tehran Regional Electricity Company Heidary kiumars sheikhbahaie azita ministry of power ministry of power 1 12 2013 4 14 183 201 03 12 2012 08 10 2013 The shares of state-owned or public companies are supplied in privatization plan. If the financial market be clear and efficient, it is expected that discovered price of supplied shares be efficient too. However, there is no guarantee for the fulfillment of this condition. Specially, implementation of those policies that, for example, a shock to exchange rate or the price of inputs (such as fuel), can affect market efficiency to discover efficient price of shares. In this study, the factors that cause the deviation of the actual share price have been identified, at first. After that a computable system has been designed by implementation error corrector filters. The input of this system is biased variable and corrected variable is the output. In this study, comparing previous studies, is generalized. So computable designed model can evaluates a wide range of factors. This system has been used to calculate the share of Tehran Regional Electricity Company. The outcomes show that the value of its shares is change from a negative amount (based on bias variables) to 2445 billion Rials (after passing based variable from correction filters). This difference, in addition of information asymmetry, maybe causes, in special in energy and electricity sectors, some opportunities to rent.