7933

7381

كارشناسي ارشد

صنايع - سيستم

اصفهان: دانشگاه صنعتي اصفهان، دانشكده صنايع و سيستم ها

1391

يازده،83ص.: مصور،جدول،نمودار

ص.ع.به فارسي و انگليسي

اكبر توكلي

17/6/92

علي زينل همداني، رضا حجازي

مهندسي صنايع و سيستم ها

ID7381

به فارسي و انگليسي: قابل رويت در نسخه ديجيتالي

84 Modeling and forecasting Iran s crude oil price volatility using GARCH models Yavar Nezamivand Chegini y chegini@gmail com 23th January 2013 Department of Industrial Engineering Isfahan University of Technology Isfahan 84156 83111 Iran Degree M Sc Language Farsi Supervisor Akbar Tavakoli atavakoli@cc iut ac ir Abstract Today the oil energy as one of nonrenewable energy sources has allocated an important place among the world s energy resources The price structure of this goods and modeling has always pay attention economic research and attempts to evaluate and predict the volatility has been done Iran is one of the largest oil exporters in the world and according to experts the country s economy is dependent on oil revenues therefore modeling and prediction of iran s crude oil price volatility is very important In many time series especially financial time series features clearly observed heteroskedasticity In this regard various classes of GARCH models as one of the best techniques for modeling volatility in financial markets are considered In this study by using generalized autoregressive conditional heteroskedasticity GARCH models the modeling and prediction of heavy crude oil price has been paid The data used in this study is the data of heavy crude oil per day five days a week during the first third of january 2002 to november 2011 To study the behavior of crude oil price and a comprehensive understanding of the models GARCH IGARCH GARCH M EGARCH GJRGARCH APARCH and FIGARCH is used for modeling The results indicate that the effect of oil price shocks on the volatility of crude oil prices is asymmetric and has a high degree of stability and negative shocks than positive shocks have a greater effect on the conditional variance of oil prices So the series of heavy crude oil price returns has the leverage effect Crude oil price return series has a long memory and volatility in the form of conditional variance models are better modeling than the form of the conditional standard deviation The results of survey the relationship between the series returns and conditional variance series show that the changes of conditional variance series has no significant effect on the return series but the reverse relationship is true In this study also examines the characteristics of the distribution of return series in performance evaluation GARCH 1 1 model and four standard normal distribution T student distribution generalized error distribution GED and skew T student distribution are also being studied The results of performance evaluation models using loss functions criteria and DM test indicate that there are in terms of excessive kortusis and skewness in the return series using skew T student distribution as the distribution of the error values has better forecast accuracy compared to other distributions Keywords Oil shock return series GARCH models DM testPDF created with pdfFactory trial version www pdffactory com

اكبر توكلي

علي زينل همداني، رضا حجازي