bu ali sina university Journal of Applied Economics Studies in Iran 2322-2530 11 41 2022 05 22 The Pattern of Long-Term Volatility Transferring to the Industry Sector in the Tehran Stock Exchange Using the Mixed Data Model (GARCH-MIDAS Approach) The Pattern of Long-Term Volatility Transferring to the Industry Sector in the Tehran Stock Exchange Using the Mixed Data Model (GARCH-MIDAS Approach) 73 95 4160 10.22084/aes.2021.24255.3291 FA Eghlim Tamry PhD Student, Department of Economics, Faculty of Economics and Social Sciences, Shahid Chamran University of Ahvaz, Ahvaz, Iran. Amir Hossein Montazar-Hojat Associate Professor, Department of Economics, Faculty of Economics and Social Sciences, Shahid Chamran University of Ahvaz, Ahvaz, Iran. 0000-0002-2300-8190 َAbdolmajid Ahangari Associate Professor, Department of Economics, Faculty of Economics and Social Sciences, Shahid Chamran University of Ahvaz, Ahvaz, Iran. Journal Article 2021 05 14 In this research, it is attempted to identify the pattern of uncertainty transferring of variables affecting the long-term volatility of the industrial sector in the Tehran Stock Exchange. In this regard, the mixed data model (MIDAS) and data of different internal and external variables with daily, monthly, seasonal and annual frequencies in the period 2009-2010 have been used. In the selection part of variables, by estimating different models, the variables affecting the volatility of industry sector in the long run were selected and finally the results of the selected model were presented. from various domestic and foreign variables, uncertainties of inflation, exchange rate, gold price and oil prices have significant effect in long run volatility of industry sector in the stock exchange. In addition, the results of the final model show that inflation is the most effective source of volatility in the industry sector in the Tehran Stock Exchange, which indicates that the capital market is more sensitive to domestic variables. According to the final model estimates, inflation, exchange rate and gold price uncertainty in the short and long term have had a positive and significant effect on industry sector volatility. However, the effect of oil price uncertainty on the volatility of the industry price index be Negative in the long run. In this research, it is attempted to identify the pattern of uncertainty transferring of variables affecting the long-term volatility of the industrial sector in the Tehran Stock Exchange. In this regard, the mixed data model (MIDAS) and data of different internal and external variables with daily, monthly, seasonal and annual frequencies in the period 2009-2010 have been used. In the selection part of variables, by estimating different models, the variables affecting the volatility of industry sector in the long run were selected and finally the results of the selected model were presented. from various domestic and foreign variables, uncertainties of inflation, exchange rate, gold price and oil prices have significant effect in long run volatility of industry sector in the stock exchange. In addition, the results of the final model show that inflation is the most effective source of volatility in the industry sector in the Tehran Stock Exchange, which indicates that the capital market is more sensitive to domestic variables. According to the final model estimates, inflation, exchange rate and gold price uncertainty in the short and long term have had a positive and significant effect on industry sector volatility. However, the effect of oil price uncertainty on the volatility of the industry price index be Negative in the long run. https://aes.basu.ac.ir/article_4160_f816dc0acface7498e10496222e9db10.pdf