Measurement of Communication and Systematic Risk in Tehran Stock Exchange Index (with Linear and Nonlinear Granger Causality Approach and Regression Switching)

In this study, using linear and nonlinear Granger causality methods and regression switching, the relationships between the returns of important industry indices in the period 2008 to 2019 in order to invest in economic growth and development were examined. Based on the results obtained in the two periods of 2008 to 2013 and 2018 to 2019: 6, the relationship between the returns of the studied industry index has reached the highest value. In the linear Granger causality approach based on centrality criteria, the returns of metals index, machinery and investment are the most important and the returns of communication and banking index are the least important. It can also be said that the degree of effectiveness and efficiency of industry index returns is well affected by the amount of stock market fluctuations and this importance is asymmetric. In the nonlinear Granger causality approach based on the centrality criterion, the communication sector is the least important and the basic metals, chemical and machinery industries are the most important. In the period 2018 to 2019, the banking sector, automotive and communications industries are the most important and oil and metal products are the least important for investment.