EGARCH model

The present research aims to evaluate impacts of crude oil price return index, Bloomberg Petroleum Index and Bloomberg energy index on stock market returns of 121 companies listed in Tehran stock exchange in a 10 years' period from early 2006 to April 2016. First, explanatory variables were aligned with petroleum products index mostly due to application of dollar data. Subsequently, to check variables stationary, Dickey-Fuller generalized test was considered and ARCH test was adopted to check for Heteroscedasticity in error terms and residual values. Finally, EGARCH was used to address model heteroscedasticity. The results showed that variations of Petroleum Bloomberg index, crude oil price and Bloomberg energy index could explain changes in Tehran stock exchange index returns. Any rise in oil prices increases total Stock Exchange returns. On the other hand, Stock Exchange index returns is aligned with Petroleum Bloomberg index.at the same time changes in Tehran stock exchange index returns was reversely correlated with changes in energy index return among others.

Nowadays, financial markets and especially the stock market are important and undeniable sources of financing for investment toward the economic growth and development of countries. These markets also have a tangible role as a basis for implementing monetary policy. This study aims to investigate the effect of monetary volatility on the seasonal performance of the Iranian stock market from April 2001 to March 2021.The TEDPIX index of the Tehran Stock Exchange was used for designing and explaining the research model for measuring monetary policy uncertainty in terms of the debt of banks to the Central Bank and to measure the Iranian stock market’s performance. With portfolio theory as the theoretical basis for the study, the housing price index and the exchange rate were added to the research model as other independent variables due to their importance to the portfolio of individuals. In this regard, monetary policy uncertainty was first calculated using the exponential general autoregressive conditional heteroskedastic (EGARCH) method. Then, the effect of uncertainty on the TEDPIX index was calculated using the vector auto regression (VAR) statistical method in EVIEWS 12. The findings indicate a significant negative correlation between monetary policy uncertainty and short and long term TEDPIX index. Moreover, exchange rate and housing price index has a significant positive effect on the TEDPIX index.