درخت حوزه‌های تخصصی

Stock return predictability has been extensively considered as a stylized reality. Theories indicate that returns should change along the time, and various studies have presented evidence on this point. On the other hand, there is an optimal portfolio in each regime, and one cannot claim that a specific portfolio can minimize risk and returns in each regime. On the other hand, the financial conditions index (FCI) is an important index to specify monetary policy conditions. Regarding the importance of the issue, this research aims to present a comprehensive index, including all monetary transmission mechanisms. In this regard, it is attempted to improve the efficiency of stock return predictability in Iran's economy by incorporating an FCI and identifying relationships between FCI and stock returns using the TVP-DMA model, which can resolve shortcomings of traditional models. The study is applied research in terms of purpose. Seasonal data over the period of April 1991 to July 2019 is used. The results based on TPV, DMS, and DMA models indicate that liquidity growth rate, economic growth rate, unemployment rate, exchange rate, financial condition index, oil revenues, misery index, and budget deficit, has significantly affected factors of stock returns in 30, 50, 11, 49, 66, 54, 7, and 84 periods of 104 periods, respectively. Accordingly, budget deficit, financial condition index, oil revenues, and economic growth are the most effective factors of stock returns predictability in Iran. Further, the incorporation of flexibility in coefficients of the financial development index leads to higher forecast accuracy.

The present study tries to find out the effect of energy consumption on economic growth and emission through applying non-linear framework, the smooth transition regression model, and threshold regression TAR by using the data from1969 to 2017. The results of empirical frameworks indicate that the economic growth is gradually affected by energy consumption and STR model demonstrates the dynamics. However, the changes in energy consumption on emission has taken place faster and the parametric changes have been more severe. In both states, there is one model which consists of two regimes. In this model, the fossil fuel energy consumption growth variable is selected as transition or threshold variable which is optimal model. The fossil fuel energy consumption variable is considered as a policy variable which in both frameworks have been selected in 12 percent level. The results of TAR model revealed that in high regime of fossil fuel consumption, the first lag of fossil fuel consumption and the logarithm of population have impact on emission and in high regime of low fossil fuel consumption, the fist lag on variable growth of fossil fuel consumption and electricity have impact on emission. Also, the results of TAR model indicated that the electricity energy consumption growth in low regime, the growth in electricity consumption and first lag investment affect the economic growth. The fossil fuel consumption in high regime, the growth variables of fossil fuel consumption and investment have impact on the economic growth.