درخت حوزه‌های تخصصی

The mutual relationship between monetary and fiscal policies and value at risk is one of the most important topics in the financial economics literature and accounts for the vast majority of empirical studies. Therefore, the main objective of this paper is to investigate the effects of monetary and fiscal policies on conditional value at risk in the financial sectors of the stock exchange, bank and insurance during the years 1995-2017. For this purpose, by quantile regression method and in the form of Adrian and Brunnermeier approach, the conditional value at risk of these three financial sectors is estimated and then by using the seemingly unrelated regression equation approach in panel data evaluated the effect of liquidity money variables. The interest rate on facility payments, the real exchange rate, the government's budget deficit, real GDP growth, and the degree of economic openness are subject to conditional risk. The results of the model estimation indicate the significance of the effect of liquidity money, interest rate on facility payments and real exchange rate variables on conditional value at risk in each of three relevant equations, and real GDP growth variable in the model, Exposure to the conditional value at risk of the insurance sector has a negative and significant effect. Also, the degree of openness of the economy in any of the three estimated equations has no significant effect on the conditional value at risk. 

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.