درخت حوزه‌های تخصصی

Value at Risk model based on a switching regime approach was used in this study to optimize portfolios consisting of industry index (petroleum products, investment, chemical products, and metal products). For this purpose, the VaR of returns on index should first be extracted through parametric models of the (GARCH) family in each of the above industries by using regime transitions. After the risk of return on index is obtained for each industry, the optimal portfolio is created in the next step based on VaR minimization, and the optimal value of each industry is determined in the portfolio. According to the results, (MRS-FIEGARCH) model had no superiority in VaR estimation over the other parametric models of the GARCH family. In fact (MS-EGARCH-t) was introduced as the optimal model. Among the designated industries, returns on indices followed regime transitions only in chemical products and investment by showing asymmetric reactions to external shocks. Moreover, the optimal weights were on the rise in the industries where VaR decreased over time, whereas the optimal weight of the portfolio decreased in the industries where VaR increased over time. The higher share of an optimal portfolio belonged to the industries where stock returns had lower rates of VaR. The risk-return-ratio was employed to show that the optimal portfolio with a risk rate was measured by considering the switching regime was superior over the optimal portfolio with a risk rate extracted without considering the switching effects. To create an optimal portfolio, it is then recommended to make investments in the industries characterized by higher stability in prices and lower fluctuations in stock returns in the long run. This approach can be employed to obtain the best results from optimal portfolio preparation in the worst-case scenario of the market fluctuations.

The stock market, as a symbol of the capital market, is one of the most important sectors of the economy of any country and, unlike the money market, is responsible for the long-term financing of corporate capital. The capital market collects funds from surplus sectors and channels them to institutions that need financing. This study investigates the feasibility of establishing a market for the Kabul Stock Exchange. It is a survey in terms of nature and descriptive method and is applied in relation to the purpose. For the feasibility study of the present study, six platforms were identified using Delphi method. Non-random and purposive sampling was used, and according to Morgan’s table, 180 people were selected from three groups of university professors, experts from the ministries of Finance, Economy, Trade and Industry, the Central Bank and a number of people in Kabul. The validity and reliability of the questionnaire was confirmed by Delphi method and Cronbach’s alpha test. SPSS statistical software was used to analyze the data. From the results of one-sample t-test, it can be seen that all H1’s sub-hypotheses were confirmed in relation to the six platforms, which means that in the current situation, Kabul city is not in a favorable situation in terms of infrastructure and requirements for legal, economic, technical and technological, cultural, social and human capital platforms for the establishment of the stock market, and the conditions for the establishment of Kabul Stock Exchange do not exist. The Friedman test showed that the degree of readiness for the establishment of Kabul Stock Exchange depended on the human capital, economic, legal, cultural, technical and technological or social platforms.

In the present study, the authors examined the impact of financial sanctions on economic growth using Iran's data and intervention time-series analysis over the period 2005-2017. Financial sanctions targeted the country's financial resources and increased interest rates and medium- and long-term financing costs. In general, financial sanctions adversely affected the financial sector. In this regard, blocking of assets and restricted access to financial and foreign exchange resources, depreciated domestic currency, reduced investment, exports, and production along with increased inflation and unemployment ultimately reduced economic growth. The results indicated the effectiveness of financial sanctions on economic growth in the short-run. However, during the third period (2010-2014), when severe and multilateral financial sanctions are imposed, the coefficient is negative (0.54), which is higher, compared to the other periods. As the economic sanctions of Iran have intensified, the economic growth has slowed down. Nevertheless, in the long run, financial sanctions have had a weaker negative effect of 0.19 on the economic growth.