Mostafa Heidari Haratemeh
Volume 4, Issue 2 , September 2023, , Pages 158-170
Abstract
Purpose: Business communities significantly promote free trade and trade security, so joining the business community is essential for long-term development. Therefore, the research aimed to form an international trade community based on network theory and resource dependence.Methodology: Twenty countries ...
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Purpose: Business communities significantly promote free trade and trade security, so joining the business community is essential for long-term development. Therefore, the research aimed to form an international trade community based on network theory and resource dependence.Methodology: Twenty countries were selected as a sample from the countries that engage in international trade based on the data available from the Comtrade database of the United Nations from 2005 to 2019.Findings: The results showed: 1) the trading partner factor has a positive effect on the formation of international trading communities, that when a country cooperates with a large number of trading partners or has a dominant position in the international trade network, the probability of the country forms the same community with other countries is higher, 2) when a country considers itself dependent on the resources of other countries, the possibility of forming a similar community with other countries increases accordingly and 3) network position plays positive role in regulating the relationship between resource dependence and the international trade community.Originality/Value: Countries that can boost resource trade based on the economic freedom and diversity of the importing country can reduce their dependence on other countries.
mostafa heidari haratemeh
Volume 2, Issue 3 , December 2021, , Pages 257-267
Abstract
Purpose: This study aimed to optimize the stock portfolio based on stochastic matrix theory in the stock market and to answer whether the relevant information will exist using the Marčenko–Pastur distribution.Methodology: The data of 31 shares in the Tehran Stock Exchange in 2016 - 2019 will be ...
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Purpose: This study aimed to optimize the stock portfolio based on stochastic matrix theory in the stock market and to answer whether the relevant information will exist using the Marčenko–Pastur distribution.Methodology: The data of 31 shares in the Tehran Stock Exchange in 2016 - 2019 will be examined for cross-correlation between shares. So, there will be 749 end-of-day prices and 748 logarithms of returns. This research was done using the descriptive-correlation method and is of an applied research type.Findings: The results showed: a) Observing the most extensive distribution of eigenvector components, it can be seen that there is a solid asymmetry to the left of the distribution, meaning that the market responds more to bad events than good events. b) By clearing the correlation matrix, the difference between the predicted and realized risk can be slightly reduced. In other words, the risk is reduced by identifying and removing non-valuable stocks from the portfolio portfolio. c) A stochastic stock matrix can significantly predict the realized return and risk of the market and, therefore, explain the risk of market information. d) The inverse participation ratio determines the stocks affecting the particular vectors, and the primary analysis of random matrices is based on adjusting this ratio using random matrix clearance.Originality/Value: Unlike other portfolio formation methods determining the weight of each asset in the portfolio, stochastic matrix theory identifies unused stocks and removes them from the stock portfolio, thereby improving portfolio return and risk.
