Identification, Clustering and Comparing Effective Industries at Tehran Stock Exchange Before and after its Legal Structure Change by Minimum Spanning Tree of Distance Ultra Metric

Abstract

The presence of a high degree cross-correlation between the synchronous time evaluation in Iran's industrial section made it impossible to forecast its economic future. As a shock hits an economy, the whole performance of industry overshadowed, the direct result is in performance fluctuation, the following is a shake in other parts of economy. As the new legal structure for stock exchange market passed in November 22, 2005, a new organization established under the title of The Securities and Exchange Organization (SEO). It was under the supervision of The Securities & Exchange Supreme Council and was responsible for administration and supervisory duties. The survey demonstrated that important industries influenced by those new set of rules and subsequently those affect other industries. We also identified and clustered effective industries, helpful in predicting the strongest industries in capital market as well as investors and managers in the market who need such information. Moreover we have investigated a period of three years that the repeat of a high degree cross-correlation between pair indices for different industries in TSE would result in hierarchical graph based on distance metric between different pairs industries. Following, the use of ultra metric function based on metric would show a minimum spanning tree from different industries on the basis of relation between them and intra-effect between these industries. The minimum spanning tree split up into two main clusters: the result from first group before structural change in TSE; clusters picturize center of four degree in minimum spanning tree, arrange set of minimum distances and thus groupings has been shown as follows: {1-Chemicals products, 2-basic metals}. second cluster before change, would result into center of three degree in minimum spanning tree, arrange set of minimum distances and thus groupings has been shown as follows: {1-Metal products, 2-Other non-metallic mineral products, 3-Investment institutions, 4-Cement,lime and Gypsum, 5-Finanacial and monetary intermediaries, 6-Banks and Credit institutions, 7-Ceramic and Tile, 8-Metal ores mining}.The result from first group after structural change in TSE; clusters picturize center of four degree in minimum spanning tree, arrange set of minimum distances and thus groupings has been shown as follows: {1-Investments,2- Other non-metallic mineral products}. Second cluster after change, would result into center of three degree in minimum spanning tree, arrange set of minimum distances and thus groupings has been shown as follows: {1- Cement , lime and Gypsum, 2- Financial and monetary intermediaries, 3-Sugar and sugar cube, 4-Metal ores mining, 5-Metal products, 6-Paper and paper products, 7-auto parts }.