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Financial Network Analysis with Dense Subgraph Detection Algorithms

Student: Kondratev Nikita

Supervisor: Ekaterina K. Batsyna

Faculty: Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod)

Educational Programme: Data Mining (Master)

Final Grade: 9

Year of Graduation: 2018

Current research is focused on applying dense subgraph discovery algorithms to stock market analysis. This paper aims to find the exact algorithm, that allows to find solution on real data in reasonable time. Classification of dense subgraph definitions is presented and dense subgraph discovery algorithms are observed. The computation time of the implemented algorithms is compared on random graphs and on the market graphs, constructed on real data of Russian and USA stock markets. Also, the analysis of dense subgraphs found on the graphs of markets using a modified version of the Degree Decomposition Algorithm is carried out.

Full text (added May 13, 2018)

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