Integrated Clustering Models of Company Performance Based on Financial Architecture

This paper studies financial architecture concept decomposition and its influence on company performance. Important role in this work allocated to clustering analysis methodologies. Empirical modeling and estimations are improved by different types of clustering on Russian and UK markets. It is shown that on the Russian and UK markets could exists sustainable clusters which might be identified by capital structure, ownership structure and corporate governance determinants as key drivers of clustering methodology. In terms of financial architecture, I also determine companies which are the same in Russian and UK markets. Moreover, some groups of companies (clusters) are unique for each market. This research also compares the emerging market financial architecture (Russia) with developed market (UK). Methodological part of this work connected with generalizing clustering methodology which is called as “algorithms ensemble” which could be an appropriate approach to clustering when classical methodologies cannot provide the certain results. Finally, I show that different financial architecture components have impact on different companies’ types (clusters).