A Clustering Methodology for Industry Categorization Using Business Cycle

Analyzing the relationship among business cycles of various industries is important not only for government decision-making but also for personal portfolio diversification choice, it is therefore of great importance to classify industrial categories and analyze their relationship and linkage mode based on their business cycle index. Based on time series angle variation, a clustering method is proposed to classify the industry. The proposed method can overcome the shortcomings of traditional distance similarity in the translation and fluctuations operation, thus better reflecting the time sequence trends. For verification purpose, the business cycle indices of ten industries from CEInet statistical database are used for empirical analysis. Experimental results revealed that the proposed angle variation based clustering approach can not only obtain better categorization results than traditional clustering approaches, but also provide an important reference in understanding the relation between industries for investors and regulators.