{'fraction_non_alphanumeric': 0.020390070921985817, 'fraction_numerical': 0.0, 'mean_word_length': 5.307262569832402, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Network approach for stock market data mining and portfolio analysis

Stock market dynamics is of great importance to researchers from diverse fields. Network Analysis of stock data can play an important role in the study of stock market. In this paper, network based data mining of stock market is done to identify crucial players. Stock market network in United States created based on dynamics of stocks over one year captured as daily time series, is used for the analysis. Along with structural aspects of the market, our analysis revealed highly influential players based on their relationships with other high influential players. Portfolio analysis of top most of the influential players revealed crucial sectors of the market. Our findings suggest that financial services for specific sectors can reduce the systemic risk without affecting the overall economic growth. The stocks in the finance, banking, insurance, technology, machine, industrials, business services. energy, chemicals, retail, transport, real estate and building sector sectors are heavily dependent on each other and affect each other's performance.