Towards Stock Recommendation and Portfolio Management Systems Using Network Analysis

Potential of complex network analysis to address complex systems such as stock markets is steadily gaining recognition. In this study, an approach for data mining of stock market based on complex networks is done as a preliminary for development of stock recommendation and/or portfolio management systems. Lobbying power of players is identified based on unweighted and weighted stock market networks that are created from United States stock data dynamics. Also, a criterion to check whether strength of correlation can significantly impact the assessment of local influence and lobbying power of players is devised. Portfolio analysis based on lobbying power and weighted lobbying power is carried out to reveal crucial industrial sections of the market. Our study revealed the affordability of offering financial services for firms belonging to such industrial sections for systemic risk reduction. Weighted lobby analysis is found to reveal in-depth structural insights for portfolio analysis than lobby centrality.