A Study Of Investment Strategies Of A Shares Based On Complex Network

The perspective of Network, as a new tool of analyzing system, receives its popularity. The stock markets, a complex system as it is, is impacted by both internal and external factors. Volatility of individual stock price is correlated both to its operation conditions and that of other stocks. Utilizing the Complex System allows us to analyze the stock market as a whole. Thus, we can capture the dynamic features of stock markets.The research objectives of this paper are Shanghai and Shenzhen A shares. We constructed stock system with the close prices series and analyzed the static features of network embedded in by threshold approach and minimum spanning tree method. By shuffling the dynamic windows, we analyzed the topological properties through the changes. We found "small world" feature of Chinese stock market and the topological properties diverse during the stock prices fluctuations.In our paper, we made some application with the features of Complex System. First, we made exponential fitting with the features of Networks. We got better fining effects when we chose degree and number of nodes as indexes. Based on clustering, we optimized our stock picking process, and we found that exponential fitting based on modular algorithm gives better fitting effects. Though the fitting effects of degree is not satisfactory, degree can be regarded as an important index of optimizing investment strategies. By constructing simple investment strategies and optimizing strategies by degree, we got investment strategies with higher returns. Thus, we offered an important reference to investors who are seeking better yields.