Advanced Visu-Analytics - Machine Learning - Predictive Tools for Stock Market and Finance

In this study we use visual-analytics techniques combined with advanced machine learning & clustering techniques, and graph theory to analysis big data and find the structure within the data.

In this experiment, we developed a series of the models that can cluster stock market (Trend Analytics, Investment, etc.) , similar companies (i.e. Marketing, Healthcare, Telecommunication, Banking, etc.), including Twitter analytics- sentiment financial/stock market/investment analysis . The training data are taken from Yahoo! historical Stock Market Finance and Wikipedia articles about companies from the S&P 500 index.

The models could be used to label up-and-coming companies based on similarities to existing S&P 500 companies. In addition, the historical data can be used to predict the performance of similar companies and track the Market more effectively and precisely in addition to adjust all the financial factors (ie. PE index, etc).

Our new analytics techniques combined with visual-analytics tools and Twitter analytics- sentiment financial/stock market/investment analysis have been able to predict the Up and Down of the stock market more precisely and accurately compare to traditional time series analysis of single company-time-series anal

ysis.