Proposal and Implementation of New Trading Strategies for Stock Markets using Web Data

The use of social networks and the Web is growing every day, generating a lot of data that can aggregate value to different applications. In financial market, there is a need to better understand the situations that occur in the capital market, through negotiation strategies and technical indicators that can assist in analysis and investment decisions. This work presents a study of the time series data of historical quotations on assets of BM&FBOVESPA and Web data about investments (e.g., social networks, forums, blogs, and news), with the objective of seeking subsidies that can assist in a better understanding of financial market behavior. Based on the theory of Elliott Wave, we propose several trading strategies, evaluating them in a realistic simulator of the financial market. The results show how the use of distinct indicators, such as the ones that are based on Web data, can help minimizing losses and maximizing the triggers that generate profit.