Forecasting out-of-the-ordinary financial events

Being able to understand the financial market is very important for investors and, given the width and complexity of the topic, tools to support investor decisions are badly needed. In this paper we present Mercurio, a system that supports the decision-making process of financial investors through the automatic extraction and analysis of financial data coming from the Web. Mercurio formalizes the knowledge and reasoning of an expert in financial journalism and uses it to identify relevant events within financial newspapers. Moreover, it performs automatic analysis of financial indexes to identify relevant events related to the stock market. Then, sequential pattern mining is used to predict exceptional events on the basis of the knowledge of their past occurrences and relationships with other events, in order to to warn investors about them.