News Analytics for Financial Decision Support Defended on Thursday, 7 February 2013
This PhD thesis contributes to the newly emerged, growing body of scientific work on the use of News Analytics in Finance. Regarded as the next significant development in Automated Trading, News Analytics extends trading algorithms to incorporate information extracted from textual messages, by translating it into actionable, valuable knowledge.
The added-value of this dissertation can be divided roughly in two contributions. On one side, we contribute to the design and implementation of systems that use news for trading. On the other side we deliver more theoretical contributions related to the technology that is required for such systems.
The dissertation presents three systems that are able to use news for financial trading. The first system we present deals with structured text, in this case the monthly statements of the European Central Bank. Another system that we present introduces a framework for using information from news messages, in the form of events, for share trading. Finally, we introduce a more complex system, able to deal with time and time-related information as extracted from news. This system stands at the foundation of the time-aware framework for financial decision support that we introduce.
A considerable part of this dissertation deals with developing technology that we deem necessary for News Analytics in Finance. Here, we present a temporal web ontology language. We envision this language as a building block of all systems that deal with temporal knowledge. The language is able to represent abstract domain knowledge as well as more concrete (temporal) facts, such as the information contained in news messages.
Finally, despite its high relevance for business and the “next big thing in automated trading” status, News Analytics, especially in a financial context, is still in its academic infancy. Next to the concrete contributions of this dissertation, our work also delivers a proposal. Our discussion identifies the disciplines that can contribute to this emerging field. Finally, we provide possible focus points for future research.
news analytics, semantic web, semantic business information systems, finance, decision support