Information Extraction in Finance

Professional traders are overwhelmed with news. Extracting the relevant information is slow and difficult — yet trading decisions must be immediate.

Written primarily for financial organisations and business analysts, this book introduces the algorithms that automatically extract the information you need from Internet news and deliver it in a well-structured form. It focuses on the principles behind each method rather than its numerical implementation, leaving out mathematical detail that could obscure the text, and concentrates on each method’s strengths and weaknesses. The authors include many practical examples with full references, algorithms for related problems that may be useful in finance, and core techniques from other areas of information extraction that could be applied to financial news analysis.

The book gives a complete overview of past and present information extraction algorithms — work otherwise scattered across many research institutes — and so a complete picture of the research in the field. Its descriptions of the basic algorithms give non-specialists a clear idea of the most common techniques, and its references will be valuable to every reader.

Who it is for

• Expert researchers who want a complete overview of other researchers’ work;
• new researchers who want a survey of the field before developing their own algorithms;
• financial organisations planning to buy an information extraction system or fund research on the topic;
• students taking a course or writing a dissertation on natural language algorithms.