By Marco Costantino and Paolo Coletti
ISBN-10: 1845641469
ISBN-13: 9781845641467
This ebook presents a whole review of prior and current algorithms forinformation extraction, that have regrettably been scattered between diversified learn institutes. It hence offers an entire proposal of the researchactivities within the box. It comprises simple algorithms descriptions, which provide the non-expert reader an idea of the commonest ideas during this box, and references.Professional monetary investors are at present beaten with information. Extracting proper details is a protracted and difficult job, whereas tradingdecisions require rapid activities. essentially meant for financialorganizations and company analysts, this e-book offers an creation tothe algorithmic ideas to immediately extract the specified info from web information and procure it in a good based shape. It locations emphasis at the ideas of the tactic instead of its numericalimplementation, omitting the mathematical information that would differently vague the textual content and attempting to specialise in the benefits and at the difficulties of every process. The authors additionally contain many sensible examples with entire references, algorithms for related difficulties, that may be beneficial within the monetary box, and uncomplicated thoughts utilized in different informationextraction fields that could be imported to the research of monetary information.
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Extra info for Information Extraction in Finance
Sample text
For example, a quantitative tool can process the price-history of a particular share, taking into account any selected variable that is relevant and show the main periodical cycles and trends, and return a qualitative indication of the current market’s trend. Other tools can be used to predict the future prices of the same shares or to suggest when is the best time to sell or buy a particular share. Many quantitative tools have been historically based on conventional techniques. More recently, tools based on innovative techniques have been introduced.
The vector space model Another approach is based on the frequency of a word in a document and, thus, on the identification of key terms in the document which can be matched with the queries supplied by the user, through a process is known as indexing. In fact, a term appearing often in the text may be more important for the identification of relevant information than a term appearing rarely. In contrast, if the same term occurs in many documents, it will probably be irrelevant for finding the relevant information.
This service behaves in the same way as Reuters, limiting the information extraction to the link between news and the corresponding company’s market data. FactSet provides the usual news and market information together with a lot of static information, such as phone number, password, type of conference call and important company investor relations contact information. However, it concentrates mostly on corporate events, such as conference call, for which it provides dates and transcripts. This system also provides analysis and expert’s estimates, trying to give to the professional user access to as many different sources as possible.
Information Extraction in Finance by Marco Costantino and Paolo Coletti
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