Please use this identifier to cite or link to this item:
http://hdl.handle.net/10071/12992
Author(s): | Eira, Lídia da Conceição Silva |
Advisor: | Cortez, Paulo Laureano, Raul M. S. |
Date: | 2016 |
Title: | Knowledge extraction of financial derivatives options in the maturity with data science techniques |
Reference: | EIRA,Lídia da Conceição Silva - Knowledge extraction of financial derivatives options in the maturity with data science techniques [Em linha]. Lisboa: ISCTE-IUL, 2016. Dissertação de mestrado. [Consult. Dia Mês Ano] Disponível em www:<http://hdl.handle.net/10071/12992>. |
Keywords: | Gestão de sistemas de informação Derivados financeiros DATA MINING Processo de decisão Árvore de decisão Information systems management Business intelligence Financial instruments Financial derivatives options |
Abstract: | To improve the level of support in information systems and quality of services by questioning the daily routine of a team using a set of financial evidence has been an interesting and challenging problem for many researcher and decision maker professionals. As part of a well-known investment bank that deals financial instruments like European-style options derivatives, operational teams are well aware that the focus of their work are around the evolution on pricing until the expiry moment. The choice of knowing more about financial derivatives options, especially in the maturity period, was made after a long process of study on economics and financial concepts in a certain institution. A special attention was given in subjects where information technology teams have less knowledge, which are the mathematical operation of derivative financial options and their implications in financial terms. As well, the identification of areas of business could be studied with greater interest for a specific organisation. |
Degree: | Mestrado em Gestão de Sistemas de Informação |
Peerreviewed: | yes |
Access type: | Open Access |
Appears in Collections: | T&D-DM - Dissertações de mestrado |
Files in This Item:
File | Description | Size | Format | |
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Eira_mestrado.pdf | 2,63 MB | Adobe PDF | View/Open |
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