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2019 | OriginalPaper | Buchkapitel

An Investment Recommender Multi-agent System in Financial Technology

verfasst von : Elena Hernández, Inés Sittón, Sara Rodríguez, Ana B. Gil, Roberto J. García

Erschienen in: International Joint Conference SOCO’18-CISIS’18-ICEUTE’18

Verlag: Springer International Publishing

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Abstract

In this article is presented a review of the state of the art on Financial Technology (Fintech) for the design of a novel recommender system. A social computing platform is proposed, based on Virtual Organizations (VOs), that allows to improve user experience in actions that is associated with the process of investment recommendation. The work presents agents functionalities and an algorithm that will improve the accuracy of the Recommender_agent which is in charge of the Case-based reasoning (CBR) system. The data that will be collected and will feed the CBR corresponds to user’s characteristics, the asset classes, profitability, interest rate, history stock market information and financial news published in the media.

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Metadaten
Titel
An Investment Recommender Multi-agent System in Financial Technology
verfasst von
Elena Hernández
Inés Sittón
Sara Rodríguez
Ana B. Gil
Roberto J. García
Copyright-Jahr
2019
Buch
International Joint Conference SOCO’18-CISIS’18-ICEUTE’18

Print ISBN: 978-3-319-94119-6

Electronic ISBN: 978-3-319-94120-2

Copyright-Jahr: 2019

DOI
https://doi.org/10.1007/978-3-319-94120-2_1