Exploiting stock data: a survey of state of the art computational techniques aimed at producing beliefs regarding investment portfolios

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1. Verfasser: Mario Linares Vásquez
Format: Artículo científico
Sprache:en
Veröffentlicht: Universidad Nacional de Colombia 2008
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author Mario Linares Vásquez
author_facet Mario Linares Vásquez
contents Exploiting stock data: a survey of state of the art computational techniques aimed at producing beliefs regarding investment portfolios Mario Linares Vásquez Diego Fernando Hernández Losada Fabio González Osorio Ingeniería risk stock return belief profile Selecting an investment portfolio has inspired several models aimed at optimising the set of securities which an investtor may select according to a number of specific decision criteria such as risk, expected return and planning horizon. The classical approach has been developed for supporting the two stages of portfolio selection and is supported by disciplines such as econometrics, technical analysis and corporative finance. However, with the emerging field of computational finance, new and interesting techniques have arisen in line with the need for the automatic processing of vast volumes of information. This paper surveys such new techniques which belong to the body of knowledge concerning computing and systems engineering, focusing on techniques particularly aimed at producing beliefs regarding investment portfolios. 2008 artículo científico 0120-5609 https://www.redalyc.org/articulo.oa?id=64328112 en http://www.redalyc.org/revista.oa?id=643 Ingeniería e Investigación application/pdf Universidad Nacional de Colombia Ingeniería e Investigación (Colombia) Num.1 Vol.28
format Artículo científico
id redalyc_64328112
institution Redalyc
language en
publishDate 2008
publisher Universidad Nacional de Colombia
spellingShingle Exploiting stock data: a survey of state of the art computational techniques aimed at producing beliefs regarding investment portfolios
Mario Linares Vásquez
Ingeniería
risk
stock
return
belief
profile
Exploiting stock data: a survey of state of the art computational techniques aimed at producing beliefs regarding investment portfolios Mario Linares Vásquez Diego Fernando Hernández Losada Fabio González Osorio Ingeniería risk stock return belief profile Selecting an investment portfolio has inspired several models aimed at optimising the set of securities which an investtor may select according to a number of specific decision criteria such as risk, expected return and planning horizon. The classical approach has been developed for supporting the two stages of portfolio selection and is supported by disciplines such as econometrics, technical analysis and corporative finance. However, with the emerging field of computational finance, new and interesting techniques have arisen in line with the need for the automatic processing of vast volumes of information. This paper surveys such new techniques which belong to the body of knowledge concerning computing and systems engineering, focusing on techniques particularly aimed at producing beliefs regarding investment portfolios. 2008 artículo científico 0120-5609 https://www.redalyc.org/articulo.oa?id=64328112 en http://www.redalyc.org/revista.oa?id=643 Ingeniería e Investigación application/pdf Universidad Nacional de Colombia Ingeniería e Investigación (Colombia) Num.1 Vol.28
title Exploiting stock data: a survey of state of the art computational techniques aimed at producing beliefs regarding investment portfolios
topic Ingeniería
risk
stock
return
belief
profile
url https://www.redalyc.org/articulo.oa?id=64328112