Abstract

Selecting an investment portfolio has inspired several models aimed at optimising the set of securities which an in-vesttor may select according to a number of specific decision criteria such as risk, expected return and planning hori-zon. 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 con-cerning computing and systems engineering, focusing on techniques particularly aimed at producing beliefs regar-ding investment portfolios.

Details

Title
Exploiting stock data: a survey of state of the art computational techniques aimed at producing beliefs regarding investment portfolios
Author
Mario Linares Vásquez; Hernández Losada, Diego Fernando; Fabio González Osorio
Pages
105-116
Section
Articles
Publication year
2008
Publication date
2008
Publisher
Universidad Nacional de Colombia
ISSN
01205609
e-ISSN
22488723
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
1677615060
Copyright
Copyright Universidad Nacional de Colombia 2008