3D Subspace Clustering for Value Investing

Autor:	Kelvin Sim, Clifton Phua, Gao Cong, Vivekanand Gopalkrishnan
Rok vydání:	2014
Předmět:	Subspace clustering Artificial Intelligence Computer Networks and Communications Computer science Value (economics) Value investing Intelligent decision support system Data mining computer.software_genre Cluster analysis computer Financial data mining
Zdroj:	IEEE Intelligent Systems. 29:52-59
ISSN:	1941-1294 1541-1672
DOI:	10.1109/mis.2012.24
Popis:	Using Graham's rules on picking stocks has been proven to generate profits for value investors. The authors propose using 3D subspace clustering to generate rules to pick potential undervalued stocks; 3D subspace clustering is effective in handling high-dimensional financial data and is adaptive to new data. In addition, its results aren't influenced by human biases and emotions, and are easily interpretable.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::37b811bd0365aa1485c9746de53a0673 https://doi.org/10.1109/mis.2012.24 Zobrazit plný text záznamu