A hybrid approach to combining CART and logistic regression for stock ranking
Data(s) |
2011
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Resumo |
The benefits of applying tree-based methods to the purpose of modelling financial assets as opposed to linear factor analysis are increasingly being understood by market practitioners. Tree-based models such as CART (classification and regression trees) are particularly well suited to analysing stock market data which is noisy and often contains non-linear relationships and high-order interactions. CART was originally developed in the 1980s by medical researchers disheartened by the stringent assumptions applied by traditional regression analysis (Brieman et al. [1984]). In the intervening years, CART has been successfully applied to many areas of finance such as the classification of financial distress of firms (see Frydman, Altman and Kao [1985]), asset allocation (see Sorensen, Mezrich and Miller [1996]), equity style timing (see Kao and Shumaker [1999]) and stock selection (see Sorensen, Miller and Ooi [2000])... |
Formato |
application/pdf |
Identificador | |
Publicador |
Institutional Investor Journals |
Relação |
http://eprints.qut.edu.au/54042/2/54042.pdf DOI:10.3905/jpm.2011.38.1.100 Zhu, Min, Philpotts, David, Sparks, Ross, & Stevenson, Maxwell J. (2011) A hybrid approach to combining CART and logistic regression for stock ranking. The Journal of Portfolio Management, 38(1), pp. 100-109. |
Direitos |
Copyright 2011 Institutional Investor Journals |
Fonte |
QUT Business School; School of Economics & Finance |
Palavras-Chave | #140000 ECONOMICS #CART #stock selection |
Tipo |
Journal Article |