THE EFFICIENCY OF ENSEMBLE CLASSIFIERS IN PREDICTING THE JOHANNESBURG STOCK EXCHANGE ALL-SHARE INDEX DIRECTION

THE EFFICIENCY OF ENSEMBLE CLASSIFIERS IN PREDICTING THE JOHANNESBURG STOCK EXCHANGE ALL-SHARE INDEX DIRECTION

The success of investors in obtaining huge financial rewards from the stock market depends on their ability to predict the direction of the stock market index. The purpose of this study is to evaluate the efficacy of several ensemble prediction models (Boosted, RUS-Boosted, Subspace Disc, Bagged, an...

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Bibliographic Details
Main Authors: THABANG MOKOALELI-MOKOTELI, SHAUN RAMSUMAR, HIMA VADAPALLI
Format: Article
Language:English
Published: World Scientific Publishing 2019-12-01
Series:Journal of Financial Management, Markets and Institutions
Subjects:
ensemble classifiers
random forest
k-nearest neighbor
logistic regression
stock index direction
support vector machines
Online Access:http://www.worldscientific.com/doi/epdf/10.1142/S2282717X19500014

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http://www.worldscientific.com/doi/epdf/10.1142/S2282717X19500014

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