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Evaluating multiple classifiers for stock price direction prediction · Study

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ArticleEvaluating multiple classifiers for stock price direction prediction

Michel Ballings2015

Article2015

Evaluating multiple classifiers for stock price direction prediction

Michel Ballings · Dirk Van den Poel · Nathalie Hespeels · Ruben Gryp

597 citations·0/0 files stored·Expert Systems with Applications

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Stock Market Forecasting Methods Financial Markets and Investment Strategies Forecasting Techniques and Applications

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References

1997A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting 1970EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK*1995A desicion-theoretic generalization of on-line learning and an application to boosting 2003The Efficient Market Hypothesis and Its Critics 2003Financial time series forecasting using support vector machines 2014Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques 2004Forecasting stock market movement direction with support vector machine 2000Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation

Cited by

2016Computational Intelligence and Financial Markets: A Survey and Future Directions 2019Literature review: Machine learning techniques applied to financial market prediction 2019A systematic review of fundamental and technical analysis of stock market predictions 2018An innovative neural network approach for stock market prediction 2020Predicting Stock Market Trends Using Machine Learning and Deep Learning Algorithms Via Continuous and Binary Data; a Comparative Analysis

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Details

Year2015

Typearticle

Published2015-05-13

VenueExpert Systems with Applications

ISSN-L0957-4174

Languageen

Citations597

Files0 public / 0

ShelfStock Market Forecasting Methods

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doi10.1016/j.eswa.2015.05.013

openalex_workW333233685

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2019Stock Market Analysis: A Review and Taxonomy of Prediction Techniques

2020Deep Learning for Stock Market Prediction

2018Algorithmic financial trading with deep convolutional neural networks: Time series to image conversion approach