A binary ensemble classifier for high-frequency trading

Abstract

The aim of this study was to model and use machine learning techniques to maximize the chance of a market maker be executed successfully in a stock market, that is, when their bid and ask orders are filled at the desired prices. In this context, a binary ensemble classifier was created to decide whether, at a specific time, is or not propitious to start a… (More)
DOI: 10.1109/IJCNN.2015.7280602

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