Publication
Title
Design and evaluation of empirical models for stock price prediction
Author
Abstract
The efficiënt market hypothesis and related theories claim that it is impossible to predict future stock prices. Even so, empirical research has countered this claim by achieving better than random prediction performance. Using a model built from a combination of text mining and time series prediction, we provide further evidence to counter the efficient market hypothesis. We discuss the difficulties in evaluating such models by investigating the drawbacks of the common choices of evaluation metrics used in these empirical studies. We continue by suggesting alternative techniques to validate stock prediction models, circumventing these shortcomings. Finally, a trading system is built for the Euronext Brussels stock exchange market. In our framework, we applied a novel sentiment mining technique in the design of the model and show the usefulness of state-of-the-art explanation-based techniques to validate the resulting models.
Language
English
Source (series)
Research paper / UA, Faculty of Applied Economics ; 2012:17
Publication
Antwerp : 2012
Volume/pages
22 p.
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Record
Identification
Creation 26.09.2012
Last edited 04.09.2013
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