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Algorithms 2018, 11(11), 181; https://doi.org/10.3390/a11110181

Measuring the Impact of Financial News and Social Media on Stock Market Modeling Using Time Series Mining Techniques

1
Department of Information and Communication Systems Engineering, University of the Aegean, GR-83200 Samos, Greece
2
Institute of Informatics and Telecommunications, National Center for Scientific Center “Demokritos”, GR-15310 Athens, Greece
*
Author to whom correspondence should be addressed.
Received: 23 August 2018 / Revised: 17 October 2018 / Accepted: 23 October 2018 / Published: 6 November 2018
(This article belongs to the Special Issue Humanistic Data Mining: Tools and Applications)
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Abstract

In this work, we study the task of predicting the closing price of the following day of a stock, based on technical analysis, news articles and public opinions. The intuition of this study lies in the fact that technical analysis contains information about the event, but not the cause of the change, while data like news articles and public opinions may be interpreted as a cause. The paper uses time series analysis techniques such as Symbolic Aggregate Approximation (SAX) and Dynamic Time Warping (DTW) to study the existence of a relation between price data and textual information, either from news or social media. Pattern matching techniques from time series data are also incorporated, in order to experimentally validate potential correlations of price and textual information within given time periods. The ultimate goal is to create a forecasting model that exploits the previously discovered patterns in order to augment the forecasting accuracy. Results obtained from the experimental phase are promising. The performance of the classifier shows clear signs of improvement and robustness within the time periods where patterns between stock price and the textual information have been identified, compared to the periods where patterns did not exist. View Full-Text
Keywords: time series analysis; symbolic aggregate approximation; dynamic time warping; stock market analysis time series analysis; symbolic aggregate approximation; dynamic time warping; stock market analysis
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Kollintza-Kyriakoulia, F.; Maragoudakis, M.; Krithara, A. Measuring the Impact of Financial News and Social Media on Stock Market Modeling Using Time Series Mining Techniques. Algorithms 2018, 11, 181.

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