Forecasting Stock Market Trends using Deep Learning on Financial and Textual Data

Georgios-Markos Chatziloizos; Dimitrios Gunopulos; Konstantinos Konstantinou

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Paper

Forecasting Stock Market Trends using Deep Learning on Financial and Textual Data

Topics: Data Science; Deep Learning; Deep Learning and Big Data; Neural Network Applications

In Proceedings of the 10th International Conference on Data Science, Technology and Applications DATA - Volume 1, 105-114, 2021

Authors: Georgios-Markos Chatziloizos ; Dimitrios Gunopulos and Konstantinos Konstantinou

Affiliation: Department of Informatics and Telecommunications, National and Kapodistrian University of Athens, Athens, Greece

Keyword(s): Technical Analysis, Sentiment Analysis, Machine Learning, Stock Market.

Abstract: Stock market research has increased significantly in recent years. Researchers from both economics and computer science backgrounds are applying novel machine learning techniques to the stock market. In this paper we combine some of the techniques used in both of these fields, namely Technical Analysis and Sentiment Analysis techniques, to show whether or not it is possible to successfully forecast the trend of the stock price and to what extent. Using the four tickers AAPL, GOOG, NVDA and S&P 500 Information Technology, we collected historical financial data and historical textual data and we used each type of data individually and in unison, to display in which case the results were more accurate and more profitable. We describe in detail how we analysed each type of data, how we used it to come up with our results.

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Paper citation in several formats:

Chatziloizos, G.; Gunopulos, D. and Konstantinou, K. (2021). Forecasting Stock Market Trends using Deep Learning on Financial and Textual Data. In Proceedings of the 10th International Conference on Data Science, Technology and Applications - DATA; ISBN 978-989-758-521-0; ISSN 2184-285X, SciTePress, pages 105-114. DOI: 10.5220/0010618801050114

@conference{data21,
author={Georgios{-}Markos Chatziloizos. and Dimitrios Gunopulos. and Konstantinos Konstantinou.},
title={Forecasting Stock Market Trends using Deep Learning on Financial and Textual Data},
booktitle={Proceedings of the 10th International Conference on Data Science, Technology and Applications - DATA},
year={2021},
pages={105-114},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010618801050114},
isbn={978-989-758-521-0},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Data Science, Technology and Applications - DATA
TI - Forecasting Stock Market Trends using Deep Learning on Financial and Textual Data
SN - 978-989-758-521-0
IS - 2184-285X
AU - Chatziloizos, G.
AU - Gunopulos, D.
AU - Konstantinou, K.
PY - 2021
SP - 105
EP - 114
DO - 10.5220/0010618801050114
PB - SciTePress