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Machine learning in predicting stock indexes: the role of online stock forum sentiment in MIDAS model

Machine learning in predicting stock indexes: the role of online stock forum sentiment in MIDAS... This study aims to accurately predict stock indexes by combining sentiment analysis with machine learning. We apply web crawlers to collect text information from a representative Chinese stock forum, build a high-frequency investor sentiment index, and select a suitable mixed-data sampling model to make nowcasting predictions on the Shanghai Composite Index (SHA). We show that the investors’ sentiments significantly drive the SHA, and that the exchange rate is the most powerful indicator for short term SHA prediction. Additionally, no autoregressive effect exists on the SHA. These results will benefit investors and policymakers. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Asia-Pacific Journal of Accounting & Economics Taylor & Francis

Machine learning in predicting stock indexes: the role of online stock forum sentiment in MIDAS model

20 pages

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References (45)

Publisher
Taylor & Francis
Copyright
© 2023 City University of Hong Kong and National Taiwan University
ISSN
2164-2257
eISSN
1608-1625
DOI
10.1080/16081625.2023.2215234
Publisher site
See Article on Publisher Site

Abstract

This study aims to accurately predict stock indexes by combining sentiment analysis with machine learning. We apply web crawlers to collect text information from a representative Chinese stock forum, build a high-frequency investor sentiment index, and select a suitable mixed-data sampling model to make nowcasting predictions on the Shanghai Composite Index (SHA). We show that the investors’ sentiments significantly drive the SHA, and that the exchange rate is the most powerful indicator for short term SHA prediction. Additionally, no autoregressive effect exists on the SHA. These results will benefit investors and policymakers.

Journal

Asia-Pacific Journal of Accounting & EconomicsTaylor & Francis

Published: May 24, 2023

Keywords: Investor sentiment index; MIDAS model; stock market prediction; web crawler; shanghai composite index

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