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        <title>Detecting Causes of Stock Price Rise and Decline by Machine Reading Comprehension with BERT</title>
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            <namePart type="given">Mahmoud</namePart>
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    <abstract>In this paper, we focused on news reported when stock prices fluctuate significantly. The news reported when stock prices change is a very useful source of information on what factors cause stock prices to change. However, because it is manually produced, not all events that cause stock prices to change are necessarily reported. Thus, in order to provide investors with information on those causes of stock price changes, it is necessary to develop a system to collect information on events that could be closely related to the stock price changes of certain companies from the Internet. As the first step towards developing such a system, this paper takes an approach of employing a BERT-based machine reading comprehension model, which extracts causes of stock price rise and decline from news reports on stock price changes. In the evaluation, the approach of using the title of the article as the question of machine reading comprehension performs well. It is shown that the fine-tuned machine reading comprehension model successfully detects additional causes of stock price rise and decline other than those stated in the title of the article.</abstract>
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%0 Conference Proceedings
%T Detecting Causes of Stock Price Rise and Decline by Machine Reading Comprehension with BERT
%A Tsutsumi, Gakuto
%A Utsuro, Takehito
%Y El-Haj, Mahmoud
%Y Rayson, Paul
%Y Zmandar, Nadhem
%S Proceedings of the 4th Financial Narrative Processing Workshop @LREC2022
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F tsutsumi-utsuro-2022-detecting
%X In this paper, we focused on news reported when stock prices fluctuate significantly. The news reported when stock prices change is a very useful source of information on what factors cause stock prices to change. However, because it is manually produced, not all events that cause stock prices to change are necessarily reported. Thus, in order to provide investors with information on those causes of stock price changes, it is necessary to develop a system to collect information on events that could be closely related to the stock price changes of certain companies from the Internet. As the first step towards developing such a system, this paper takes an approach of employing a BERT-based machine reading comprehension model, which extracts causes of stock price rise and decline from news reports on stock price changes. In the evaluation, the approach of using the title of the article as the question of machine reading comprehension performs well. It is shown that the fine-tuned machine reading comprehension model successfully detects additional causes of stock price rise and decline other than those stated in the title of the article.
%U https://aclanthology.org/2022.fnp-1.4
%P 27-35

Markdown (Informal)

[Detecting Causes of Stock Price Rise and Decline by Machine Reading Comprehension with BERT](https://aclanthology.org/2022.fnp-1.4) (Tsutsumi & Utsuro, FNP 2022)

• Detecting Causes of Stock Price Rise and Decline by Machine Reading Comprehension with BERT (Tsutsumi & Utsuro, FNP 2022)

ACL

• Gakuto Tsutsumi and Takehito Utsuro. 2022. Detecting Causes of Stock Price Rise and Decline by Machine Reading Comprehension with BERT. In Proceedings of the 4th Financial Narrative Processing Workshop @LREC2022, pages 27–35, Marseille, France. European Language Resources Association.