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(The Analysis on Korean Stock Market By High Frequency Data and TextClassification using LSTM)
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Sungjae Yoon1, Aiko Suge1, Hiroshi Takahashi111ďĐŷÛâæâæƷųÎůŔŠũŤ
Graduate School of Business Administration, Keio University

Abstract: This study analyzes the relationship between news aritcles and stock price changes. Whileseveral researches about stock return analysis using deep learning and frequency data have been reported,
Korean cases haven’t. In this study, we analyze the influence of news articles on Korean stock markets
using high frequency data and text classification by LSTM network.

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79 Ð¦Ôâ (2017)[ǎǐ]E.Chong, C.Han, F.C. Park [2017] “Deep learningnetworks for stock market analysis and prediction :Methodology, data representations, and case studies,”
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