Social network news sentiments and stock price movement: a correlation analysis
The stock market prediction is one of the most important issues extensively investigated in the existing academic literatures. Researchers have discovered that real-time news has much bearing on the movement of stock prices. Analysts now have to deal with vast amounts of real time, unstructured stre...
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| 主要な著者: | , , , |
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| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
Penerbit UTM Press
2015
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| 主題: | |
| オンライン･アクセス: | http://eprints.utm.my/id/eprint/55529/1/NaomieSalim2015_SocialNetworkNewsSentimentsandStock.pdf http://eprints.utm.my/id/eprint/55529/ http://dx.doi.org/10.11113/jt.v77.6565 |
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| 要約: | The stock market prediction is one of the most important issues extensively investigated in the existing academic literatures. Researchers have discovered that real-time news has much bearing on the movement of stock prices. Analysts now have to deal with vast amounts of real time, unstructured streaming data due to the advent of electronic and online news sources. This paper aims to investigate the relationship between online news and actual stock price movement. R programming together with R package are applied to capture and analyze the online news data from Yahoo Financial. The data are plotted into graphs to analyze the relationship between the two variables. In addition, to ensure the levels of the relationship, the Pearson’s correlation and Spearman’s Rank are applied to test whether there is a statistical association between these two variables. This initial analysis of dynamic online news based on sentimental words is relatively constructive. |
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