Analyzing stock market movements using news, tweets, stock prices and transactions volume data for APPLE (AAPL), GOOGLE (GOOG) and SONY (SNE)

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Conference Proceeding

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Goal: Today’s financial markets are of complex behavior which is the result of decisions made by many traders. Goal of this research is to calculate the relationship between financial markets stock prices, volumes, counts in financial news and tweets. Method: Collect the data sets for the three companies - Apple, Google and Sony 1. Collect tweets using Twitter API written in Python and extract tweet counts only related to stocks for the above companies. 2. Collect News data counts using News API, written in Python, only related to stocks for the above companies. 3. Collect stocks data including Volume, Close Price, etc. for the above companies. Findings: We find a positive correlation between the daily number of mentions of the above companies in the Tweets, News, daily stocks close prices and daily transactions volume of a company's stock after the tweets and news are released. Our results provide measurable support for the suggestion that activities in financial markets, news and tweets are fundamentally interlinked.

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ACM International Conference Proceeding Series

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