Does mainstream news influence markets?

A semantic normalization based sentiment approach

COMP4560 PresentationSupervisor: Dr Timothy GrahamZhiheng Zhou

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Project Introduction • News may affect stock market price

• Apple, Google, Amazon, Microsoft

Project methodology

• Extract news data of above four companies. Combine, order them by date time

• Get score of each daily news by sentiment analyze approach

• Compare score plot to stock market price plot

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Sentiment analysis approach

• Original sentiment score function

• Using semantic normalization to improve sentiment score function

• Evaluation of the improvement

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Original Sentiment score function

• hu and liu [2] positive and negative dictionary

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• I love Apple.0 +1 0 total score: 1

Example

Using semantic normalization to improve sentiment score function

• Thesaurus (Synonyms dictionary) [3]• Hypernyms [4]• N-grams (multiple key words)• Grammatical modifier (not, very)

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Hypernyms and hyponyms example

• Kind of like the generic term and instance term

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N-grams example

• I look forward to getting the new iPhone.

• Look, forward, to : neutral

• Look forward to : positive

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Grammatical modifier

• I do not like Apple.

• Like : positive

• Not like : negative

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Evaluation --Granger causality test

• The Granger causality test is a statistical hypothesis test for determining whether one time series is useful in forecasting another.

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Project outcomes

Thanks for your watching.

Reference:[1] http://tozalezy.pl/index.php/the-news-impact-on-stock-prices/[2] Hu and Liu, KDD-2004[3] http://www.thesaurus.com[4] https://en.wikipedia.org/wiki/Hyponymy_and_hypernymy