University of Twente Student Theses
Using Sentiment Data from the Global Database for Events, Language and Tone (GDELT) to Predict Short-Term Stock Price Developments
Jakel, Tibor (2019) Using Sentiment Data from the Global Database for Events, Language and Tone (GDELT) to Predict Short-Term Stock Price Developments.
|
PDF
681kB |
| Abstract: | This study is set to investigate whether media sentiment, retrieved from the Global Database of Events, Language and Tone, can be a predictor of stock price. A business process model for the extraction and utilization of sentiment data from GDELT is presented and used for measuring the cross-correlation between average media sentiment and closing stock price of Facebook, Apple, Amazon, Alphabet and Tesla. A total of more than 5 million news article entries from GDELT were analyzed, 58.655 of which are relevant to this research. Alphabet is the only company with a strong positive cross-correlation of average daily media sentiment with adjusted closing stock price on the same day, while Facebook and Tesla exhibit weak negative correlations. |
| Item Type: | Essay (Bachelor) |
| Faculty: | BMS: Behavioural, Management and Social Sciences |
| Subject: | 54 computer science, 58 process technology, 85 business administration, organizational science |
| Programme: | International Business Administration BSc (50952) |
| Keywords: | Big data, Cross-correlation analysis, GDELT, Sentiment analysis, Stock market forecasting |
| Link to this item: | https://purl.utwente.nl/essays/78614 |
| Export this item as: | BibTeX EndNote HTML Citation Reference Manager |
Show download statistics for this publication
Show download statistics for this publicationRepository Staff Only: item control page