Date of Award
Spring 2021
Degree Name
Bachelor of Science (BS)
Advisor(s)
Evan Katsamakas
Abstract
This thesis project addresses if narratives pertaining to publicly traded companies within web-based news articles can be perceived, plotted, and used to predict stock price movements. The foundational framework is grounded in economist Robert J. Shiller’s concept of Narrative Economics and the role of viral news stories in influencing economic decisions. Natural language processing tools such as sentiment analysis, word polarity, and text subjectivity can disclose stock-specific narratives concealed within the words, sentences, and writing structure of web-based news articles and headlines. These narratives can then be plotted over time and compared to historical stock price fluctuations to discern if any correlation exists or if a narrative can serve as a leading indicator for future price movements.
Recommended Citation
Fitzmaurice, Liam and Ma, Richard, "News, Narratives, and Natural Language Processing to Predict Stock Price Movements" (2021). Gabelli School of Business Honors Thesis Collection. 47.
https://research.library.fordham.edu/gabelli_thesis/47
