Schumaker, Robert P. and Zhang, Yulei and Huang, Chun-Neng and Chen, Hsinchun (2011) Evaluating sentiment in financial news articles: Working paper series--11-10. Working Paper. NAU W.A. Franke College of Business.
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Abstract
We investigate the pairing of a financial news article prediction system, AZFinText, with sentiment analysis techniques. From our comparisons we found that news articles of a subjective nature were easier to predict in both price direction (59.0% vs 50.4% without sentiment) and through a simple trading engine (3.30% return vs 2.41% without sentiment). Looking into sentiment further, we found that news articles of a negative sentiment were easiest to predict in both price direction (50.9% vs 50.4% without sentiment) and our simple trading engine (3.04% return vs 2.41% without sentiment). Investigating the negative sentiment further, we found that AZFinText was best able to predict price decreases in articles of a positive sentiment (53.5%) and price increases in articles of a negative or neutral sentiment (52.4% and 49.5% respectively).
| Item Type: | Monograph (Working Paper) |
|---|---|
| Publisher’s Statement: | Copyright, where appropriate, is held by the author. |
| ID number or DOI: | 11-10 |
| Keywords: | Working paper, Knowledge management, prediction from textual documents, sentiment analysis |
| Subjects: | H Social Sciences > HG Finance |
| NAU Depositing Author Academic Status: | Faculty/Staff |
| Department/Unit: | The W.A. Franke College of Business |
| Date Deposited: | 17 Oct 2015 09:25 |
| URI: | http://openknowledge.nau.edu/id/eprint/1478 |
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