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| Type | Master's Thesis |
| Scope | Discipline-based scholarship |
| Title | Post-Jump Return Dynamics and News Sentiment |
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| Institution | University of Zurich |
| Faculty | Faculty of Business, Economics and Informatics |
| Number of Pages | 61 |
| Date | 2023 |
| Abstract Text | We investigate the stock return predictive power at the high-frequency level after statistically significant overnight jumps conditioned on prevailing stock and market level news sentiment. We provide evidence that sentiment variables as well as the jump direction explain variation in intraday returns following a jump event and document the effect over the trading day. We identify overnight jumps through highfrequency based jump tests and calculate our sentiment variables from the Thomson Reuters News Analytics dataset. We document our findings for S&P 500 constituents from 2004 to 2021. In the case of positive jumps, we document a stronger overreaction behaviour to both, the direction of the jump and to the prevailing news sentiment, whilst for negative jumps, we can only document a reversal behaviour relating to the direction of the jump. In addition, the paper presents a trading strategy based on the observed phenomena. The strategy exhibits no correlation to the market portfolio, exhibits tail hedging characteristics, whilst maintaining a positive drift component. Key words: stock return predictability, statistical jumps, private information, news sentiment, nontrading hour information, market level sentiment, company-specific sentiment |
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