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This is an announcement of Jingwen Jiang's Dissertation Defense.
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<div class="ContentPasted0">Candidate: Jingwen Jiang</div>
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<div class="ContentPasted0">Date: Tuesday, December 06, 2022</div>
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<div class="ContentPasted0">Time: 1 pm CST</div>
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<div class="ContentPasted0">Remote Location: https://uchicago.zoom.us/j/97772156520?pwd=bGl5QnByWTA5Vk8rbjdsUitMYWhzdz09</div>
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<div class="ContentPasted0">Title: Expected Returns and Foundation Models of Language</div>
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<div class="ContentPasted0">Abstract: We extract contextualized representations of news text to predict returns using the state-of-the-art foundation models in natural language processing. The contextualized representation of news reflects its content more
accurately than the bag-of-words representation prevalent in the literature. In particular, the latter approach is more prone to errors when negation words appear in news articles. Moreover, we provide polyglot evidence on news-induced return predictability
in 16 international equity markets with news written in 13 different languages. Information in newswires is assimilated into prices with an inefficient delay that is broadly consistent with limits-to-arbitrage, yet can be exploited in a real-time trading strategy.
Furthermore, a trading strategy that exploits fresh news in the form of news alerts leads to even higher Sharpe ratios.</div>
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<div class="ContentPasted0">Advisors: Dacheng Xiu</div>
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<div class="ContentPasted0">Co-advisor: Janos Simon</div>
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Committee Members: Dacheng Xiu, Janos Simon, and Chenhao Tan<br>
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