Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading

@article{Zhou2021TradeTE,
  title={Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading},
  author={Zhihan Zhou and Li-Qian Ma and Han Liu},
  journal={ArXiv},
  year={2021},
  volume={abs/2105.12825}
}
In this paper, we introduce an event-driven trading strategy that predicts stock movements by detecting corporate events from news articles. Unlike existing models that utilize textual features (e.g., bag-of-words) and sentiments to directly make stock predictions, we consider corporate events as the driving force behind stock movements and aim to profit from the temporary stock mispricing that may occur when corporate events take place. The core of the proposed strategy is a bi-level event… 

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