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Utilization of deep learning to mine insights from earning calls for stock price movement predictions

Published: 07 October 2021 Publication History

Abstract

Earnings calls are hosted by management of public companies to discuss the company's financial performance with analysts and investors. Information disclosed from an earning call is an essential source of data for analysts and investors to make investment decisions. Thus, we leverage earning call transcripts combined with companies' historical stock data and sector information to predict company's stock price movements. We propose to model these three features in a deep learning framework jointly, where attention mechanism is applied to the earnings call textual feature and a recurrent neural network (RNN) is used on the sequential stock price data. Our empirical experiments show that the proposed model is superior to the traditional baseline models and earnings call information can boost the stock price prediction performance.

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      cover image ACM Conferences
      ICAIF '20: Proceedings of the First ACM International Conference on AI in Finance
      October 2020
      422 pages
      ISBN:9781450375849
      DOI:10.1145/3383455
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      Published: 07 October 2021

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      Author Tags

      1. deep learning
      2. earnings call transcript
      3. stock price movement
      4. text mining

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      ICAIF '20: ACM International Conference on AI in Finance
      October 15 - 16, 2020
      New York, New York

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