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Tracking Turbulence Through Financial News During COVID-19

arXiv 2109.04369 ↗First posted 9 Sep 2021cs.CLcited by 0

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Abstract (arXiv)

Grave human toll notwithstanding, the COVID-19 pandemic created uniquely unstable conditions in financial markets. In this work we uncover and discuss relationships involving sentiment in financial publications during the 2020 pandemic-motivated U.S. financial crash. First, we introduce a set of expert annotations of financial sentiment for articles from major American financial news publishers. After an exploratory data analysis, we then describe a CNN-based architecture to address the task of predicting financial sentiment in this anomalous, tumultuous setting. Our best performing model achieves a maximum weighted F1 score of 0.746, establishing a strong performance benchmark. Using predictions from our top performing model, we close by conducting a statistical correlation study with real stock market data, finding interesting and strong relationships between financial news and the S&P 500 index, trading volume, market volatility, and different single-factor ETFs.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 11 of its 27 references that are in the map. First posted on arXiv 9 Sep 2021.

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References · 11

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  3. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,346
  4. 2019ERNIE: Enhanced Language Representation with Informative Entitiescited by 525
  5. 2019FinBERT: Financial Sentiment Analysis with Pre-trained Language Modelscited by 378
  6. 2013Good Debt or Bad Debt: Detecting Semantic Orientations in Economic Textscited by 310
  7. 2020Impact of News on the Commodity Market: Dataset and Resultscited by 80
  8. 2014DepecheMood: a Lexicon for Emotion Analysis from Crowd-Annotated Newscited by 13
  9. 2015SentiBench - a benchmark comparison of state-of-the-practice sentiment analysis methodscited by 5
  10. 2017Fortia-FBK at SemEval-2017 Task 5: Bullish or Bearish? Inferring Sentiment towards Brands from Financial News Headlinescited by 5
  11. 2021Impact of the COVID-19 outbreak on Italy's country reputation and stock market performance: a sentiment analysis approachcited by 1

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