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FNSPID: A Comprehensive Financial News Dataset in Time Series

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  • Zihan Dong
  • Xinyu Fan
  • Zhiyuan Peng

Abstract

Financial market predictions utilize historical data to anticipate future stock prices and market trends. Traditionally, these predictions have focused on the statistical analysis of quantitative factors, such as stock prices, trading volumes, inflation rates, and changes in industrial production. Recent advancements in large language models motivate the integrated financial analysis of both sentiment data, particularly market news, and numerical factors. Nonetheless, this methodology frequently encounters constraints due to the paucity of extensive datasets that amalgamate both quantitative and qualitative sentiment analyses. To address this challenge, we introduce a large-scale financial dataset, namely, Financial News and Stock Price Integration Dataset (FNSPID). It comprises 29.7 million stock prices and 15.7 million time-aligned financial news records for 4,775 S&P500 companies, covering the period from 1999 to 2023, sourced from 4 stock market news websites. We demonstrate that FNSPID excels existing stock market datasets in scale and diversity while uniquely incorporating sentiment information. Through financial analysis experiments on FNSPID, we propose: (1) the dataset's size and quality significantly boost market prediction accuracy; (2) adding sentiment scores modestly enhances performance on the transformer-based model; (3) a reproducible procedure that can update the dataset. Completed work, code, documentation, and examples are available at github.com/Zdong104/FNSPID. FNSPID offers unprecedented opportunities for the financial research community to advance predictive modeling and analysis.

Suggested Citation

  • Zihan Dong & Xinyu Fan & Zhiyuan Peng, 2024. "FNSPID: A Comprehensive Financial News Dataset in Time Series," Papers 2402.06698, arXiv.org.
    • Handle: RePEc:arx:papers:2402.06698
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    References listed on IDEAS

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    1. Dhruhi Sheth & Manan Shah, 2023. "Predicting stock market using machine learning: best and accurate way to know future stock prices," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 1-18, February.
    2. Fama, Eugene F & French, Kenneth R, 1992. "The Cross-Section of Expected Stock Returns," Journal of Finance, American Finance Association, vol. 47(2), pages 427-465, June.
    3. Boyu Zhang & Hongyang Yang & Xiao-Yang Liu, 2023. "Instruct-FinGPT: Financial Sentiment Analysis by Instruction Tuning of General-Purpose Large Language Models," Papers 2306.12659, arXiv.org.
    4. Yen-Ju Hsu & Yang-Cheng Lu & J. Jimmy Yang, 2021. "News sentiment and stock market volatility," Review of Quantitative Finance and Accounting, Springer, vol. 57(3), pages 1093-1122, October.
    5. Sakariyahu, Rilwan & Johan, Sofia & Lawal, Rodiat & Paterson, Audrey & Chatzivgeri, Eleni, 2023. "Dynamic connectedness between investors’ sentiment and asset prices: A comparison between major markets in Europe and USA," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 89(C).
    6. Alejandro Lopez-Lira & Yuehua Tang, 2023. "Can ChatGPT Forecast Stock Price Movements? Return Predictability and Large Language Models," Papers 2304.07619, arXiv.org, revised Sep 2024.
    7. William F. Sharpe, 1964. "Capital Asset Prices: A Theory Of Market Equilibrium Under Conditions Of Risk," Journal of Finance, American Finance Association, vol. 19(3), pages 425-442, September.
    8. Chen, Nai-fu, 1983. "Some Empirical Tests of the Theory of Arbitrage Pricing," Journal of Finance, American Finance Association, vol. 38(5), pages 1393-1414, December.
    9. David E. Allen & Michael McAleer & Abhay K. Singh, 2019. "Daily market news sentiment and stock prices," Applied Economics, Taylor & Francis Journals, vol. 51(30), pages 3212-3235, June.
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    Cited by:

    1. Hamidou Tembine & Manzoor Ahmed Khan & Issa Bamia, 2024. "Mean-Field-Type Transformers," Mathematics, MDPI, vol. 12(22), pages 1-51, November.

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