FNSPID: Financial News for Time-Series Forecasting and Market Trends

FNSPID provides financial news articles aligned for time-series forecasting, developed by Zihan1004 and associated with Arxiv paper 2402.06698. The dataset focuses on market trends and investor sentiment through the lens of temporal news data. It was last updated in April 2024.

Use Cases

• Sentiment analysis of news article text to predict stock price movements
• Time-series forecasting using news publication timestamps to identify market trends
• Classification of market indicators based on the content of financial news

Strengths

• Academic provenance via Arxiv paper 2402.06698
• Specifically structured for time-series forecasting tasks
• Focuses on market-specific investor sentiment

Limitations

• Unknown total record count
• Lack of explicit column documentation in the primary metadata
• Potential geographic bias toward the US market as indicated by the Regionus tag

Provenance

Source

Arxiv paper 2402.06698

Freshness

Last updated April 2024.

Geography

United States