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MarketWatch Financial News Impact Dataset
Entertainment & Media Consumption
Tags and Keywords
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Free
About
This dataset offers URL links to news articles from MarketWatch, specifically focusing on NASDAQ100 companies, spanning from 1st January 2017 to 1st May 2021. It comprises information such as article dates, sentiment scores, associated stock symbols, and stock prices recorded on, as well as before and after, the publication date of each article. The inclusion of stock returns further enhances its utility for analysing the impact of news events on stock market movements.
Columns
The dataset is presented in a tabular format and includes the following columns:
- ARTICLE_ID: A unique identifier for each news article.
- SYMBOL: The ticker symbol corresponding to the stock.
- LINK: The URL of the news article.
- ARTICLE_DATE: The date on which the news article was published.
- POLARITY: A calculated polarity score for the article's content.
- AWS_POLARITY: The polarity score derived from AWS Comprehend for the article.
- P_at_0d: The stock price recorded on the same day as the article's publication.
- P_bef_15d: The stock price 15 days prior to the news article's publication.
- P_bef_7d: The stock price 7 days prior to the news article's publication.
- P_bef_3d: The stock price 3 days prior to the news article's publication.
Distribution
The dataset is typically structured as a CSV data file. It contains approximately 136,000 unique values across its entries. The data includes stock prices ranging from 4.59 to 3531.45 and polarity scores varying from -1.00 to 1.00. The time range covered by the dataset extends from 1st January 2017 to 1st May 2021.
Usage
This dataset is well-suited for a variety of applications and use cases, including:
- Financial Market Analysis: Investigating the correlation between news sentiment and stock price fluctuations.
- Sentiment Analysis Modelling: Developing and refining models to assess the emotional tone of financial news.
- Algorithmic Trading Strategy Development: Designing and backtesting automated trading strategies that react to news events.
- Natural Language Processing (NLP) Research: Utilising the text links and sentiment scores for advanced NLP studies in finance.
- Academic Research: Conducting econometric and financial studies on market efficiency and news impact.
- Predictive Analytics: Building machine learning models, such as linear regression, to forecast stock behaviour based on news.
Coverage
The dataset primarily covers companies listed on the NASDAQ100 index. The time period spans from 1st January 2017 to 1st May 2021. While focused on NASDAQ100 companies, the data's relevance can be considered global due to the international reach and influence of these organisations.
License
CC-BY-SA
Who Can Use It
- Financial Professionals: Including analysts, portfolio managers, and traders looking to gain insights from news.
- Data Scientists: For developing and deploying machine learning models in the financial domain.
- Academic Researchers: In fields such as finance, economics, and computational linguistics.
- Developers: Creating applications that integrate financial news sentiment.
- Students: Undertaking projects in data science, finance, or artificial intelligence.
Dataset Name Suggestions
- NASDAQ100 News Sentiment & Stock Price Tracker
- MarketWatch Financial News Impact Dataset
- Stock Price Volatility from News
- Financial News & NASDAQ100 Performance
- Sentiment-Driven Stock Market Data
Attributes
Original Data Source: MarketWatch News Links and Prices for NASDAQ100
QUALITY