Brain News Topics Analysis with LLM


Product Summary 
The Brain News Topics Analysis dataset exploits an internal and customized large language model to monitor specific topics and their sentiment within the financial news flow for stocks.

For example, an investor may want to identify all news related to the topic “innovation” for a set of companies and track their sentiment with respect to each specific topic. Similarly, another investor can be interested in tracking all news related to the topic “risks for the company” and their sentiment.

Metrics Provided for Each Stock and Topic
For each stock and each topic three metrics are provided using the news published within a given time interval:

1.  The volume of news relevant to the topic
2.  The buzz, which measures the variation in the amount
of news that are published for each topic.
3.  A sentiment score for the specific topic, ranging
from -1 to +1.

All metrics are calculated based on the news published within a given time interval, e.g. the past 7 days that the model identifies as relevant for each topic.

List of Monitored Topics
The topics monitored by the Brain Large Language Model in the news flow are the following:

1. Contracts, Licenses, and Partnerships
2. Financial Results
3. Investor Asset Transactions and Positions
4. Governance and Management related Events 5. Innovation
6. Price variations
7. Rating and valuation estimates
8. Risks for the company
9. Legal

Coverage
The dataset covers the largest 1000 US stocks approximately corresponding to the Russell 1000 Index.

Brain Sentiment Indicator

• Financial news are collected every few minutes from various financial media sources.

• A dedicated Large Language Model evaluates the relevance with respect to each monitored topic. If the news item is relevant the model assigns a sentiment with respect to the specific topic.

• Daily, for each stock, the news relevant to each topic are aggregated over various time periods into both a buzz and a sentiment for the topic.

• Repetition of news is taken into account during the aggregation phase.

• The dataset files can be shared via FTP or an AWS S3 bucket.

• Daily historical data starting from 2017 will be available for testing.

Brain Copyright

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