Brain Sentiment Indicator / Stock Sentiment using NLP on financial news / 10000+ Global Stocks
# | CALCULATION_DATE |
NAME |
SHARE_CLASS_FIGI |
COMPOSITE_FIGI |
PRIMARY_EXCHANGE |
REGION |
VOLUME |
VOLUME_SENTIMENT |
SENTIMENT_SCORE |
BUZZ_VOLUME |
BUZZ_VOLUME_SENTIMENT |
||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxxxx |
2 | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxx | xxxxxxxx | xxxxxxx | Xxxxx |
3 | Xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx |
4 | Xxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx |
5 | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx |
6 | xxxxx | xxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx |
7 | xxxxx | Xxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxxxxx |
8 | xxxxxx | xxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx |
9 | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxx |
10 | xxxxxxxxx | Xxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxx |
... | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxx |
# | CALCULATION_DATE |
NAME |
SHARE_CLASS_FIGI |
COMPOSITE_FIGI |
PRIMARY_EXCHANGE |
REGION |
VOLUME |
VOLUME_SENTIMENT |
SENTIMENT_SCORE |
BUZZ_VOLUME |
BUZZ_VOLUME_SENTIMENT |
||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxxxx |
2 | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxx | xxxxxxxx | xxxxxxx | Xxxxx |
3 | Xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxx | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx |
4 | Xxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx |
5 | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx |
6 | xxxxx | xxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx |
7 | xxxxx | Xxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxx | xxxxx | Xxxxxxxxxx |
8 | xxxxxx | xxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx |
9 | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxx |
10 | xxxxxxxxx | Xxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxx |
... | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxx |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
CALCULATION_DATE
|
DateTime | 2020-01-01T00:00:00+00:00 | |
NAME
|
String | AGILENT TECHNOLOGIES INC | |
SHARE_CLASS_FIGI
|
String | BBG001SCTQY4 | |
COMPOSITE_FIGI
|
String | BBG000C2V3D6 | |
String | A | Stock Ticker | |
PRIMARY_EXCHANGE
|
String | NYSE | |
String | UNITED STATES | Country Name | |
REGION
|
String | NORTH AMERICA | |
VOLUME
|
Integer | 23 | |
VOLUME_SENTIMENT
|
Integer | 18 | |
SENTIMENT_SCORE
|
Float | 0.0265 | |
BUZZ_VOLUME
|
Float | -0.0291 | |
BUZZ_VOLUME_SENTIMENT
|
Float | 0.5198 |
Attribute | Type | Example | Mapping |
---|---|---|---|
CALCULATION_DATE
|
DateTime | 2020-01-01T00:00:00+00:00 | |
NAME
|
String | AGILENT TECHNOLOGIES INC | |
SHARE_CLASS_FIGI
|
String | BBG001SCTQY4 | |
COMPOSITE_FIGI
|
String | BBG000C2V3D6 | |
String | A | Stock Ticker | |
PRIMARY_EXCHANGE
|
String | NYSE | |
String | UNITED STATES | Country Name | |
REGION
|
String | NORTH AMERICA | |
VOLUME
|
Integer | 200 | |
VOLUME_SENTIMENT
|
Integer | 101 | |
SENTIMENT_SCORE
|
Float | 0.1094 | |
BUZZ_VOLUME
|
Float | 1.4845 | |
BUZZ_VOLUME_SENTIMENT
|
Float | 1.4502 |
Description
Country Coverage
History
Volume
10,000 | stocks covered |
Pricing
License | Starts at |
---|---|
One-off purchase | Not available |
Monthly License | Available |
Yearly License | Available |
Usage-based | Not available |
Suitable Company Sizes
Delivery
Use Cases
Categories
Related Products
Frequently asked questions
What is Brain Sentiment Indicator / Stock Sentiment using NLP on financial news / 10000+ Global Stocks?
The Brain Sentiment Indicator monitors public financial news for more than 10000 global stocks from about 2000 financial media sources in 33 languages.
What is Brain Sentiment Indicator / Stock Sentiment using NLP on financial news / 10000+ Global Stocks used for?
This product has 5 key use cases. Brain Company recommends using the data for Quantitative Investing, stock ranking, stock sentiment, Natural Language Processing (NLP), and financial news sentiment. Global businesses and organizations buy Stock Market Data from Brain Company to fuel their analytics and enrichment.
Who can use Brain Sentiment Indicator / Stock Sentiment using NLP on financial news / 10000+ Global Stocks?
This product is best suited if you’re a Small Business, Medium-sized Business, or Enterprise looking for Stock Market Data. Get in touch with Brain Company to see what their data can do for your business and find out which integrations they provide.
How far back does the data in Brain Sentiment Indicator / Stock Sentiment using NLP on financial news / 10000+ Global Stocks go?
This product has 5 years of historical coverage. It can be delivered on a daily basis.
Which countries does Brain Sentiment Indicator / Stock Sentiment using NLP on financial news / 10000+ Global Stocks cover?
This product includes data covering 240 countries like USA, China, Japan, Germany, and India. Brain Company is headquartered in Italy.
How much does Brain Sentiment Indicator / Stock Sentiment using NLP on financial news / 10000+ Global Stocks cost?
Pricing information for Brain Sentiment Indicator / Stock Sentiment using NLP on financial news / 10000+ Global Stocks is available by getting in contact with Brain Company. Connect with Brain Company to get a quote and arrange custom pricing models based on your data requirements.
How can I get Brain Sentiment Indicator / Stock Sentiment using NLP on financial news / 10000+ Global Stocks?
Businesses can buy Stock Market Data from Brain Company and get the data via S3 Bucket and REST API. Depending on your data requirements and subscription budget, Brain Company can deliver this product in .csv format.
What is the data quality of Brain Sentiment Indicator / Stock Sentiment using NLP on financial news / 10000+ Global Stocks?
You can compare and assess the data quality of Brain Company using Datarade’s data marketplace.
What are similar products to Brain Sentiment Indicator / Stock Sentiment using NLP on financial news / 10000+ Global Stocks?
This product has 3 related products. These alternatives include The Data Appeal Point of Interest (POI) Data API, Dataset 200 Million+ POI Data Mapped Measure Sentiment and Customer Experience, Dappier Financial & Real-Time Stock Market Data RAG API, LLM Compatible Market & Exchange Search, and Brand Data API Global Brand Sentiment Data 3.5M+ daily news articles. You can compare the best Stock Market Data providers and products via Datarade’s data marketplace and get the right data for your use case.