Introducing
Sep 10, 2024
Welcome to the September 2024 edition of our release notes. This update provides a comprehensive overview of the latest enhancements to the Polygon.io platform, featuring new tools, API functionalities, and educational content designed to improve your experience and capabilities.
This section highlights the latest enhancements and additions to the Polygon.io platform. From infrastructure upgrades to new functionalities, these developments are designed to improve service performance and user experience.
Polygon.io has expanded its infrastructure with a new data center in Chicago, now fully operational and serving live traffic. This addition complements our Equinix NY campus data center, enabling us to operate two dedicated facilities that improve service performance and reliability through added redundancy and decreased latency for all users.
Our Ticker News API has been upgraded to include advanced sentiment analysis, utilizing Large Language Models (LLMs) to extract structured insights such as ticker mentions, sentiment, and summaries from unstructured financial news. This enhancement enables users to monitor sentiment trends efficiently for specific tickers, providing a valuable tool for market analysis.
Here’s a simple example of how to retrieve news insights for a ticker using the API:
from polygon import RESTClient client = RESTClient() # Fetch news articles for 'AAPL' with insights news_articles = client.list_ticker_news( "AAPL", params={"published_utc.gte": "2024-09-03"}, order="desc", limit=1000 ) # Display the title and insights for each article for article in news_articles: print(f"{article.title} [Insights = {article.insights}]")
Here's an example of the Insights object that showcases these enhancements:
Title: Apple, Nvidia Key Supplier TSMC Leads Taiwanese Chip Giants To Localize Neon Gas Production By 2025 Insights = [ Insight( sentiment="positive", sentiment_reasoning="TSMC is leading the initiative to localize neon gas production, which is a significant step towards enhancing supply chain reliability for the Taiwanese semiconductor industry.", ticker="TSM", ), Insight( sentiment="positive", sentiment_reasoning="UMC is considering purchasing locally produced neon gas from Linde LienHwa, further supporting the initiative to localize neon gas production.", ticker="UMC", ), Insight( sentiment="positive", sentiment_reasoning="TSMC, a key supplier for Nvidia, is leading the effort to localize neon gas production, which will benefit Nvidia's supply chain.", ticker="NVDA", ), ]
If you're interested in a more in-depth application, our detailed tutorial demonstrates how to extract these insights for tickers like
We are excited to introduce the Related Companies API, a new feature designed to identify and analyze connections between companies based on news articles and financial data. This innovative tool can help you uncover inter-company relationships across various sectors.
Here’s a simple example of how to retrieve related companies for a ticker using the API:
from polygon import RESTClient client = RESTClient() # Retrieve and display companies related to Apple Inc. related_companies = client.get_related_companies("AAPL") print(related_companies)
Here's an example of the related companies being returned:
$ python examples/rest/stocks-related_companies.py [ RelatedCompany(ticker="MSFT"), RelatedCompany(ticker="GOOGL"), RelatedCompany(ticker="AMZN"), RelatedCompany(ticker="GOOG"), RelatedCompany(ticker="TSLA"), RelatedCompany(ticker="NVDA"), RelatedCompany(ticker="META"), RelatedCompany(ticker="NFLX"), RelatedCompany(ticker="DIS"), RelatedCompany(ticker="BRK.B"), ]
If you're interested in a more in-depth application, please refer to our detailed tutorial on using the Related Companies API.
The Polygon.io Postman collection has been launched to streamline the API development process. This tool facilitates building, testing, and validating API calls, enhancing productivity and optimizing the developer experience. Learn more about it here.
Explore our comprehensive tutorials designed to help you make the most of Polygon.io's features. Each guide provides detailed instructions and insights, enabling you to leverage our APIs and tools for better data analysis and decision-making.
If you need to download large volumes of market data this tutorial is tailor-made for you. It provides a comprehensive guide on accessing and downloading historical stock market data through our Flat Files service, which is ideal for anyone managing extensive datasets across stocks, options, indices, forex, and cryptocurrencies. This tutorial covers everything from setting up an S3 client to navigating the interface and downloading the compressed CSV files. For a detailed walkthrough, you can explore the full tutorial on our blog.
Want to learn how stock splits work and how they impact aggregate data? This tutorial is for you. We dive into Nvidia's 10-for-1 stock split using our Stock Splits API, demonstrating how to retrieve split information and analyze its effects on aggregate market data. This guide provides crucial insights into the adjustments' impacts on financial analysis, making it a good resource for anyone looking to understand the nuances of stock market splits. If you want to see the full details, please go to the tutorial here.
We thought it might be fun to dive deep and explore what happens under the hood in the stocks and options markets when a major event like the July 2024 CrowdStrike outage occurs. This comprehensive analysis utilizes our datasets to detail the incident's effects on market dynamics, providing a vivid illustration of how significant events can impact financial markets. This case study is a perfect example of the practical application of our data in understanding and visualizing real-world market behaviors. If you're curious to see the insights we uncovered, check out the full analysis here.
We invite you to explore these updates and tutorials. Your feedback is vital as we continue to refine and enhance our offerings. Stay connected for more updates and features in future releases.
Team Polygon
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