The future of finance is in the hands of developers. Get to know our tools built by developers for developers and sharpen your skills with code tutorials.
XBRL represents a massive shift in financial reporting, and it impacts what data you can access, how accurate that data is, and how difficult and expensive retrieving it will be for your company. We’ve put together a simple primer to explain what XBRL is and what it means for you.
In this post, Intrinio guest blogger Pedro Lealdino demonstrates how to install Intrinio's Python software development kit, how to import the data of the assets for analysis through the Intrinio API, and how to create a heatmap of the correlations of the returns of these assets.
Intrinio’s fundamental data is powered by our proprietary machine learning technology, which helps us maintain a high level of quality while keeping costs low. Read on to learn how we process fundamentals, what’s included, and how you can start your free trial to test the data.
Read our Q&A with TYKR, an investment platform designed to make investing easier, smarter, and faster. We spoke to Sean Tepper, founder and CEO of TYKR, about what inspired him to start the company, how TYKR stands out among other investing tools, and partnering with Intrinio.
Welcome to part V of the Quant Quickstart series from Analyzing Alpha's Leo Smigel. In this installment, you'll build on your existing strategy by learning how to rank stocks by their price-to-book ratio and selecting the top N stocks that are the cheapest based on this ratio.
Join Stefan Winter of findstox.com as he dissects the last decade of share buybacks by major players within the airline industry and examines why those buybacks were needed to offset dilution during the great financial crisis of 2008, using Intrinio's financial data in R.
Welcome to part IV of the Quant Quickstart series from Analyzing Alpha's Leo Smigel. In this installment, you'll learn how to complement price data with fundamentals from financial statements that publicly traded companies file with the SEC, all through the Intrinio Sandbox.
Welcome to part III of the Quant Quickstart series from Analyzing Alpha's Leo Smigel. In this installment, you'll learn how to create a simple mean reversion strategy that you’ll be able to build on to develop your own profitable trading strategies, using data from the Intrinio Sandbox.
Welcome to part II of the Quant Quickstart series from Analyzing Alpha's Leo Smigel. In our previous post, we discussed how to backtest a simple crossover strategy for a single stock. In this post, we’re going to build on this framework and graph the RSI of multiple securities.
Can you sort through billions of data points to find exactly the data you’re looking for? Can you connect multiple datasets and run complex queries…all within a few seconds? You can now. Intrinio is excited to announce direct database access to our financial data through Snowflake’s platform.