Find, Analyze, and Value Stocks Quickly With Intrinio

Intrinio provides many different data feeds and applications in its Fintech marketplace and this blog explains how to use three of those apps to analyze stocks using the US Public Company Financials API. Intrinio makes it possible to screen for stocks based on set parameters, quickly run a DCF on those companies, and then dig into the details for those that look under valued- all for free. This article will show you how.

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Modeling Financial Data in R with Intrinio

This is the third blog in a series showing how to use Intrinio financial data in R or R Studio to create quant models. The tools at Intrinio are built to make modeling financial data straightforward. The first blog shows the basics of making an API call for financial data in R. The second blog shows how to write two functions, one to pull in historical stock prices and another to pull in historical fundamentals data.

This blog takes both of those blogs a step further, creating a single function that will pull in historical stock prices as well as historical fundamentals for many companies and many metrics at once. The function code as well as an explanation of what is going on under the hood is included, enabling R developers to quickly create a data frame for analysis with exactly the data they want.

Update 05/22/16- Check out this blog as well showing how to create a for loop in R to get multiple pages of data via API. This example shows the best way (known to the author) to parse JSON from an API in R.

Creating a data frame with the desired tickers, date ranges, and financial data

Please take a look at this code. Its not long, the point is to see how easy it is to pull the data you need:

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Developer Spotlight #1: WakeBotApp [blog series]

Our mission at Intrinio is to power a generation of applications that will fundamentally change the way our broken financial system works. Intrinio data feeds form the basis of large enterprise business reporting applications, Fintech web-apps, simple mobile apps and even blogs. It's rewarding to see our product come to life at the hands of today's most innovative developers building powerful things.

We're lucky to be in a business where we grow together with our customers, and we're proud to show off their hard work. Each blog in this series will feature a developer or a startup that has leveraged our financial data feeds to build something incredible.

These are their stories.

wakebot-app

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Historical Financial Data in R for Stocks

This blog is a follow up to a blog explaining how to pull Intrinio financial data into R and R-Studio. In that blog I showed the basics of how to get the data flowing. In this blog I take it one step further and provide custom functions that will allow you to pull historical data into R very efficiently. I plan to build quant models, predicting historical prices based on historical metrics for a stock, and use a subset of the historical data to back test my models. This blog explains how to get the data for such an analysis.

Update 05/22/16- Check out this blog as well showing how to create a for loop in R to get multiple pages of data via API. This example shows the best way (known to the author) to parse JSON from an API in R.

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