How To Navigate Missing Stock Fundamental Data?

Hi, I’m Rachel Carpenter, the CEO of Intrinio. One of our most popular products, which also happens to be our bread and butter, is stock fundamental data. This mission-critical, foundational data is needed by most investors and can be a powerful addition to any investment app or platform. It can, however, be a little complicated. One thing we sometimes hear from our customers is that there is “missing data”, so - if you’ve come across a “missing” piece of data, we wrote this article to clear it up for you.

Fundamental Data Basics: Overview

Let’s start from the top with some high-level concepts to help explain fundamental data discrepancies. No two fundamental data sets are alike, since every data provider has their own way of cleaning the data.

The data has to be cleaned, or “standardized”, because no two companies file their financial statements the same way. If the data isn’t comparable across companies and time periods - it’s nearly impossible to use.

Fundamental Data Basics: Templates

Okay, let’s move a level deeper. Companies in similar industries tend to file their financial statements the same way, but the statements can vary drastically across industries.

That’s why most companies, including Intrinio, use “templates” for different industries. At the highest level, there is a template for financial companies and a template for industrial companies. This is primarily due to the fact that financial companies earn “revenue” very differently than industrial companies. So, if you are seeing “different” or “missing” data, it may be because you are comparing a financial company to an industrial company.

Fundamental Data Basics: Company Size

The SEC gives publicly traded companies a lot of flexibility in what they file within their financial statements. The statements are filed in a programming language called XBRL, which is “extensible” meaning accountants and filers are able to “make up” any data tag they want.

Oftentimes, smaller companies will file less data overall within their financial statements in order to save time and money. So, if you are looking at a small company that is “missing” data this may be why. It just doesn’t exist!

Fundamental Data Basics: Filing Errors

Sometimes you’ll notice data that just seems completely wrong, and more often than not, this is because the company actually filed the data incorrectly. Even large companies mis-file on a regular basis. Sometimes our team can fix this data, but sometimes it doesn’t actually make sense to. 

Arguably everyone is looking at the wrong data, so it might be baked into analysis and “prices” already. This is a gray area, but it’s good to keep in mind that the company itself might have filed the wrong data point with the SEC. Companies can amend these filings and correct the data. Intrinio picks up those amended documents when they are published and incorporate it into our data.

Fundamental Data Basics: As-Reported vs. Standardized

Okay, the last basic concept when it comes to fundamental data is as-resported and standardized data feeds. Intrinio, like most providers, offers both “as reported” and “standardized” fundamental data feeds. The as-reported data includes data tags exactly as the company has filed them, using their own special style. 

Sometimes these data tags look as crazy as this: StatementCondensedCombinedAndConsolidatedStatementsOfCashFlowsUnaudited

This level of granularity can be valuable to some investors, which is why we offer it, but it’s nearly impossible to compare across companies and time periods with it, since none of it matches up. That’s where standardized fundamental data comes in. We drop all the data tags into standardized buckets so, for example, you can compare “total revenue” from two different companies.

As you can imagine, looking at Apple’s “as reported” data is very different from looking at its “standardized” data. So, if you are looking for a very specific data point and can’t find it, it’s worth checking out both of those endpoints.

Common Fundamental Data FAQs

Now that you have a basic understanding of fundamental data structure, which might clear up some of your questions about “missing fundamental data”, we’re going to dive into a couple of specific cases that we hear often from our customer base.

There’s missing data - it came back as “null”!

Let’s be honest - sometimes our team makes a mistake, and we are missing a data tag! This is a normal part of any data business, where 100% data quality is literally impossible.

However, most of the time a data point comes back as “null” because the company simply didn’t report that tag. This is most common with ADRs which stands for American Depository Receipt. These are foreign companies that file in the US. These companies have different filing requirements and may only file once a year instead of quarterly.

The dates are not lining up correctly in the data!

If you are looking at fundamental data and get confused by the dates, remember that not all fiscal years align with the calendar year. It's likely that as you start to look at different company fundamentals you will see dates that are all over the place.

This is normal - the data isn’t incorrect.

I can’t find trailing-twelve-months (TTM) on the balance_sheet!

Intrinio TTM data is only found on the cash_flow_statement, the income_statement, and our calculated data tags - so head there to look for it. This may change in the future as we expand the data set - so stay tuned.

You are missing the Q4 filing!

Fun fact, public companies don’t file a Q4 filing, their data from Q4 is wrapped up and included inside of their fiscal year (FY) document. If you are looking specifically for Q4 data, there’s a simple calculation that will get it for you if you pull in the FY data and subtract Q1, Q2, and Q3.

This can be done programmatically as well.

The ADR I am looking at is missing calculations!

ADRs are foreign companies that trade in the US and therefore submit some filings to the SEC. Most of these companies only file annually with the SEC, unlike US publicly traded companies who file quarterly.

Because of this, ADRs won’t have full calculations, trailing twelve months (TTM), year-to-date (YTD), or Q4 data.

Price to earnings is coming back NULL!

9 times out of 10, if you query our API asking for price to earnings and it comes back null, it’s because it was negative. If it’s negative, we always return the data as “null”.

Revenue is negative!

It’s always a surprise to see the revenue tag come back as a negative, but honestly, it’s probably right. Not every business makes money, and you will see this more often if you are looking at small caps or R&D-intensive businesses. Sometimes these companies don’t report revenue at all, so keep that in mind.

Intrinio’s Stock Fundamental Data Package

Okay, there you have it. Some of the most frequently asked questions about missing fundamental data, explained. Hopefully, this was helpful to you, but if you are experiencing other issues with the data you can chat with our team live on our website or submit a support ticket to let us know. Our team will get back to you ASAP with an explanation or a fix!

If you are looking for fundamental data, feel free to chat with us or head to our website to sign up for a free trial.

Our fundamental data packages include ALL of this:

• Standardized financial statements
• As-reported financial statements
• Hundreds of financial metrics and ratios
• Company reference and metadata
• Raw 10-Q, 10-K, 8-K, 20-F, and 40-F text
• Searchable 10-Q and 10-K notes
• Company news
• Insider transactions & ownership
• Institutional ownership
• Upcoming and historical IPOs
• Aggregrate sector and industry data
• Economic data

A subscription comes with top-notch support, partnership, co-marketing, and more. We make our plans super scalable so you can start small and risk-free on a bronze plan, and upgrade to silver or gold when you are ready.

Thanks for reading, please be sure to follow up with our blog to stay on top of the latest trends in fintech and financial data.

And as we always say at Intrinio, we can’t wait to see what you build with this data.

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