Challenges When Analyzing Financial Data
We all love free, right? This fact is as true in the financial markets as it is anywhere else. But free can be costly, especially when it comes to the accuracy of financial data. Data providers that offer free access to financial data make no warranties about its accuracy. That leaves you wondering about the challenges when analyzing financial data.
If you subscribe to a paid service, then you should lean on your data provider to ensure the data is correct. That’s their job, and if they are unwilling to perform this essential service to paid members, it’s time to find another provider. If you use free services, however, you won’t have the luxury of leaning on your data provider. You can undoubtedly alert them to the fact that there are incorrect data points in their data. But they aren’t going to make any assurances of correctness.
What Are Your Data Needs?
For the most part, data, even from free services, is going to be accurate. But what do you do when it isn’t? If you depend on this data and make trading decisions from it, you could be steered in the wrong direction when the information is incorrect.
There are no easy answers. If you are using free data for algorithmic or program trades (ones that are automatic), then you may be risking capital by relying on free data. If you are making money from your trades, then the right answer is to subscribe to a paid service so that you have a guarantee of accurate data. Most algorithmic traders, except for those experimenting with different techniques, will opt for the paid route to ensure correctness.
If you are an investor relying on free data, it’s not likely that you are going to make frequent trades. Therefore, my suggestion, in this case, is to check your data with other sources before you make any trades. In other words, continue to use the free data in a manner that you’ve been using, but when your ready to take the plunge, check out the accuracy of your numbers.
I ran into this situation recently with a paid provider that I am using. I won’t name drop here because they are working on the problem. Besides, the amount they charge per month for access is so cheap, I consider them a free provider, for all intents and purposes.
Here is what happened. I was finishing writing an article about reconciling the ROE with an example. In this article, I explained how financial data providers like Morningstar and Yahoo Finance would report certain metrics for companies, as the ROE. However, when you try to tie out the numbers yourself, you often find that the results you get don’t match. You can learn what to do in that situation by reading the article.
Why Reconcile the Numbers?
Why should you even bother to tie out the numbers? Why not just use what is reported in Morningstar and Yahoo Finance? The reason I wrote the article was to show that an indicator such as the ROE can be broken down into constituent parts. Those parts can tell you more about a company and actually get hidden by factoring into a short form. Most financial reporting is based on this short form.
The point here is that since the data providers don’t report on theses constituent parts and the fact that those parts offer more to the story of the company, you’ll need to calculate them yourself. When you calculate them, they should reach the same result as the short form. It’s when they don’t that you have to investigate the reasons why.
The article illustrates the reconciling numbers provided by a popular financial resource (Investopedia). I chose the article as it gave an example of how to reconcile the numbers. For the one example they gave, it matched completely to Morningstar’s result. But, when I checked the other companies, there were mismatches. I discuss in the article how I was able to match to Morningstar’s data, even though the numbers reported in Investopedia were wrong.
After that exercise, I thought it would be a good exercise to see how my data provider fares in coming up with the numbers. Then, it could be something I wrote about on this website. Three of the four companies that I used came up with the correct ROE numbers. The numbers for one of the years for Microsoft was incorrect. I have alerted the data provider, and they are looking into it.
Another reason to reconcile numbers is that the activity can alert you to problems. For instance, the ROE deals with several data points, both in the income statement and the balance sheet. When you reconcile to a source such as Morningstar and find the numbers are not correct, this will give you a clue as to which numbers may be wrong. The ROE is comprised of Net Income, Revenues, Total Assets for previous and current year and Total Equity for previous and current year. This will help you see which of these components are not being reported correctly.
You may need to check a few sources. Always check the annual reports on the company’s website and check the reports file on SEC.gov. Publicly-traded companies are required to register yearly reports to the SEC. Also, check Morningstar and Yahoo Finance. These numbers should all tie out.
Conclusion
Hopefully, I have given you some insight on some steps you can take when financial data you use is incorrect. It’s frustrating when you depend on data to even need to check for correctness. The whole purpose of having this data is so that you don’t have to scour through reports.
The course of action you take will depend much on how you use the data. Again, if you are frequently trading and it’s part of your business, you probably should be subscribing to a data service. These aren’t cheap, and that is the motivation for many people using free services. However, if your business depends on it, then you’ll want the comfort of knowing that your data is accurate. For casual data users and researchers, you’ll have to muddle through, unfortunately.
