XBRL creates a new equities research value chain & democratizes the stock market

Democratized data

This is Part 2 of a 2 Part Research Note, where we look at how XBRL could enable a new equities research value chainIn Part 1, on Wednesday, our Research Note described how regulation and market pressure is forcing transparency on equities research and how that is leading to cost pressures. Our thesis is that the only way out is to reduce cost via automation and that is where XBRL is ready for its prime time. A new breed of micro research firms will enter the market opened up by regulation and empowered by XBRL. They will start by solving a huge pain point in small cap equities research. There are investing bargains to be had in small cap. On the other side of the table the small cap companies have been neglected; they are in “small cap hell” and want to be discovered by investors. New value chains will form around new business models that use XBRL automation.  

XBRL 101

  • XBRL stands for eXtensible Business Reporting Language.
  • It is an open standard based on XML, created by an accountant named Charlie Hoffman.
  • If you tag content consistently, software applications can more easily analyze the data and present more useful information. Think of XBRL like a barcode on financial statements. Yes, that sounds like the Semantic Web, and we all know that the Semantic Web has faced the chicken-and-egg problem (i.e. not enough content is semantically tagged yet and so developers don’t create tools to parse the semantic data). Imagine a Semantic Web standard where governments around the world tell companies that they must tag data that way. That is XBRL
  • XBRL gained attention when the SEC in the US in 2009, mandated that public companies report their financial results in XBRL.
  • The SEC XBRL mandate motivated almost every major market around the world to follow suite.
  • XBRL is being used across almost every asset class. In this post we focus only on equities.

For more research, go to XBRL.org

It was this superb article in Wired called Radical Transparency in the dark days of February 2009 in the thick of the Global Financial Crisis that first got me excited about XBRL.

Two reasons why XBRL will move to prime time in 2016

  • # 1: High Frequency Trading killed the Day-Trading business. When speed of trading is the game, computers will always beat humans. When you work on small gains every day, the front running done by HFT hurts. So there are a lot of retail investors looking to find the next game, looking for new ways to make money in the stock market. The winners in the market will now be stock-pickers who can go either Long or Short based on fundamental analysis.
  • #2: The XBRL rollout on US stocks is now complete. So we can move from the production phase of XBRL (all costs, no benefits) to the analysis phase (lots of benefits, very low costs).

XBRL is one of our Top 10 Fintech Predictions for 2016:

“XBRL will start climbing out of the slough of despond but won’t be recognized yet as moving into the plateau of productivity.”

Three reasons why XBRL fell into the slough of despond

It has been 7 years since XBRL was mandated by the SEC and got public attention. That is too long in our attention deficit world. We see the same thing with something as complex as Bitcoin, which is also about 7 years old, that is losing attention because the results have not been quick enough. There are also three reasons specific to XBRL why it fell into the slough of despond:

  • # 1: XBRL is a complex story that requires an understanding of both technology and accounting.
  • #2: The XBRL production process took longer, cost more and was more error-prone than forecast. In the production phase it was all costs and no benefits. It was all problems and no results.
  • # 3. There have not yet been any success stories for journalists to write about.

Why you will continue to hear these negative stories

XBRL democratizes fundamental stock analysis in the same way that PCs democratized computing and social media democratized HTML.

When you can compare the cash holdings across 100 companies with a single entry in your spreadsheet, or see quarter to quarter revenue growth for every company in the index that you devised, do you need mega brokers and their me too reports churned out by freshly minted MBA graduates in an outsourcing center somewhere?

That is disruptive to the current financial value chain (aka Wall Street). Those threatened by disruption always point out the flaws in a new technology and in all new technology there are plenty of flaws (XBRL is no exception).

When you see issues with XBRL, remember how klunky the Internet was in 1994 (cue sound of a screeching dial up modem). When something promises to automate a task 100% and only achieves 90%, it is easy to point out the flaws that meant 100% was not achievable. The reality shouting at us is that 90% automation is game-changing. The firms who mastered the business of deploying people to do things manually (i.e the threatened incumbents) have the money and the motivation to convince you that this will never work.

Those who have been toiling in the XBRL world know that the data is still not totally reliable. So, they will be defensive when they hear the incumbents talk about all the problems with XBRL. True there are problems with XBRL, but it is still way better than what we have now (manually cutting and pasting from HTML into Excel). To the retail investor, finding a data problem is an opportunity. They have the time. If you use XBRL to screen 100 stocks based on some parameter and end up with 3 that “look interesting”, you can easily eyeball those 3 on your short-list to spot where the data errors might be or why a stock that looks crazily undervalued based only on the numbers is still a lousy stock to buy. Automated analysis of the basics enables more time for value added analysis (“Alpha” in Hedge Fund speak).

New technology usually gets a foothold in a market that has major pain where the market participants will over look something klunky because the need is so great. This leads us to looking at the “small cap hell” pain point.

Getting out of “small cap hell”

When I was writing the SAAS Insights Report in 2010, only Big Caps (over $2bn market cap) had to report in XBRL. Now I can get all the SAAS stocks in XBRL; or I can get all Biotech, Oil, Property, e-commerce stocks, financials/Fintech. I can get whatever is the focus of my research. Then I can set up automated screening programs to find the investing gems (long or short) in those markets. Those screens are not just based on something as crude as price or PE or PSR. They are based on data that you can only get by digging deep into the 10Q statements and – this is what matters – knowing what you are looking for because you understand the market that you are researching.

Today, Small Cap stocks are in “Small Cap Hell”. When your market cap is below $2bn, mutual funds cannot buy your stock unless the Fund is specifically mandated to buy Small Cap Stocks.

It is worse than that. Since ETF trading took off, fundamental research declined even more. About 75% of stocks now have no research. Only Mega Caps or recent IPOs get research on a consistent basis.

When everything changes, one law that remains constant is the law of supply and demand. When all of the research supply goes to a few stocks and the demand is screaming from the rest, there is a window of opportunity.

So, XBRL needs stories of a couple of geeky young Warren Buffet like investors to make a fortune this way. That will get them onto CNBC or Fortune or Business Insider. A good reporter with a nose for the story will ask “how did you do it?” and that is where the newly-rich investors will go against their best interests and reveal that XBRL analysis tool they used.

Investors win in inefficient markets. Small Cap is an inefficient market. Here is a report from Credit Suisse that shows why trading in Big Caps is a mugs game for retail investors, but how there are big opportunities if you can quickly find the undervalued/overvalued small cap stocks. The TL:DR summary of that Credit Suisse report:

“Shares in small and mid cap companies are, for the most part, less liquid than those of large caps. The typically higher risk of an investment in small and mid cap stocks is reflected in higher risk and liquidity premiums and has a positive effect on performance over time.”

In other words, Small Cap stocks are ideal hunting ground for individual retail investors. With the small sums they trade, the lack of liquidity is less of an issue.

Qui Bono and Qui Amisit?

Translation – who wins and who loses?

  • Private Equity Funds – lose a bit. They are currently doing very well in an inefficient market. They can afford to have analysts screen for small cap value and take them private. As other investors figure out how to do this – meaning the market becomes efficient and small cap bargains go up in price – the easy arbitrage will be gone. PE funds have many other ways to make money; this is just some easy-pickings that will go.
  • Small Cap Funds – gain a bit. Their existing holdings will go up in value. They will have to work harder to find bargains in future but as that is what they do for a living, they will figure out how to add value in the new value chain.
  • Me Too Research – lose a lot. Investors will demand a lot more value and insight. Me Too Research, even with lots of fancy charts and visualization, will be downgraded.
  • New investing services – gain a lot. There is room for a new Yahoo Finance (free, ad supported) or a new Bloomberg or a new (pick your favorite subscription based service). This is a high risk/high reward game that is subject of a future Daily Fintech Research Note. The winners will be distribution channels for the Micro Research Firms (see below).
  • Micro Research Firms – gain a lot. This will be like the blogging revolution. Suddenly everybody can be a research firm. All you need is insight; the mechanical part is automated. I call this latent alpha. For example, somebody with decades of experience as an oil geologist might have valuable insight into the oil business, but lacked any way to monetize that insight.
  • Jane Q Public – gain the most. Some will become Micro Research Firms. Most will simply invest smarter. This is how the stock market was supposed to work. This will be a democratized stock market that will help to reduce inequality. Wall Street is based on information asymmetry. It is like a car dealer with all the data. That era is coming to an end.

Daily Fintech Advisers provide strategic consulting to organizations with business and investment interests in Fintech. Bernard Lunn is a Fintech thought-leader.

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