Having been a professional investor, it’s hard not to be amused by all the excitement around alternative data, quantitative and factor based investing. They are often cited as radical new technologies that will change the future of investing. Admittedly, at Quantavista Research we contribute to this perspective. But, I’d like to share some inconvenient truths. As they say, what’s old becomes new again. Quantitative investing has been around for decades. Fama and French wrote the first paper that’s very similar to today’s factor investing in 1992. Arguably what’s changed the most is not the innovation, but rather the widespread adoption of these concepts.
I’m far from negative on these topics, but I wanted to add balance to the seemingly one sided conversation of these capabilities as investing nirvana. Here are a few observations:
Truth #1: Mainstream Business Media Gets Paid to be Terrible Market Forecasters. PERIOD. Their job is to sell papers/magazines/pageviews/subscriptions, not to make investment recommendations. The editors of the WSJ, FT, Barron’s, CNBC know exactly what they’re doing. People like to buy/read/watch media about topics and subjects they like and already know something about. Mix these two and you realize that editors WANT every front page headline to be the market consensus or only just shy of it. So, when the WSJ dedicates a week of articles in May 2017 to quant investing that helps you gauge where the consensus is at.
Truth #2: The Best Businesses in the World Get Better With Size and Have a Network Effect. But, Selling Alternative Data Faces Challenges With Growth. Selling alternative data is a tough standalone business and I commend the companies like EagleAlpha, 1010Data and Earnest Research that do it well. They mainly sell to 40–50 highly sophisticated quant funds that are power users. Each dataset is essentially a decaying asset that has the most value at the beginning when investors are skeptical or don’t believe the signal and not willing to pay a lot. But, when more investors realize the usefulness of the signal either: A) increased competition drives down pricing and/or B) the original data source provider wants a larger % of revenue. Thus, the business model of an Alternative Data & Service Provider is to: A) acquire novel, cheap, high quality datasets faster than peers before they become commoditized, B) sell as many product & services to customers as possible C) and scare/attract new customers to seeing the product benefits. This actually seems a lot like a branded pharma business and would seem to benefit from scale, with one key problem:
How useful is alternative data if everyone has it? How popular can alternative data be before its considered fundamental?
The other things to think about with alternative data are that the market prices in information very quickly and the window to deploy alt data insights is likely only a few weeks between earnings releases.
Truth #3: These Types of Businesses Actually Have Relatively Small and Declining Barriers to Entry. Quantitative analysis, factor investing and alternative data are all digital businesses that you can literally start overnight. Constantly improving open source software is making digital businesses ridiculously easy nowadays. Anyone can scrape this webpage in about 3 lines of Python code, which can be written in about the time it takes you to finish this sentence.
BTW, want to know the secret formula for success in factor investing?…. Ready? …. A multi-factor model using Value, Momentum and Quality. Buy cheap stocks of good companies that are starting to work. Shh… Now run along and don’t tell anyone. Yes, it actually has worked over time, the future’s unclear though. I’m still surprised that there are entire businesses built around factor investing.
Rule #1 of capitalism: Capital and competition kills high returns unless there’s a barrier to entry. Of course it’s not that simple, but this does put a ceiling on how profitable these types of businesses can be. Hence, the only real point of differentiation and competitive advantage will come from scale, similar again to the pharma and digital media industries. Which leads to my final conclusion….
Truth #4: Within a Decade Almost All of The Small Companies in the Space Will Either Be Acquired or Shutdown With Few If Any Standalone Survivors. The real truth is that these are all useful capabilities, but are also all inherently digital products with economies of scale for customer acquisition and engineering. For the time being, a lot of young companies, including Quantavista, in this space are innovating and succeeding because the larger companies lack the innovation, know how or focus in the area. But, the big guys are coming. In the end, the larger companies’ advantages of scale along with their desire for growth and capabilities will drive smaller players to either: A) get acquired or B) shutdown within a decade. If you want to see what this looks like, just look at the digital media space and the staggering number of acquisitions made by Google, Facebook, Microsoft and even Yahoo over the last decade.
The alt data providers will likely be bought by the fundamental data giants: Bloomberg, Thompson Reuters and S&P Capital IQ.
Quantitative and quantamental application companies will eventually be acquired by: either the fundamental data giants, but more likely the hedge funds and asset managers that want to desperately improve performance.
I’m skeptical that there’s much real innovation in factors that the large companies can’t do themselves. But, the ones that are truly innovating will likely be bought by the ETF firms: Blackrock, Statestreet and Vanguard.
One More Thing
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Okay. One Last Thing
This is the first article that is part of the Quantavista Quantmental, our new publication dedicated to quantamental analysis, alt data and the future of investing. Please let me know if you’d like to be a writer or sign up to subscribe to updates.
On a random note, have you noticed how many financial startup website and blog posts (ours included) have pictures of the Manhattan skyline? I had to switch it up this time. Who doesn’t love kids?