Algorithmic trading is Wall Street’s last best hope.
So said the lead sentence in a story called Algo Wars in the May 30, 2005 edition of Investment Dealer’s Digest. That publication is gone and so is Lehman Brothers, co-leader of program-trading at the NYSE in May 2005, and computers were then rapidly displacing humans in driving it.
Algorithms, computerized mathematical models for trading, are ubiquitous now not just in equities but across a spectrum of electronically traded securities ranging from currencies and options to futures and US Treasuries.
History illuminates origins. It’s the reason to be a student of it, paraphrasing the Spanish philosopher called George Santayana (his actual name is a lot longer), who made the cover of Time Magazine in 1936 and observed that those who cannot remember the past are condemned to repeat it.
Algorithms, the article says, were birthed by “market developments and regulations that made trading equities more complicated and less profitable.” It quotes Sang Lee, founder of then brand-new market consultancy Aite Group, now a thought leader on market structure, saying algorithms “emerged from this hostile institutional trading environment where it’s getting increasingly difficult to move large blocks of orders.”
That was ten years ago. I had started ModernIR a few months earlier. Josh Friedlander, author of Algo Wars, wrote near the beginning that “because the democratization of algorithmic trading has just begun, its impact on the corporate world is still uncertain,” referring to ambiguity about how algorithms would affect stocks of companies.
Friedlander also wondered if small-caps, victimized then by decimalization and a regulatory separation of research and trading, would suffer further. The JOBS Act, made law in 2012, made it easier for small firms to go public but didn’t address structural woes for small stocks. Today analyst coverage is a Rorschach blot on the biggest 750 firms, leaving 3,000 largely in uncovered white space. And the buyside and sellside have spent billions on technologies for hiding trades in a complex market.
Exchange Traded Funds (ETFs) grew out of this milieu. Moving big orders was a problem a decade ago. Now look at it. We have Blackrock and Vanguard with $8 trillion of assets and a stock market with $24 trillion of capitalization. ETFs are the next evolution for a market built on rules meant to fuel movement but which paradoxically paralyze it.
I looked up one of our small-cap clients with about $1 billion of market cap and compared it to one with $10 billion. The small-cap was in 58 ETFs, 15% more than the $10 billion stock, and short volumes for it are in the highest 20% marketwide. It’s not that ETFs are focused on small-caps. Our typical large-cap client with $25 billion or more of market-cap is in about 100 ETFs. Borrowing and derivatives predominate.
What should be obvious from the IR chair upon retrospection is how little faith one can have in what’s observable on the surface of price and volume. ETFs move positions relentlessly and without respect to news save for reactions to prices and direction where applicable. Algorithms proliferating for a decade are designed to hide intention.
If as an institutional seller you wanted to obscure your disbursements, would you employ algorithms that pressured prices? Selling would be patently obvious and the billions spent on sleights of hand wasted. Clients, you know we routinely observe contrarian patterns in the data – Positive sentiment signaling impending pressure, Negative sentiment a bottom and probable buying.
Let me summarize. The obvious lesson of history here is that a decade of profound stock-market transformation coupled with leviathan investment from its core participants in purpose-obfuscating trading technologies will not produce a market where you look at your price and volume and say, “I think we have a big seller.”
Every now and then that might be right. But 90% of the time what seems to be apparent is probably not what’s occurring. Thus ModernIR thrives today and we can help anybody regardless of size or trading volume observe reality under the market’s skin.
