Nanex: Investors Need To Realize The Machines Have Taken Over

 

In the blink of an eye, the market moves what used to take humans thirty minutes

High Frequency Trading (HFT) deeply concerns Erik Hunsader, founder of Nanex. He worries that today’s investors, our regulators, — heck, even the HFT algorithms themselves — don’t fully understand the risks market prices face in the brave new era of bot-dominated trading.

For instance, Hunsader estimates that HFT algorithms are responsible for 70%(!) of all completed transactions on our exchanges, and for 99.9%(!!!) of all exchange quotes.

The pictures of trading floors you see on TV, where the people in bright jackets appear frantically busy in making their trades, have no bearing — claims Hunsader — on the actual trading action. The real action happens across fiber-optic cables, on racks of servers in cooled rooms; where an arms race defined by cable length and switching speeds is being waged

The reality is that the machines have taken over. When you buy or sell a security, the odds are extremely high the other side of the trade is being placed by an algorithm — one that cares nothing for the fundamentals of the underlying instrument. It simply is looking to make a quick profit, oftentimes measured in fractions of pennies. And this has vast repercussions for the stability and the fairness of our financial markets.

Because of speed advantages, HFT algos can see and react to prices faster than you can. Ridiculously faster. A second on the clock, to an HFT algo, is an eternity.

The deep pockets of the firms emplying HFT algos combine with this speed to move asset prices around, sometimes wildly so, faster than most of us can comprehend. In the time it takes for your “real-time” quote system to refresh, an individual stock could have traded many percetages up and/or down — and you would have no idea.

This unfair advantage, along with the short-term profit outlook of the algos, creates the potential for deadly market price downdrafts. Algorithms prefer predictability. If something spooks them (e.g., unexpected breaking news, a delay in the market’s opening), they simply stop trading. And — poof! — 70% of the market has just disappeared. With no support and no bids, prices can drop dizzyingly fast. Making matters worse, the “smarter” algos can recognize a downdraft in process, and begin piling back into the market on the short side, exacerbating the price declines.

The Facebook IPO provides a recent example of the vulnerability of our system:

 

 

Erik Hunsader: If we get one bad, unsuspected news event I guarantee you it will be lights out very quick. One of the things these algorithms do is they make sure the input is good. And whenever the input isn’t quite good they back off. When I say back off I mean they back off in the blink of an eye. So it can go from good to very bad that quickly. And all it’s going to take is some unforeseen news event and they won’t be there. And then we’ll see what the liquidity is.

 

Chris Martenson: So do you see this on a daily basis or some frequency where you see volumes or liquidity just suddenly dry up in the market?

 

Erik Hunsader: Yes.

 

For example on the Facebook IPO day, NASDAQ was trying to open the IPO up. By their third attempt, they’re telling everybody “Wait, we’ll get it at 11:05. No, we’ll get it at 11:10. No we’ll get it at 11:30″. So it was do-or-die time, 11:29:50 comes around. Somebody there has the bright idea to just reboot the system. It takes NASDAQ offline a full seventeen seconds. Nothing coming out of NASDAQ. Not a peep in any stock, market wide, for seventeen seconds. When NASDAQ finally did reappear — what happened? The orders that were resting in the book all that time immediately disappeared. Like 60%-70% of all liquidity within 200 milliseconds was gone: SPY, Microsoft, Apple. Not just Facebook — it was every stock. We were extremely vulnerable over, I would say, that fifteen to thirty minutes to any sudden external shock. And we usually get away with it but one day we’re not going to get away with it.

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