[FoRK] This is What Wall Street's Terrifying Robot Invasion Looks Like

Eugen Leitl eugen at leitl.org
Wed Aug 8 03:27:13 PDT 2012


This is What Wall Street's Terrifying Robot Invasion Looks Like

Posted by Alec_Liu on Tuesday, Aug 07, 2012

Given the the endless mind-whirling acronyms, derivatives and structures of
the financial markets, we’re rarely served with a visualization that so
elegantly illustrates the arrival of Wall Street’s latest innovation. This is
what High Frequency Trading — the official monicker of Wall Street’s robot
army — looks like, when specially programmed computers make massive bets at
lightning speed. Created by Nanex, the GIF charts the rise of HFT trading
volumes across all US stock exchanges between 2007 and 2012. The initial
murmur, the brewing storm, the final detonation: Not just unsettling, it’s

The majority of all trades made everyday are now executed by robots looking
to exploit micro-movements in stock price in a perpetual game of musical
chairs. The finance industry insists that this is a net-positive operation.
The established argument is that, by increasing liquidity and reducing price
spreads, everyone benefits from price stability and lower transaction costs.

This may be true, but there are side effects, as one HFT insider explained to
Zero Hedge:

    HFT affects all investors to an extent, because stocks are now priced
differently than in the past. The market used to consist mostly of investors
analyzing cash flows and balance sheets, trying to calculate a company’s fair
value. HFTs, on the other hand, react to movements in stock prices alone.
That is not necessarily a bad thing, but since HFTs are responsible for
two-thirds of the trading volume, we have the strange situation where they
can set the price based on what they perceive others’ perceptions to be.

We also don’t know is what the long term consequences are of all this
hyper-volume as depicted by the Nanex GIF and the kind of systemic risks
created from the market’s ongoing evolution from human traders to rapidfire
AI. Sometimes things go wrong, a software glitch, an algorithm gone rogue and
the music stops, like last week when Knight Capital lost $10 million a minute
when it’s trading platform went haywire or during the infamous Flash Crash
when the Dow dropped 1000 points in mere minutes.

These incidents have so far been contained with minimal collateral damage.
But that may not always be the case. More likely, these are ominous signs of
what’s to come, potential warnings we are failing to heed, as we did in
recent past with the destructive concoction of leverage and complex
off-balance sheet derivatives that led to the crash of 2008.

In the 90s, the finance industry was heavily marketing its mathematical risk
models devised by rocket scientist quants. These new formulas were foolproof,
they insisted, reducing risk while making people richer for it. One hedge
fund, Long Term Capital Management, was the obvious star, pushing these
models to the limit and claimed board members like Myron Scholes and Robert
C. Merton, who shared the 1997 Nobel Memorial Prize in Economic Sciences.
These guys were certified geniuses. In just three years, the fund quadrupled
investor returns. Then in 1998, the machine broke.

When it crashed, LTCM had $4.72 billion with a further $124.5 billion
borrowed but thanks to off balance derivatives, the fund had a notional value
of approximately $1.25 trillion. If LTCM were to go down, it would send
catastrophic losses rippling through the global system. The fund was
officially too big to fail. Forced into action, the Fed swooped in with a
consortium of banks producing a bailout worth $3.62 billion. In its
aftermath, the tune shifted. Merrill Lynch observed that mathematical risk
models “may provide a greater sense of security than warranted; therefore,
reliance on these models should be limited.”

Instead of changing the music, then Fed Chairman Alan Greenspan dismissed the
blowup as a one-off. Ten years later, encumbered by the same kind of massive
leverage and a web of convoluted derivatives, the markets, held hostage by
too-big-to-fail banks, finally imploded leaving in its wake an economic
disaster the world has yet to fully shake off.

It’s possible that these robot-traders, the ones that have turned the markets
into their battleground for pennies could be totally innocuous. Yet if
something were to go wrong — some bug or mutated AI gone awry, big enough to
create a feedback loop that cascades through the system — it would happen in
the blink of an eye. By then, for the humans at least, it would already be
too late.

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