

Algorithms Had Themselves a Treasury Flash Crash - dsri
http://www.bloombergview.com/articles/2015-07-13/algorithms-had-themselves-a-treasury-flash-crash?repost

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msellout
This is simply the new normal as too many small-brain (and thus fast)
algorithms are crowded into the same strategy space. Periodically, they will
all randomly converge on the same strategy, liquidity dries up, and the prices
jump dramatically.

The fix is to add a delay in all public stock markets between order placement
and execution. This could be done either through a fixed lower speed limit,
through specifying a human-scale atomic time quanta, or adding a tax inversely
proportional to the duration between consecutive trades from the same agent --
a tax on simplicity.

Increasing the time-scale of the market will increase the sophistication of
the algorithms, as they no longer need to fight to be winner-take-all fast.
Bigger-brained algorithms mean the strategy space is larger and convergence is
less likely. Thus, no more flash crashes.

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mrchicity
I don't think that's the case at all. Consider Levine's point about self-
trading. Even algorithms developed within the same company have such different
views that one believes the price will hold steady or revert and expresses
this view by sitting on the offer while another is so confident that it will
move that it's willing to lift that offer.

Just looking at ultra-low latency algos in liquid products like treasuries you
have a lot of diversity: market-makers, yield curve spreaders, cash/future/ETF
arbitrageurs, statistical signal trading, along with combinations of all of
those. All of these players need to be fast but have vastly different risk
profiles and trading style.

If you made trading more expensive or slower, traders doing useful things like
making quotes or keeping the cash and futures markets in line would be driven
out, making the markets less efficient. I'm less sure about the value that
high-speed momentum strategies provide. If they're right, they move prices to
be more efficient more quickly, but they can also negatively impact liquidity
providers and make prices inefficient if they're wrong. I figure the market
will sort that out though. Nobody can run a money-losing algo indefinitely.

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msellout
You're correct that without low-latency trading, markets will be less
efficient in that bid-ask spreads will increase. However, I think of that
efficiency as an architect optimizing a skyscraper's earthquake tolerance.
Sure, on a regular day we want to save money, but a prudent person will
"waste" on redundant systems and excessive tolerances.

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anigbrowl
_On Monday, U.S. regulators released a long shrug of a report_

Someone kidnap Levine and force him to produce book-length work. I will gladly
donate an attic and snarling canines to bar his exit.

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imrehg
Yup! I'll donate a crate of red bulls or coffee or whatever he drinks to come
up with all this!

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gfodor
I think another dynamic to be nervous about here is the fact that when humans
see the US treasury market flash, they probably jump to conclusions. A big buy
move on the treasury market that says "risk-off" would tell me some serious
shit just happened and hasn't hit the news wires yet. If the algos don't
correct themselves quickly enough, a crisis could actually materialize out of
the reactions humans make under the assumption that the market is pricing in a
real event.

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lmm
It's self-correcting though - those who misprice stuff pay for their mistakes.
Ultimately as Levine says it's just another bubble - something humans are
already very good at making for themselves. The algorithms just do it faster.

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millstone
> A chunk of it was high-frequency traders making money off themselves

What in the world? How is that even possible? Can anyone explain?

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dllthomas
s/themselves/other high-frequency traders/

