5 ms·

Algorithms Had Themselves a Treasury Flash Crash

47 points by dsri 11y ago

deleted 11y ago
[deleted]
anigbrowl 11y ago
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.
- imrehg 11y ago
  Yup! I'll donate a crate of red bulls or coffee or whatever he drinks to come up with all this!
- harperlee 11y ago
  Perhaps we could do a kickstart on behalf of this cause. We should not be touting it as kindapping, though :P
msellout 11y ago
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.
- jfoutz 11y ago
  I'd sort of assumed the slower but bigger brained algorithms saw the spike and decided to start selling. They also put a floor on the bottom price (i'd guess).
- anigbrowl 11y ago
  I wonder where you would go about obtaining high resolution market data? e.g. [ticker_symbol, buyer_id, seller_id, volume, price, time[]] I'd like to find a way to visualize the algorithms, along the lines of http://content.stamen.com/visualizing_a_day_of_financial_transactions_on_nasdaq_part_2 http://content.stamen.com/visualizing_a_day_of_financial_tra... or so. I don't care about the specific securities or trader identities, I just like finding patterns in noisy data.
  - dllthomas 11y ago
    As I recall, ICE market data contains the full order book (size and identity of individual orders, not just total size at each level). Anonymized, of course. I have no idea if this is available if you're not actually trading...
- mrchicity 11y ago
  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.
gfodor 11y ago
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.
- lmm 11y ago
  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.
millstone 11y ago
> A chunk of it was high-frequency traders making money off themselves What in the world? How is that even possible? Can anyone explain?
- dllthomas 11y ago
  s/themselves/other high-frequency traders/

47 points by dsri 11y ago

deleted 11y ago

[deleted]

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.

imrehg 11y ago
Yup! I'll donate a crate of red bulls or coffee or whatever he drinks to come up with all this!
harperlee 11y ago
Perhaps we could do a kickstart on behalf of this cause. We should not be touting it as kindapping, though :P

msellout 11y ago

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.

jfoutz 11y ago
I'd sort of assumed the slower but bigger brained algorithms saw the spike and decided to start selling. They also put a floor on the bottom price (i'd guess).
anigbrowl 11y ago
I wonder where you would go about obtaining high resolution market data? e.g. [ticker_symbol, buyer_id, seller_id, volume, price, time[]] I'd like to find a way to visualize the algorithms, along the lines of http://content.stamen.com/visualizing_a_day_of_financial_transactions_on_nasdaq_part_2 http://content.stamen.com/visualizing_a_day_of_financial_tra... or so. I don't care about the specific securities or trader identities, I just like finding patterns in noisy data.
- dllthomas 11y ago
  As I recall, ICE market data contains the full order book (size and identity of individual orders, not just total size at each level). Anonymized, of course. I have no idea if this is available if you're not actually trading...
mrchicity 11y ago
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.

gfodor 11y ago

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.

lmm 11y ago
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.

millstone 11y ago

> A chunk of it was high-frequency traders making money off themselves What in the world? How is that even possible? Can anyone explain?

dllthomas 11y ago
s/themselves/other high-frequency traders/