4 ms·

I don't know anybody that uses anything as weak as 2-sigma results in HFT, at least. Most of our valid signals have 20-50+ sigma.

by consz 12y ago

gojah 12y ago
20+ sigma is mostly kidding yourself about assumptions. That said, the 2-sigma tests are for client-facing algos, where the goal isn't to build wealth for the client, it's to generate fees.
- consz 12y ago
  Agreed, errors are non-normal so 20+ sigma is practically false. But it's not too far off -- I've seen strategies that never have a down day and have daily sharpes of 2.5-3.0, and those setups will generally have incredibly high sigma values even after accounting for non-normality (and other assumptions).
  - joosters 12y ago
    Remember, strategies that 'never have a down day' are only one day away from having a down day... ...and there are plenty of strategies that had only a single down day, unfortunately that one down day wiping out the entire company :)
    - consz 12y ago
      Sure, but most strategies have such small positions that even if the market went to 0 instantly at your maximum long position, you'd still lose less than a year's worth of PNL in that strategy. The more relevant risk of blowout is something like Knight happening, statistical black swan events are not really an issue (in HFT).
    - stevewepay 12y ago
      I used to be very big into algorithmic and day trading, and one trader I was introduced to had Martingale'd himself into a record of something like 2 years without suffering a loss. Then he suffered a 300k loss and wiped out all of his earning plus more and then he lost a lot of his followers, at least for a while.
  - deleted 12y ago
    [deleted]
gmunu 12y ago
It doesn't look like the article is not about HFT in particular or even trading professionals in general. It's about academic articles, where the incentive is to publish a paper, not to make money. I recall (but cannot find) a paper that looked at the sort of strategies published by academics. Younger, non-tenured professors sometimes published results that were actually interesting, because they needed to get a job and built a reputation. Older professors don't do that. If they find an effect that's real, they take it to a hedge fund. There isn't too much incentive to publish a paper about something that will really make you money.
jeffreyrogers 12y ago
Since you seem pretty well acquainted with HFT, I'm curious about how much of a constraint capacity is? From what I understand the amount earned per trade is very small (this paper[1] suggests $1.45 per $10,000 traded). And since HFT is already a large fraction of the daily volume it seems that the natural way to increase profit (i.e. just trade more) isn't an option in most cases. [1]: http://faculty.haas.berkeley.edu/hender/hft-pd.pdf http://faculty.haas.berkeley.edu/hender/hft-pd.pdf
- consz 12y ago
  $1.45 per 10k traded seems really high. A good S&P futures strategy (one of the biggest products in the world) is typically going to make 60-80 cents per contract traded. Since each contract is approximately 100k, thats closer to .06-.08 cents per $10k traded? Even for equities (I don't touch US equities, so I'm not entirely sure how good the best strategies perform), making a full price tick per contract is still < $1earned/$10k traded... and good HFT strategies are more on the order of 5-10% of a tick per contract traded. In any case, capacity is probably the first constraint you hit. Most firms have reasonably accurate simulations, so most HFT strategies are scaled up to as large as they can possibly trade (ie. quote the largest amount passively or aggress with the largest amount you possibly can) within a few days of being released -- once you can confirm that your live trading is at least mostly matching simulation, you usually try to simulate the maximum possible size it can trade and just start live trading that. Since you're typically scalping a tick at a time, your maximum size is typically some fraction of the zero level bid/offer -- relatively small. Typically the way you scale up is either have better execution (know when to size up/size down appropriately) or better prediction quality -- since you're adversely selected, your bad trades get filled at a much higher percentage than your good trades, so as your have better prediction quality, a smaller percentage of your volume is bad and you can start to fire larger and larger.
  - jeffreyrogers 12y ago
    Thanks, that's really interesting. I hadn't even thought of the adverse selection problem. And you're right the $1.45 was high. I looked at the paper again and that number was before adding in costs. With trading costs the number was much lower, but still profitable (can't remember the exact number off the top of my head), and that paper was just US equities.
seeingfurther 12y ago
One of the largest quant funds out there... http://www.twosigma.com/ http://www.twosigma.com/

I don't know anybody that uses anything as weak as 2-sigma results in HFT, at least. Most of our valid signals have 20-50+ sigma.

by consz 12y ago

I don't know anybody that uses anything as weak as 2-sigma results in HFT, at least. Most of our valid signals have 20-50+ sigma.

gojah 12y ago

20+ sigma is mostly kidding yourself about assumptions. That said, the 2-sigma tests are for client-facing algos, where the goal isn't to build wealth for the client, it's to generate fees.

consz 12y ago
Agreed, errors are non-normal so 20+ sigma is practically false. But it's not too far off -- I've seen strategies that never have a down day and have daily sharpes of 2.5-3.0, and those setups will generally have incredibly high sigma values even after accounting for non-normality (and other assumptions).
- joosters 12y ago
  Remember, strategies that 'never have a down day' are only one day away from having a down day... ...and there are plenty of strategies that had only a single down day, unfortunately that one down day wiping out the entire company :)
  - consz 12y ago
    Sure, but most strategies have such small positions that even if the market went to 0 instantly at your maximum long position, you'd still lose less than a year's worth of PNL in that strategy. The more relevant risk of blowout is something like Knight happening, statistical black swan events are not really an issue (in HFT).
  - stevewepay 12y ago
    I used to be very big into algorithmic and day trading, and one trader I was introduced to had Martingale'd himself into a record of something like 2 years without suffering a loss. Then he suffered a 300k loss and wiped out all of his earning plus more and then he lost a lot of his followers, at least for a while.
- deleted 12y ago
  [deleted]

gmunu 12y ago

It doesn't look like the article is not about HFT in particular or even trading professionals in general. It's about academic articles, where the incentive is to publish a paper, not to make money. I recall (but cannot find) a paper that looked at the sort of strategies published by academics. Younger, non-tenured professors sometimes published results that were actually interesting, because they needed to get a job and built a reputation. Older professors don't do that. If they find an effect that's real, they take it to a hedge fund. There isn't too much incentive to publish a paper about something that will really make you money.

jeffreyrogers 12y ago

Since you seem pretty well acquainted with HFT, I'm curious about how much of a constraint capacity is? From what I understand the amount earned per trade is very small (this paper[1] suggests $1.45 per $10,000 traded). And since HFT is already a large fraction of the daily volume it seems that the natural way to increase profit (i.e. just trade more) isn't an option in most cases. [1]: http://faculty.haas.berkeley.edu/hender/hft-pd.pdf http://faculty.haas.berkeley.edu/hender/hft-pd.pdf

consz 12y ago
$1.45 per 10k traded seems really high. A good S&P futures strategy (one of the biggest products in the world) is typically going to make 60-80 cents per contract traded. Since each contract is approximately 100k, thats closer to .06-.08 cents per $10k traded? Even for equities (I don't touch US equities, so I'm not entirely sure how good the best strategies perform), making a full price tick per contract is still < $1earned/$10k traded... and good HFT strategies are more on the order of 5-10% of a tick per contract traded. In any case, capacity is probably the first constraint you hit. Most firms have reasonably accurate simulations, so most HFT strategies are scaled up to as large as they can possibly trade (ie. quote the largest amount passively or aggress with the largest amount you possibly can) within a few days of being released -- once you can confirm that your live trading is at least mostly matching simulation, you usually try to simulate the maximum possible size it can trade and just start live trading that. Since you're typically scalping a tick at a time, your maximum size is typically some fraction of the zero level bid/offer -- relatively small. Typically the way you scale up is either have better execution (know when to size up/size down appropriately) or better prediction quality -- since you're adversely selected, your bad trades get filled at a much higher percentage than your good trades, so as your have better prediction quality, a smaller percentage of your volume is bad and you can start to fire larger and larger.
- jeffreyrogers 12y ago
  Thanks, that's really interesting. I hadn't even thought of the adverse selection problem. And you're right the $1.45 was high. I looked at the paper again and that number was before adding in costs. With trading costs the number was much lower, but still profitable (can't remember the exact number off the top of my head), and that paper was just US equities.

seeingfurther 12y ago

One of the largest quant funds out there... http://www.twosigma.com/ http://www.twosigma.com/