high frequency trading
You know what’s a surprisingly not-great business? High frequency trading, for Getco anyway. A couple months back Getco signed a deal to acquire Knight Capital after one of Knight’s computers had an unfortunate couple of minutes. Yesterday Knight and Getco filed a joint S-4 containing a passel of merger details and Getco financials, and they’re sort of sad:
The sadness is really brought home by the fact that, if current trends hold, this year the average Getco employee will take home less than the average Goldman Sachs employee for the first time in modern memory. The Getco employees will still be a bit more productive, revenue-wise, though it’s getting closer: Read more »
Study Suggests High Frequency Trading Might Cost Small Investors Almost One One-Hundredth Of One Percent Of Their InvestmentsBy Matt Levine
What do you think of the big HFT study? It’s this big HFT study that CFTC chief economist Andrei Kirilenko conducted on S&P 500 e-mini futures at the CME, and it’s already inspired a metaphor from CFTC commissioner and all-purpose spinner of metaphors Bart Chilton:
Mr. Chilton said that the study would make it easier for regulators “to put forth regulations in a streamlined fashion. It’s a key step in the process and it should fuel-inject the regulatory effort going forward.”
Not his best effort, fine. Anyway, the study: I’m not sure I’ve earned the right to have an opinion, both because (1) that, generally, and (2) my model of high frequency traders as micro-mini-market-makers is a bit upended by the fact that the bulk of the HFTs in this study seem to be taking, rather than providing, liquidity.1 It’s possible that the e-mini market is not the best place to measure the overall effects of HFT, either for fundamental reasons (its use for hedging etc.) or more crassly because it lacks the liquidity rebates that drive a lot of HFT in other markets.
That said what I like about this study is that instead of measuring transaction costs in naive ways like “bid/ask spread,” it measures transaction costs in sensible ways like “in a series of zero-sum transactions, how much money do HFTs suck out in profits.” Though the measure of profitability is sort of kooky:
The profits calculated in Table 3 are the implied short-term profits: we calculate the marked-to-market profits of each trader on 1 minute frequencies2 and reset the inventory position of each trader to zero after each of these 1 minute intervals. Then, we sum up all the 1 minute interval profits to get a measure of daily profits. Therefore, we capture the short-term profits of traders and not gains and losses from longer-term holdings.
What this means is that if your model of market-making is “buy at 99.9, wait five minutes, and sell at 100.1,” then your profits might end up showing as 0.2 or -0.2 or zero or something else on that calculation.3 So regular old market making may look bad, while HFT market making – designed to move quickly – looks much better. And so you get this table: Read more »
The standard illustration of the efficient markets hypothesis is the thing about the economists and the $20 bill on the ground, but it is so old and stale at this point that Matt Yglesias had to invent a new version this week, and it’s something like “if you find a penis-enlarging injection on the ground, don’t pick it up, because if a penis-enlarging injection actually existed then Pfizer would already have picked it up, and so this one will kill you of exploding penis, QED.” You could take this advice overly literally as an argument against all human effort, and perhaps you should, but in fact someone didn’t take it literally enough, or at all, and so died of exploding penis.
“If it works someone’s getting paid for it” of course doesn’t imply the converse “if someone’s getting paid for it it works” – particularly not in the penile-enlargement field – and I suppose neither does EMH; if anything it just implies “nothing works and nobody gets paid.” Still, there is at least some weak intuitive support for the belief that if lots of sophisticated financial market participants pay for something, they’re getting some value back in return.
“Improper early access to market data, even measured in milliseconds, can in today’s markets be a real and substantial advantage that disproportionately disadvantages retail and long-term investors,” said Robert Khuzami, Director of the SEC’s Division of Enforcement. “That is why SEC rules mandate that exchanges give the public fair access to basic market data. Compliance with these rules is especially important given exchanges’ for-profit business interests”
Yesterday I and others pointed out that, while UBS was not alone in getting screwed by Nasdaq failures on Facebook, it was alone in losing 10x as much as other, more competent market makers like Knight Capital, and ha ha ha. This apparently had a jinxing effect:
Knight Capital Group Inc., one of the largest trading firms, told brokerages to send their orders elsewhere and was probing a software problem, according to people involved in the matter. U.S. exchanges said they were examining potentially erroneous trading in more than 100 securities that saw big price swings or unusually high volume. Knight saw a fifth of its own market value wiped out. …
The system error and reports of irregular trading stoked suspicions that trades had been accidentally duplicated via computer algorithms, rather than the problem being contained to one server, as has happened in the past, traders said.
Knight is down ~21%, vs. ~4% yesterday for UBS and its costly Facebook fail, a useful reminder that focusing on perfecting your market-making business may make you less likely to fuck it up, but when you do fuck it up it goes far worse for you. That’s maybe some sort of a metaphor for high-frequency electronic market-making generally, which it will not surprise you to learn is coming in for some flak today.* Algorithmic high frequency trading makes it more likely that your small trade will be executed quickly and cheaply, but it also makes it more likely that larger orders will go horribly awry as prices move away from them.
Which is why this coincidence (?) pointed out by the Journal is kind of tantalizing: Read more »
Market microstructure is a thing that I don’t really understand and that seems daunting to me so I’ll pass this along as tentatively as possible, but: I thought this piece was really good.* Again, not my area, so if you disagree just get furious at me in the comments, but I thought it might be fun to talk about it as a parable of financial regulation.
The background here is that there is a thing called high-frequency trading in which (i) people, and by “people” I mean “computers,” (ii) trade, and by “trade” I really mean more like “post bids and offers” – they trade, too, but the activity that they’re optimizing is posting bids and offers, (iii) frequently, and by “frequently” I mean “in tiny fractions of a second.” There are various worries about this thing, of which the two biggest are:
(1) computers are scary and
(2) the amount of resources devoted to this activity is staggering and probably out of proportion to its social benefit.
Worry (1) is hard to address** but maybe you’ll be a bit soothed to learn that humans can be scary too? No, I mean, fat fingering is a problem and seems to be a bigger problem with virtual fingers but let’s just bracket that and talk about worry (2). Read more »
We live in a golden age of information dissemination and stock liquidity, in which news moves faster than earthquakes and high-frequency-trading robots can trade faster than you can blink, meaning that the next time there’s an earthquake your 401k will have bought construction stocks and Twitter even before you stop shaking.
But we’re also living in a golden age of misinformation, where you can find someone to publish pretty much any rumor you want, and those rumors can move markets up or down instantly. And for some reason the robots who’ve been put in charge of markets seem to be not dispassionate calculating machines but rather touchy C-3PO types, and can exacerbate the speed and severity of crashes with their hypersensitivity. But the upside should be that the recovery from millisecond crashes should be similarly quick – once misinformation is corrected, the robots should dry their tears, blow their noses, and bid prices back up in a few more milliseconds.
SEC Is Going To Take Your High Frequency Trading Algorithm, Run It On A Commodore 64, See If It Crashes The MarketBy Matt Levine
After decades of responding to tips about fraud by writing notes on napkins and then throwing them away, the Securities and Exchange Commission finally got itself some computers and is excited to put them to use. Legitimate use. First up: figure out if maybe the computers are in fact the problem.
Read more »
Gian-Paul Caccia of Wolverine Trading, a high-frequency trading firm, won [last night's JPMorgan] corporate challenge for the second year in a row with a time of 17:05 minutes, according to the unofficial results. Emily Mareb of Bloomingdales was the fastest female racer, with a time of 21:02 minutes. [Dealbook]
Take it away, William Arnuk. Read more »
EU Joins Team US Regulators In ‘We Have No Idea What High Frequency Trading Is But We’ll Just Regulate The Hell Out Of It Anyway’ GameBy Dealbreaker
The EU is hopping on the let’s get after the-high-frequency-trading bandwagon and has started to investigate the practice. Bloomberg reports that the European commission met with industry representatives in Brussels on Jan. 11 and that the talks are part of an information-gathering exercise. In the US, the practice, which accounts for 50% to 60% of equity market trading volumes, has been under fire in the past months as regulators are calling for more stringent oversight.