Results for “hft”
38 found

A study of limiting HFT

From Philip Delves Broughton:

These advantages were demonstrated in a recent natural experiment set off by Canada’s stock market regulators. In April 2012 they limited the activity of high-frequency traders by increasing the fees on market messages sent by all broker-dealers, such as trades, order submissions and cancellations. This affected high-frequency traders the most, since they issue many more messages than other traders.

The effect, as measured by a group of Canadian academics, was swift and startling. The number of messages sent to the Toronto Stock Exchange dropped by 30 percent, and the bid-ask spread rose by 9 percent, an indicator of lower liquidity and higher transaction costs.

But the effects were not evenly distributed among investors. Retail investors, who tend to place more limit orders — i.e., orders to buy or sell stocks at fixed prices — experienced lower intraday returns. Institutional investors, who placed more market orders, buying and selling at whatever the market price happened to be, did better. In other words, the less high-frequency trading, the worse the small investors did.

…In a paper published last year, Terry Hendershott of Berkeley, Jonathan Brogaard of the University of Washington and Ryan Riordan of the University of Ontario Institute of Technology concluded that, “Over all, HFTs facilitate price efficiency by trading in the direction of permanent price changes and in the opposite direction of transitory price errors, both on average and on the highest volatility days.”

The pdf of the paper is here.  Here is the conclusion of a Charles M. Jones survey paper on HFT (pdf):

Based on the vast majority of the empirical work to date, HFT and automated, competing markets improve market liquidity, reduce trading costs, and make stock prices more efficient. Better liquidity lowers the cost of equity capital for firms, which is an important positive for the real economy. Minor regulatory tweaks may be in order, but those formulating policy should be especially careful not to reverse the liquidity improvements of thelast twenty years.
There are a variety of significant problems on Wall Street, but this really isn’t one of them.

Matt Levine and Felix Salmon on Michael Lewis and HFT

In my alternative Michael Lewis story, the smart young whippersnappers build high-frequency trading firms that undercut big banks’ gut-instinct-driven market making with tighter spreads and cheaper trading costs. Big HFTs like Knight/Getco and Virtu trade vast volumes of stock while still taking in much less money than the traditional market makers: $688 million and $623 million in 2013 market-making revenue, respectively, for Knight and Virtu, versus $2.6 billion in equities revenue for Goldman Sachs and $4.8 billion forJ.P. Morgan. Even RBC made 594 million Canadian dollars trading equities last year. The high-frequency traders make money more consistently than the old-school traders, but they also make less of it.

There is more here.  Here is Felix Salmon on the book:

Similarly, Lewis goes to great lengths to elide the distinction between small investors and big investors. As a rule, small investors are helped by HFT: they get filled immediately, at NBBO. (NBBO is National Best Bid/Offer: basically, the very best price in the market.) It’s big investors who get hurt by HFT: because they need more stock than is immediately available, the algobots can try to front-run their trades. But Lewis plays the “all investors are small investors” card: if a hedge fund is running money on behalf of a pension fund, and the pension fund is looking after the money of middle-class individuals, then, mutatis mutandis, the hedge fund is basically just the little guy. Which is how David Einhorn ended up appearing on 60 Minutes playing the part of the put-upon small investor. Ha!

Lewis is also cavalier in his declaration that intermediation has never been as profitable as it is today, in the hands of HFT shops. He does say that the entire history of Wall Street is one of scandals, “linked together trunk to tail like circus elephants”, and nearly always involving front-running of some description. And he also mentions that while you used to be able to drive a truck through the bid-offer prices on stocks, pre-decimalization, nowadays prices are much, much tighter — with the result that trading is much, much less expensive than it used to be. Given all that, it stands to reason that even if the HFT shops are making good money, they’re still making less than the big broker-dealers used to make back in the day. But that’s not a calculation Lewis seems to have any interest in.

Father of HFT: Slow Down

Thomas Peterffy is one of the pioneers of automated stock trading. From NPR’s Planet Money:

…The company he started, Interactive Brokers, does electronic trades on a mind-boggling scale. Forbes estimates his net worth is now over $5 billion.

Peterffy says automation has done some very good things for the world. It’s made buying and selling stocks much much cheaper for everyone.

But Peterffy thinks the race for speed is doing more harm than good now. “We are competing at milliseconds,” he says. “And whether you can shave three milliseconds of an order, has absolutely no social value.”

Here are previous MR posts on high frequency trading.

HFT versus the sub-optimal Tick

Felix Salmon has an interesting follow-up to my post, Should Stocks Trade in Increments of $.0001?  First he notes (as did Chris Stuccio) that for stocks above say $50 the sub-penny rule doesn’t make much difference.

Here’s the chart, from Credit Suisse via Cardiff Garcia:

cs-24may12.jpg

The y-axis shows the bid-offer spread on any given stock, in basis points; the x-axis shows the price of the stock, in dollars. Clearly, there’s an artificial clustering around that curve. For a lot of stocks trading at less than $50 a share, the market would happily provide bid-offer spreads of less than a penny if it could; but it can’t. And when stocks get really cheap, the bid-offer spread becomes enormous. For instance, an eye-popping 3.766 billion shares of Citigroup were traded on December 17, 2009, when the stock fell 7.25% to $3.20. At that level, a one-penny bid-offer spread is equivalent to a whopping 31 basis points; if Apple traded at a 31bp spread, then its bid-offer spread would be almost $2.

Clearly, the traders were the big winners when Citi was trading at a very low dollar price — if you make the assumption that traders capture half the bid-offer spread on each trade, then the traders made almost $20 million trading Citigroup alone, in one day.

On the other hand, it seems that the market almost never trades stocks at a bid-offer spread much below 2bp. Which in turn means that for stocks over $50 per share, we’re pretty much already living in Stuccio’s ideal world, where the spread is determined by traders, rather than by an artificial rule barring increments of less than a penny.

Salmon then makes another point – firms may use stock splits and IPO pricing to deliberately price their stocks below $50. Salmon says this is in part to grease their relationship with Wall Street but one could also say this is done in order to create more liquidity. In fact, there is good evidence for Salmon’s hypothesis that firms care about nominal share price; In Tick Size, Share Prices, and Stock Splits (JSTOR, H/T OneEyedMan) James Angel makes the interesting point that even as the S&P and CPI soared between 1924 and 1994 the average nominal price of a stock was very flat near $32. Angel’s explanation is that firms use the IPO price and splits to keep a consistent relationship between tick size and share price because:

A large relative tick size also encourages dealers to make a market in a stock….a larger tick provides a higher minimum round-trip profit to a dealer who can buy at the bid and sell at the offer.

Angel even notes the potential for rent-seeking that motivated the original argument to eliminate the sub-penny rule:

If the relative tick size is too big, the profits from a wider tick size may be dissipated through vigorous competition for order flow and payment for order flow.

Overall, I find these arguments continue to favor eliminating the sub-penny rule but these results indicate that firms already have some control over the extent of HFT so the net benefits may be smaller than at first imagined. It is probably easier to split than to combine shares to raise price, however, and social benefits may exceed private benefits so I still see an argument for eliminating the rule. See Felix’s post also for a number of very good comments.

What if all the HFTers run away from the market?

That’s a common criticism of high-frequency traders, or for that matter of the older specialist system, or of some other trading practices; many MR readers make that point in these comments.

But is that a problem with uninternalized, Pareto-relevant externalities?

Let’s say many men visit a bar for its beautiful women.  That said, if the women, on a given evening, don’t see enough desirable men, they go home.  The beautiful women run away, but the plain women stick in the other bar, across the street, no matter what.  Men choose between bars, knowing that the one bar will often be very crowded, but sometimes empty.

The negative externality from the beautiful women, if there is one at all, is on the bar with the plain women.  That bar might find it harder to achieve critical mass and get off the ground.  But the first bar is not made worse off by the possibility that beautiful women might show up or instead might “flake.”  Men internalize that knowledge when deciding whether or not to visit that bar.

In other words, potential negative externalities from HFT (or other culprit trading strategies) are on the markets where HFT is not very active.  Yet the complaints you hear are about the markets where HFT is very active, and those complaints don’t correspond to the theoretical argument which might make sense.  They are wishing for the beautiful woman who sticks around at the bar no matter what.

The high-frequency traders are like the beautiful women.  If their biggest “threat” is to stay home, we are not worse off for their existence.   If we fear their flaky departures enough, we may prefer to trade in other markets or at other time horizons, namely very long.

All this is assuming that such flaky departures occur — relative to the relevant alternatives — and that point can be debated.

In which ways does inflation harm the poor?

That is the topic of my latest Bloomberg column, here is one bit:

One major factor: The poor is the socioeconomic group that finds it hardest to purchase a home, and real estate seems to be one of the best inflation hedges. U.S. real estate prices have been on a tear for some time, including through the recent inflationary period…

The poor also save less, including as a share of their incomes, because they have to spend a relatively large percentage of their incomes on necessities. That means they have smaller buffers against many kinds of changes and uncertainties, including those of inflation.

Some researchers have referred to inflation as a “regressive consumption tax,” because cash balances are so often the pathway to consumption for poorer income groups. Poorer individuals also are less likely to have cash management accounts and other asset holdings that might partially insulate them from the losses of inflation.

And:

Probably the strongest argument in favor of the notion that the poor are less affected by inflation is that inflation can, under some circumstances, lower the real value of debt. If prices go up 7%, and your income goes up 7%, all of a sudden your debts — which typically are fixed in nominal value — are worth 7% less.

This mechanism is potent, but it assumes that real wages keep pace with inflation. Right now real wages are falling, and with higher inflation may continue to do so. Furthermore, many poor people roll over their debts for longer periods of time. Repaying those debts will eventually be cheaper in inflation-adjusted terms, but not anytime soon.

I’ve been focusing on the U.S., but elsewhere in the world the general correlation is that high inflation and high income inequality go together. Correlation is not causation, but those are not numbers helpful to anyone who wishes to argue that inflation is a path to greater income equality. Have very high levels of inflation done much for the poor in Venezuela and Zimbabwe?  And if you ask which group would benefit from an improvement in living standards prompted by higher rates of investment, as might follow from a period of stability — it is the poor, not the wealthy.

There is further content at the link.

Larry Summers, Right Again

No surprise but in can case you were wondering, retail investors trade mostly on noise. A little bit more surprising is that the effect is to make markets less liquid since some models suggest that noise traders make markets more liquid and accurate by bringing in the sharks.

Contrasting with recent evidence that retail traders are informed, we find that Robinhood ownership changes are unrelated with future returns, suggesting that zero-commission investors behave as noise traders. We exploit Robinhood platform outages to identify the causal effects of commission-free traders on financial markets. Exogenous negative shocks to Robinhood participation are associated with increased market liquidity and lower return volatility among stocks favored by Robinhood investors, as proxied by WallStreetBets mentions. Platform outages are also associated with reduced high frequency trader (HFT) activity, indicative of payments for order flow. However, outages have the strongest effect on stocks neglected by HFTs, suggesting that zerocommission traders have direct negative effects on market quality.

Here is the paper by Eaton, Green, Roseman and Wu.

The demise of the happy two-parent family

Here is new work by Rachel Sheffield and Scott Winship, I will not impose further indentation:

“-          We argue, against conventional wisdom on the right, that the decades of research on the effects of single parenthood on children amounts to fairly weak evidence that kids would do better if their actual parents got or stayed married. That is not to say that that we think single parenthood isn’t important–it’s a claim about how persuasive we ought to find the research on a question that is extremely difficult to answer persuasively. But even if it’s hard to determine whether kids would do better if their unhappy parents stay together, it is close to self-evident (and uncontroversial?) that kids do better being raised by two parents, happily married.

–          We spend some time exploring the question of whether men have become less “marriageable” over time. We argue that the case they have is also weak. The pay of young men fell over the 1970s, 1980s, and early 1990s. But it has fully recovered since. You can come up with other criteria for marriageability–and we show several trends using different criteria–but the story has to be more complicated to work. Plus, if cultural change has caused men to feel less pressure to provide for their kids, then we’d expect that to CAUSE worse outcomes in the labor market for men over time. The direction of causality could go the other way.

–          Rather than economic problems causing the increase in family instability, we argue that rising affluence is a better explanation. Our story is about declining co-dependence, increasing individualism and self-fulfillment, technological advances, expanded opportunities, and the loosening of moral constraints. We discuss the paradox that associational and family life has been more resilient among the more affluent. It’s an argument we advance admittedly speculatively, but it has the virtue of being a consistent explanation for broader associational declines too. We hope it inspires research hypotheses that will garner the kind of attention that marriageability has received.

–          The explanation section closes with a look at whether the expansion of the federal safety net has affected family instability. We acknowledge that the research on select safety net program generosity doesn’t really support a link. But we also show that focusing on this or that program (typically AFDC or TANF) misses the forest. We present new estimates showing that the increase in safety net generosity has been on the same order of magnitude as the increase in nonmarital birth rates.

–          Finally, we describe a variety of policy approaches to address the increase in family stability. These fall into four broad buckets: messaging, social programs, financial incentives, and other approaches. We discuss 16 and Pregnant, marriage promotion programs, marriage penalties, safety net reforms, child support enforcement, Career Academies, and other ideas. We try to be hard-headed about the evidence for these proposals, which often is not encouraging. But the issue is so important that policymakers should keep trying to find effective solutions.”

A highly qualified reader emails me on heterogeneity

I won’t indent further, all the rest is from the reader:

“Some thoughts on your heterogeneity post. I agree this is still bafflingly under-discussed in “the discourse” & people are grasping onto policy arguments but ignoring the medical/bio aspects since ignorance of those is higher.

Nobody knows the answer right now, obviously, but I did want to call out two hypotheses that remain underrated:

1) Genetic variation

This means variation in the genetics of people (not the virus). We already know that (a) mutation in single genes can lead to extreme susceptibility to other infections, e.g Epstein–Barr (usually harmless but sometimes severe), tuberculosis; (b) mutation in many genes can cause disease susceptibility to vary — diabetes (WHO link), heart disease are two examples, which is why when you go to the doctor you are asked if you have a family history of these.

It is unlikely that COVID was type (a), but it’s quite likely that COVID is type (b). In other words, I expect that there are a certain set of genes which (if you have the “wrong” variants) pre-dispose you to have a severe case of COVID, another set of genes which (if you have the “wrong” variants) predispose you to have a mild case, and if you’re lucky enough to have the right variants of these you are most likely going to get a mild or asymptomatic case.

There has been some good preliminary work on this which was also under-discussed:

You will note that the majority of doctors/nurses who died of COVID in the UK were South Asian. This is quite striking. https://www.nytimes.com/2020/04/08/world/europe/coronavirus-doctors-immigrants.html — Goldacre et al’s excellent paper also found this on a broader scale (https://www.medrxiv.org/content/10.1101/2020.05.06.20092999v1). From a probability point of view, this alone should make one suspect a genetic component.

There is plenty of other anecdotal evidence to suggest that this hypothesis is likely as well (e.g. entire families all getting severe cases of the disease suggesting a genetic component), happy to elaborate more but you get the idea.

Why don’t we know the answer yet? We unfortunately don’t have a great answer yet for lack of sufficient data, i.e. you need a dataset that has patient clinical outcomes + sequenced genomes, for a significant number of patients; with this dataset, you could then correlate the presences of genes {a,b,c} with severe disease outcomes and draw some tentative conclusions. These are known as GWAS studies (genome wide association study) as you probably know.

The dataset needs to be global in order to be representative. No such dataset exists, because of the healthcare data-sharing problem.

2) Strain

It’s now mostly accepted that there are two “strains” of COVID, that the second arose in late January and contains a spike protein variant that wasn’t present in the original ancestral strain, and that this new strain (“D614G”) now represents ~97% of new isolates. The Sabeti lab (Harvard) paper from a couple of days ago is a good summary of the evidence. https://www.biorxiv.org/content/10.1101/2020.07.04.187757v1 — note that in cell cultures it is 3-9x more infective than the ancestral strain. Unlikely to be that big of a difference in humans for various reasons, but still striking/interesting.

Almost nobody was talking about this for months, and only recently was there any mainstream coverage of this. You’ve already covered it, so I won’t belabor the point.

So could this explain Asia/hetereogeneities? We don’t know the answer, and indeed it is extremely hard to figure out the answer (because as you note each country had different policies, chance plays a role, there are simply too many factors overall).

I will, however, note that this the distribution of each strain by geography is very easy to look up, and the results are at least suggestive:

  • Visit Nextstrain (Trevor Bedford’s project)
  • Select the most significant variant locus on the spike protein (614)
  • This gives you a global map of the balance between the more infective variant (G) and the less infective one (D) https://nextstrain.org/ncov/global?c=gt-S_614
  • The “G” strain has grown and dominated global cases everywhere, suggesting that it really is more infective
  • A cursory look here suggests that East Asia mostly has the less infective strain (in blue) whereas rest of the world is dominated by the more infective strain: