Results for “high frequency trading”
43 found

What kinds of financial risks do women prefer to take?

As mentioned, women make up about 5 percent of an average trading floor.  But these numbers change dramatically when we leave the banks and visit their clients, the asset-management companies.  Here we find a much higher percentage of women.  The absolute numbers are not large, because asset managers employ far fewer risk taker than banks, but at some of the big asset-management companies in the United Kingdom women make up as much as 60 percent of the risk takers.  This fact is, I believe, crucial to understanding the differences in risk taking between men and women.  Asset management is risk taking, so it is not the case that women do not take risks; it is just a different style of risk taking from the high-frequency variety so prevalent at the banks.  In asset management one can take time to analyze a security and then hold the resulting trade for days, weeks or years.  So the difference between men’s and women’s risk taking may be not so much the level of risk-aversion as it is the period of time over which they prefer to make their decisions.

Perhaps men have dominated the trading floors of banks because most of the trading done on them has traditionally been of the high-frequency variety.  Men love this quick decision-making, and the physical side of trading.

That is from The Hour Between Dog and Wolf.  The author is John Coates and you can buy the book here.  I would consider that hypothesis speculative, but nonetheless I found the passage of interest.

Should Stocks Trade in Increments of $.0001?

In Modern Principles Tyler and I explain that price floors create wasteful increases in quality. The classic story is the Civil Aeronautics Board’s regulation of airline prices between 1938 and 1978. Through entry, exit and price regulation, the CAB kept prices above market levels and airlines earned excess profits with every customer. Although the airlines were not allowed to compete on price they could compete to attract customers by offering better meals, wider seats and more frequent flights. Airline quality, as a result, was high but it was inefficiently high; for example, too many flights flew half empty. More fundamentally, if airlines compete by lowering prices by $100, customers are automatically better off by $100. But when airlines have no choice but to compete by spending $100 on “quality” customers are not necessarily better off by $100. Indeed, enforced non-price competition will always result in more spending than value creation on the margin. If given the choice, customers would have preferred lower prices to higher quality but until deregulation in 1978 they were not given the choice. Thus, price floors create wasteful increases in quality.

Ok, so where does stock pricing come into play? Chris Stucchio, a high-frequency trader, argues that the sub-penny rule, SEC Rule 612, “essentially acts as a price floor on liquidity – it is illegal to sell liquidity at a price lower than $0.01.” As a result, traders compete on speed (latency) rather than on price.

As with a classical minimum wage, two parties are harmed – the purchaser (who must pay extra) and the lower priced seller (who is pushed out of the market).

Similarly, at prices higher than $0.01, it makes price movements lumpy – on a bid ask spread of $0.05, it is illegal for someone to enter the market at price $0.049 or $0.045. Thus, at any price point, speculators are forced to compete on latency rather than on price. Price competition is only possible if one market maker is willing to offer a price at least $0.01 better than another, which is often not the case.

When price competition is impossible, market makers must compete for business via other methods – in this case latency.

As with the airlines, the increase in speed–now such that 40,000 trades can be executed in the literal blink of an eye and relativity matters–is profitable for the traders even though it doesn’t add nearly as much to customer or social welfare. As I wrote earlier:

A small increase in speed over one’s rivals has a large effect on who wins the race but no effect on whether the race is won and only a small effect on how quickly the race is won.  We get too much investment in innovations with big influences on distribution and small (or even negative) improvements in efficiency and not enough investment in innovations that improve efficiency without much influencing distribution (i.e. innovations in goods with big positive externalities).

Penny pricing (and before that 1/16th pricing) made sense when stocks were mostly traded by humans and we needed to conserve cognition but, as Stucchio points out, most trading today is done by computers and pricing in hundredths of a penny (or less) would not impose any extra effort on the computers. Pricing in 1/100ths of a penny, however, would dramatically increase price competition and reduce wasteful quality competition.

Here are previous MR posts on HFT about which Tyler and I have debated.

Terrence Hendershott writes to me

Below are thoughts from an author of a paper Tyler cited on algorithmic trading (and HFT). There is a project by the UK government on related topics. Some related working papers on HFT are here, here, here, here, and here.

1. Technology has made financial markets work better; improvements in liquidity are large, important, and should result in lower costs of capital for firms; these do not mean that every application of technology is good.

2. There is evidence that investors prefer continuous to periodic trading, but batch auctions as frequent as every few seconds have not been studied.

3. Until technology allows buyers and sellers to better find each other simultaneously, markets need a group of intermediaries; the lowest-cost intermediaries are those closest to the market.

4. Historically, intermediaries were floor traders, now are HFT; floor traders profit from those further from the trading mechanism as do HFT now.

5. What is the best industrial organization for the intermediation sector? i) free entry (HFT) or ii) regulated oligopoly (NYSE specialists, Nasdaq market makers, etc.)?

6. Floor trading had the advantage that within-market relative latency was not so important and the amount of market data produced was small; costs were floor traders’ large advantages and possible collusion.

7. There is yet to be robust empirical evidence linking HFT to declines in market quality or efficiency; Haldane has interesting ideas, but as comments point out, it is difficult to blame HFT more than the economic and euro crises for recent fat tails in asset returns; systemic uncertainty increases fat tails and cross-asset correlations.

Overall, technology applied to intermediation appears to bring benefits with the standard rent seeking costs of intermediaries making money, possible instability (although 1987 showed human markets have their own failings), and technology costs.

Can markets find solutions?

i) If HFT becomes competitive (zero rents), will HFT then resell their technology as brokers? Could this lead to efficiency without negative externalities?

ii) Do dark pools and batch auctions limit part of the “arms race” of technology investment? Significant volumes are already traded in these ways, e.g., the opening and closing auctions. There are many ways investors can avoid HFT.  If they do not, is it revealed preference?

If regulations are needed they should target behavior, not certain trading firms, otherwise HFT features will simply be incorporated into other strategies, e.g., a HFT strategy is merged with a mid-frequency strategy.

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.

Do our intuitions about deadweight loss break down at very small scales?

I’ve been thinking about high-frequency trading again.  Some of the issues surrounding HFT may come from whether our intuitions break down at very small scales.

Take the ordinary arbitrage of bananas.  If one banana sells for $1 and another for $2, no one worries that the arbitrageurs, who push the two prices together, are wasting social resources.  We need the right price signal in place and the elimination of deadweight loss is not in general “too small” to be happy about.

But at tiny enough scales, we stop being able to see why the correct price is the “better” price, from a social point of view.  Think of the marginal HFT act as bringing the correct price a millisecond earlier, so quickly that no human outside the process notices, much less changes an investment decision on the basis of the better price coming more quickly.  (Will we ever use equally fast computers to make non-financial, real investment decisions in equally small shreds of time?  Would that boost the case for HFT?  Is HFT “too early to the party”?  If so, does it get credit for starting the party and eventually accelerating the reactions on the real investment side?)

HFT also lowers liquidity risk in many cases (it is easier to resell a holding, especially for long-term investors, as day churners can get caught in the froth), and thereby improving the steady-state market price, again especially for long-term investors.  That too could improve investment decisions, even if the improvement in the price is small in absolute terms.

Some decisions based on prices have to rely on very particular thresholds.  If no tiny price change stands a chance of triggering that threshold, we encounter the absurdity of there being no threshold at all.  We fall into the paradoxes of the intransitivity of indifference and you end up with too many small grains of sugar in your coffee.

So maybe a tiny price improvement, across a very small area of the price space, carries a small chance of prompting a very large corrective adjustment, with a comparably large social gain.  Yet we never know when we are seeing the adjustment.  The smaller the scale of the price improvement, the less frequently the real economy gains come, but in expected value terms those gains remain large relative to the resources used for arbitrage, just as in the bananas case.  It’s not obvious why operating on a smaller scale of price changes should change this familiar logic.  Is the key difference of smaller scales, combined with lumpy real economy adjustments, a greater infrequency of benefit but intact expected gains?

In this model the HFTers labor, perhaps blind to their own virtues, and bring one big grand social benefit, invisibly, every now and then.  Occasionally, for real investors, their trades help the market cross a threshold which matters.

I am reminded of vegetarians.  Say you stop eating chickens.  You are small relative to the market.  Does your behavior ever prompt the supermarket to order a smaller number of chickens based on a changed inventory count?  Or are all the small rebellions simply lost in a broader froth?

What is the mean expected time that HFT must run before it triggers a threshold significant for the real economy?

Aren’t the rent-seeking costs of HFT near zero?  Long-term investors do not have to buy and sell into the possible froth.  HFTers thus “tax” the traders who were previously the quickest to respond, discourage their trading, and push the rent-seeking costs of those traders out of the picture.  More fast computers, fewer carrier pigeons.  Are there models in which total rent-seeking costs can fall, as a result of HFT?  Does it depend on whether fast computers or pigeons are more subject to production economies of scale?

Relativistic statistical arbitrage

I haven’t read this paper (pdf) yet, but the abstract is already a winner:

Recent advances in high-frequency financial trading have made light propagation delays between geographically separated exchanges relevant. Here we show that there exist optimal locations from which to coordinate the statistical arbitrage of pairs of spacelike separated securities, and calculate a representative map of such locations on Earth. Furthermore, trading local securities along chains of such intermediate locations results in a novel econophysical effect, in which the relativistic propagation of tradable information is effectively slowed or stopped by arbitrage.

Hat tip goes to Robert Cottrell, and Kevin Drum pulls the map out.

Assorted links

1. Read a book you'll hate.

2. New story on high-frequency trading.

3. 2010 book preview; oddly not one of them excites me except maybe the Per Petterson.

4. The music industry of the future?

5. "Superstar teachers had four other tendencies in common: they avidly recruited students and their families into the process; they maintained focus, ensuring that everything they did contributed to student learning; they planned exhaustively and purposefully–for the next day or the year ahead–by working backward from the desired outcome; and they worked relentlessly, refusing to surrender to the combined menaces of poverty, bureaucracy, and budgetary shortfalls." More here.

6. Why the Eurozone has a tough decade to come.

7. Ezra Klein is on Colbert tonight, early part of the show.  Today his WP blog is broken so he can't announce it.

8. What not to say when buying a car.

Interview with Denise Shull

She is using neurobiology to better understand traders' behavior and also to advise traders.  Here is one bit:

StockTickr: What single lesson did you learn along the way that has helped you the most in your trading?

Denise: Learn how to process your emotions in real time. so that the emotion is not “acted out” in trade entries or exits.

Here is a recent article on Denise Shull.  Unlike many contemporary researchers in her field, she still has a real attachment to Freud.  "Emotional intelligence" for traders is perhaps a good summary of her core message.  I wonder how many professions (bloggers? no) are lucrative enough to afford paid emotional intelligence consultants.

Via Daniel Hawes, here is a piece on how length-ratios of second and fourth digits predict success among high-frequency stock traders.  I can't say I'm convinced that "prenatal androgen exposure may affect a trader by sensitizing his subsequent trading performance to changes in circulating testosterone" but it's worth a read.

Assorted links

1. Advice for holiday shopping: buy it, don't wait.

2. Rich Germans demand higher taxes.

3. A Georgist approach to financing health care reform: tax water.

4. Don Boudreaux defends insider trading.

5. A simple look at dark pools and high-frequency trading.

6. Essay on Freakonomics and other popular economics books, as they relate to the economics profession.  How fun is economics really?

Mindles Dreck is the Dreck of my dreams

I’d like to reproduce chunks of his old yet prescient post (or go here and scroll down to 22 January):

Pundits continue to link the Enron debacle to a need for increased regulation,
especially of derivatives. What most of these people…don’t appreciate is that regulation and/or accounting rules are the
most fertile breeding ground for derivatives and synthetic or packaged
securities. Regulations and accounting rule-inspired transactions
describe the bulk of the well known derivative-related blow-ups of the
last two decades. Proscriptive regulation and the derivative trade have
a symbiotic relationship.

Investors and operating companies buy derivatives for two basic
purposes: speculation and risk transfer. A derivative, (a financial
contract based on the price of another commodity, security, contract or
index) either eliminates an exposure, creates an exposure, or
substitutes exposures. That last one, substituting exposures, is
important to heavily regulated investors.

For example, insurance companies were a goldmine for derivatives
salespeople in the last two decades, only slowing down in the late
1990s. The fundamental reason for this is not because insurance
executives were stupid, but because they manage their investments in a
thicket of proscriptive regulation. Insurance companies have to respond
to their national regulatory organization (the NAIC), their home state
insurance department and the insurance departments of states in which
they sell or write business. They file enormous statutory reports every
quarter using special regulatory pricing, and calculate complex
risk-based capital reports and "IRIS" ratios regularly.

Even though the insurance industry has been heavily regulated
throughout the entire post-war era, the incidents of fraud and
financial mismanagement have been numerous and spectacular.  Remember Marty Frankel?
Mutual Benefit Life? For each of these cases that are in the news,
there are many smaller ones you don’t hear about. Some of that may be
the nature of the industry, but it doesn’t make a prima facie case for more regulation…

Insurance companies often need the yield of less creditworthy
obligations. So derivative salesmen see an opportunity to engineer
around the regulations. They package securities that substitute price
volatility for the proscribed credit risk. Then the investor can be
compensated for taking some additional risk, and the banker can be
compensated for creating the opportunity. A simple example of this is
the Collateralized Bond Obligation (CBO). A CBO is created by buying a
bunch of bonds, usually of lower credit quality, putting them in a
"special purpose vehicle" (SPV) and then issuing two or more debt
instruments from the SPV. The more senior instruments can obtain an
investment grade rating based on the "cushion" created by the junior
debt tranche. The junior bond absorbs, for example, the first 10% of
losses in the entire portfolio and only when losses exceed that amount
will the senior obligations be impaired. The junior instruments, known
as "Z-Tranches" become "toxic waste", suitable only for speculators and
trading desks with strange risks to lay off (or, in a famous 1995 case,
the Orange County California Treasurer).

A CBO is just one example of a credit rating-driven transaction, but most of them achieve the same thing – they decrease frequency of loss but increase the severity.
So they blow up infrequently, but when they do it’s often a big mess.
Ratings-packaged instruments are less risky than the pool of securities
they represent but often riskier and less liquid than the investment
grade securities for which they are being substituted. As a result,
they pay a yield or return premium (even net of high investment banking
fees). That premium may or may not be enough to pay for their risk. But
they pass the all-important credit rating process and are therefore
sometimes the only choice for ratings-restricted portfolios reaching
for yield.

…[Frank] Partnoy is a former derivatives salesperson, and he clearly suggests
that regulation is often the derivative salesman’s best friend.
Complicated rules encourage complex transactions that seek to conceal
or re-shape their true nature. Regulated entities create demand for
complex derivatives that substitute proscribed risks for admitted
risks. If a new risk is identified and prohibited, the market starts
inventing instruments that get around it. There is no end to this
process. Regulators have always had this perversely symbiotic
relationship with Wall Street. And the same can be said for the
ridiculously complicated federal taxation rules and increasingly
byzantine Financial Accounting Standards, both of which have inspired
massive derivative activity as the engineers find their way around the
code maze.

Dreck, in case you don’t know, used to blog with Megan McArdle over at Asymmetric Information.  Here is what happens when you enter "Star Dreck" into YouTube.

What is the real mutual fund scandal?

It’s not market timing, not according to Mark Hulbert. He writes:

Market timing, as the phrase has traditionally been used in the stock market, refers to shifting a portfolio from equities to cash in the hope of sidestepping a market decline, then moving back into the market in anticipation of a rally. There are many approaches to market timing; they vary according to the techniques used to forecast rallies and declines and in the frequency of the switching. Market timers’ track records also vary widely.

Strictly defined, market timing has little to do with the fund industry’s current troubles.

In part, late trading allows some shareholders to trade after the market close. But much of the real problem is — stale pricing:

Some mutual funds have been accused of allowing certain investors to take advantage of out-of-date securities prices used by funds in calculating their net asset values. Because those stale prices were sometimes too low or too high, investors who frequently switched into and out of these funds could realize substantial profits at the expense of other shareholders.

This stale-price arbitrage, as the practice is sometimes called, happens most often in international stock funds. When funds calculate their net asset values at 4 p.m., they generally use the prices at which their portfolio stocks traded most recently. For international funds, those prices can be several hours out of date.

Here is a related New York Times article, on Eric Zitzewitz, who is developing means of measuring asset values more correctly, to prevent stale pricing. The problem: fund managers themselves engage in the practice, and so they are reluctant to adopt these innovations. The solution?: Enforce current laws, already on the books.

See also my earlier post, on how much the mutual fund scandals cost investors.