These days, a lot of buying and selling of stocks is done by computers—it’s called algorithmic trading. Computers can do it much faster than people. Watch how they’ve been going wild!
The date is at lower left. In 2000 it took several seconds for computers to make a trade. By 2010 the time had dropped to milliseconds… or even microseconds. And around this year, market activity started becoming much more intense.
I can’t even see the Flash Crash on May 6 of 2010—also known as The Crash of 2:45. The Dow Jones plummeted 9% in 5 minutes, then quickly bounced back. For fifteen minutes, the economy lost a trillion dollars. Then it reappeared.
But on August 5, 2011, when the credit rating of the US got downgraded, you’ll see the activity explode! And it’s been crazy ever since.
The movie above was created by Nanex, a company that provides market data to traders. The x axis shows the time of day, from 9:30 to 16:00. The y axis… well, it’s the amount of some activity per unit time, but they don’t say what. Do you know?
The folks at Nanex have something very interesting to say about this. It’s not high frequency trading or ‘HFT’ that they’re worried about—that’s actually gone down slightly from 2008 to 2012. What’s gone up is ‘high frequency quoting’, also known as ‘quote spam’ or ‘quote stuffing’.
Over on Google+, Sergey Ten explained the idea to me:
Quote spam is a well-known tactic. It used by high-frequency traders to get competitive advantage over other high-frequency traders. HF traders generate high-frequency quote spam using a pseudorandom (or otherwise structured) algorithm, with his computers coded to ignore it. His competitors don’t know the generating algorithm and have to process each quote, thus increasing their load, consuming bandwidth and getting a slight delay in processing.
A quote is an offer to buy or sell stock at a given price. For a clear and entertaining of how this works and why traders are locked into a race for speed, try:
• Chris Stucchio, A high frequency trader’s apology, Part 1, 16 April 2012. Part 2, 25 April 2012.
I don’t know a great introduction to quote spam, but this paper isn’t bad:
• Jared F. Egginton, Bonnie F. Van Ness, and Robert A. Van Ness, Quote stuffing, 15 March 2012.
Toward the physical limits of speed
In fact, the battle for speed is so intense that trading has run up against the speed of light.
For example, by 2013 there will be a new transatlantic cable at the bottom of the ocean, the first in a decade. Why? Just to cut the communication time between US and UK traders by 5 milliseconds. The new fiber optic line will be straighter than existing ones:
“As a rule of thumb, each 62 miles that the light has to travel takes about 1 millisecond,” Thorvardarson says. “So by straightening the route between Halifax and London, we have actually shortened the cable by 310 miles, or 5 milliseconds.”
Meanwhile, a London-based company called Fixnetix has developed a special computer chip that can prepare a trade in just 740 nanoseconds. But why stop at nanoseconds?
With the race for the lowest “latency” continuing, some market participants are even talking about picoseconds––trillionths of a second. At first the realm of physics and math and then computer science, the picosecond looms as the next time barrier.
Actions that take place in nanoseconds and picoseconds in some cases run up against the sheer limitations of physics, said Mark Palmer, chief executive of Lexington, Mass.-based StreamBase Systems.
Black swans and the ultrafast machine ecology
As high-frequency trading and high-frequency quoting leave slow-paced human reaction times in the dust, markets start to behave differently. Here’s a great paper about that:
• Neil Johnson, Guannan Zhao, Eric Hunsader, Jing Meng, Amith Ravindar, Spencer Carran amd Brian Tivnan, Financial black swans driven by ultrafast machine ecology.
A black swan is an unexpectedly dramatic event, like a market crash or a stock bubble that bursts. But according to this paper, such events are now happening all the time at speeds beyond our perception!
Here’s one:
It’s a price spike in the stock of a company called Super Micro Computer, Inc.. On October 1st, 2010, it shot up 26% and then crashed back down. But this all happened in 25 milliseconds!
These ultrafast black swans happen at least once a day. And they happen most of all to financial institutions.
Here’s a great blog article about this stuff:
• Mark Buchanan, Approaching the singularity—in global finance, The Physics of Finance, 13 February 2012.
I won’t try to outdo Buchanan’s analysis. I’ll just quote the abstract of the original paper:
Society’s drive toward ever faster socio-technical systems, means that there is an urgent need to understand the threat from ‘black swan’ extreme events that might emerge. On 6 May 2010, it took just five minutes for a spontaneous mix of human and machine interactions in the global trading cyberspace to generate an unprecedented system-wide Flash Crash. However, little is known about what lies ahead in the crucial sub-second regime where humans become unable to respond or intervene sufficiently quickly. Here we analyze a set of 18,520 ultrafast black swan events that we have uncovered in stock-price movements between 2006 and 2011. We provide empirical evidence for, and an accompanying theory of, an abrupt system-wide transition from a mixed human-machine phase to a new all-machine phase characterized by frequent black swan events with ultrafast durations (<650ms for crashes, <950ms for spikes). Our theory quantifies the systemic fluctuations in these two distinct phases in terms of the diversity of the system's internal ecology and the amount of global information being processed. Our finding that the ten most susceptible entities are major international banks, hints at a hidden relationship between these ultrafast 'fractures' and the slow 'breaking' of the global financial system post-2006. More generally, our work provides tools to help predict and mitigate the systemic risk developing in any complex socio-technical system that attempts to operate at, or beyond, the limits of human response times.
Trans-quantitative analysts?
When you get into an arms race of trying to write algorithms whose behavior other algorithms can’t predict, the math involved gets very tricky. Over on Google+, F. Lengvel pointed out something strange. In May 2010, Christian Marks claimed that financiers were hiring experts on large ordinals—crudely speaking, big infinite numbers!—to design algorithms that were hard to outwit.
I can’t confirm his account, but I can’t resist quoting it:
In an unexpected development for the depressed market for mathematical logicians, Wall Street has begun quietly and aggressively recruiting proof theorists and recursion theorists for their expertise in applying ordinal notations and ordinal collapsing functions to high-frequency algorithmic trading. Ordinal notations, which specify sequences of ordinal numbers of ever increasing complexity, are being used by elite trading operations to parameterize families of trading strategies of breathtaking sophistication.
The monetary advantage of the current strategy is rapidly exhausted after a lifetime of approximately four seconds — an eternity for a machine, but barely enough time for a human to begin to comprehend what happened. The algorithm then switches to another trading strategy of higher ordinal rank, and uses this for a few seconds on one or more electronic exchanges, and so on, while opponent algorithms attempt the same maneuvers, risking billions of dollars in the process.
The elusive and highly coveted positions for proof theorists on Wall Street, where they are known as trans-quantitative analysts, have not been advertised, to the chagrin of executive recruiters who work on commission. Elite hedge funds and bank holding companies have been discreetly approaching mathematical logicians who have programming experience and who are familiar with arcane software such as the ordinal calculator. A few logicians were offered seven figure salaries, according to a source who was not authorized to speak on the matter.
Is this for real? I like the idea of ‘trans-quantitative analysts’: it reminds me of ‘transfinite numbers’, which is another name for infinities. But it sounds a bit like a joke, and I haven’t been able to track down any references to trans-quantitative analysts, except people talking about Christian Marks’ blog article.
I understand a bit about ordinal notations, but I don’t think this is the time to go into that—not before I’m sure this stuff is for real. Instead, I’d rather reflect on a comment of Boris Borcic over on Google+:
Last week it occurred to me that LessWrong and OvercomingBias together might play a role to explain why Singularists don’t seem to worry about High Frequency Robot Trading as a possible pathway for Singularity-like developments. I mean IMO they should, the Singularity is about machines taking control, ownership is control, HFT involves slicing ownership in time-slices too narrow for humans to know themselves owners and possibly control.
The ensuing discussion got diverted to the question of whether algorithmic trading involved ‘intelligence’, but maybe intelligence is not the point. Perhaps algorithmic traders have become successful parasites on the financial system without themselves being intelligent, simply by virtue of their speed. And the financial system, in turn, seems to be a successful parasite on our economy. Regulatory capture—the control of the regulating agencies by the industry they’re supposed to be regulating—seems almost complete. Where will this lead?
Azimuth 
I don’t know much about this, but I feel that the interesting part about using ultra-fast machines is not so much to make the system more complex and potentially more unstable. Rather it is the time scale of the dynamics that is considerably shortened. Thus it may not be so surprising to see “black swans” more frequently.
I often lose 5-0 at soccer, but I play a lot…
Great post, I love it! I was in the flash crash that day, will never forget it. This is a classic vid from that time:
Glad you liked the post! After you read it, I added a graph of an ‘ultrafast black swan’—you might like that too.
What do you mean by saying you were “in” the Flash Crash? Were you working in finance?
There are a few facts I would like to mention:
– I have a lot of programming experience,
– I also know a bit about math,
– any salary above 200 000 $ is a lot for me,
– my current contract has a 3 months notice.
So if I understood correctly one should look for:
– I have only little programming experience
– I also know only a bit about math
– any salary above 200 000$ is also a lot for me
– My freelancing salary has currently to stay below 375 Euros a month since it is currently often only a few Euros an hour (in some jobs it was rather Eurocent)
-the unemployment rate in my age group (>45) in my city district is about 50 per cent.
– My pension will currently be about 441 Euros a month.
– If you want to hire me, you need to risk 1-3 months of me learning stuff.
– I have quite a bit of programming experience, thus am able to learn any programming language within 1 day (believe me or not) plus 1 day of practise plus 1 month of finding the most important bugs in the libs.
– As a kid I’ve played with LFSR and binary prime numbers, thus I almost invented the quote spam machine. My stochastics thesis advisor was Anton Thalmaier.
– I’d love to learn this ordinal stuff, given:
— flexible work time (not only for early birds)
— non-counterproductive work conditions (e.g. adequate tools, cooperative collegium)
— no suit, no tie, no funny looks when I come barefoot at noon
– From my experience the latter 3 conditions are impossible to fulfill for the classic German Fachkräftemangel boss. That’s why I want 200.000 compensation.
– Actually I don’t need 200.000
While you posted your blog post here I replied to your Google+ posting with the same content (interrupted by being occupied with a broken heating system). I post my reply there also here –
sorry for double replying, but Google+ is so badly searchable (…it seems the Google search engine has a autoimmune disorder with respect to Google+) and may be there are still people here who do not read your Google+ postings.
The black swan analysis is interesting, however the correlation with the high financial institutions is hard to grasp:
One would expect that such big banks are not so sensitive to their HFT sector – so is it an overall tendency of negligence within these banks which is in charge of this?
Here my Google+ reply:
+tqft simpson and +John Baez thanks for the links.
The Nanex company holds some interesting charts.
I am currently asking myself to what extent actual values are being burned and/or stored due to increased transaction lengths. (With transaction length I mean the length an actual real “product with value” (or its money equivalent) is really exchanged (“bought”). In the case of shares this could be the transaction length between a company and someone who would invests his/her money in that particular company. (This transaction length actually refers not only to stock trading but similarily also to “lending chains” (here a part of a value which was brought to a bank is “exchanged” with someone who lends it for a concrete “real value”.).)
What I mean is more explained in here:
http://en.wikipedia.org/wiki/Hans_in_Luck
:)
which sort of also explains the difficulty to distinguish between real and “fake” values….
no but seriously, some more thoughts are at:
http://www.randform.org/blog/?p=4758
and on Azimuth:
http://www.azimuthproject.org/azimuth/show/Economic+growth+and+limitations
I preliminarily inserted some of your links there. Unfortunately it seems a lot of the Nanex pages are only sort of preliminary, I’d rather prefer a more stable reference, which can be cited.
Moreover it would be interesting to see actual data about the claim (that’s how I understood the businessinsider article) that a lot of HFT takes place among traders and not between traders and investors.
I find it really, really hard to believe that Christian Marks’ post is anything more than a sublime prank. He was trying to pull a Sokal on all of us…
Once upon a time, some smart physicists also decided to invent Quantum Finance, probably to extort some money from gullible rich people.
Was I the first to get suspicious, or did others too? There was a long discussion of his post on slashdot, which I skimmed – but I didn’t see anyone question it.
Bill Gasarch wrote the following blog post in June 2010:
Alternative Careers for Logicians
and someone posted this comment:
It’s obviously a joke. Ordinal notations are what you use to prove that tremendously inefficient algorithms terminate. (E.g., normalization of all primitive recursive functions.) Arbitrary towers of exponentials are not what you look for when designing algorithms to run in microseconds.
If the post had been about hiring proof theorists who studied linear logic, then it would have been more plausible, since linear logic is useful for designing logical systems of bounded computational complexity.
Neel wrote:
Right. So we officially declare it a joke.
The paper Financial black swans driven by ultrafast machine ecology says that as we zoom in and investigate the stock market at ever shorter time scales, we see a phase transition as we approach times shorter than the human reaction time, because at this point we have lots of agents following the same strategies. This is the opposite of what I’d expect from people using really fancy algorithms: it’s what I’d expect from people using many copies of relatively few very fast algorithms.
There’s two components to ultra-high-frequency trading: techniques to get your “system” (ie, both software and hardware) working as fast as possible and the actual decision making. There’s relatively little complexity in the decision making, partly by the nature of the problem — you’re trying to predict a very short term event, so it’s mostly going to be determined primarily by the small volume of data immediately preceding it, possibly combined with some more general statistics about the market. So that combined with the fact there’s it’s possible to come up with the same ideas independently, it wouldn’t surprise me that the decision making algorithms are essentially the same. Most of the effort goes into making the system fast (or rather, most of the system is created first in a ill-thought out way for performance and poorly testing even basic correctness, then cutting corners to make it fast: think of a clown car with an F16 jet engine strapped to the back).
Haven’t got to reading the paper, but I’m a bit confused about the use of “black swan” nomenclature for 18,520 ultrafast events. The point about original use of “black swan” is that no-one (or virtually no-one) thinks it a “physical” possibility. I don’t think anyone in finance would be shocked by any of these events happening. I guess the term has changed to just mean “bad thing”, which is a pity. (I’ll stop there before I say anything really incendiary about financial programmers.)
I think ‘black swan’ is being extended here to mean an event that’s way far out in a long-tailed probability distribution. But yeah, if they’ve seen 18,520 of them, they can’t be all that shocking. They compare them to the microscopic cracks in an airplane wing that’s getting ready to fall off. No one individual crack deserves to be called a black swan, but together they might cause a big nasty surprise someday.
It’s important to distinguish between high volume and low latency. It’s interesting to see what one HFTer thinks about the latency race: http://www.chrisstucchio.com/blog/2012/hft_whats_broken.html and http://www.chrisstucchio.com/blog/2012/subpenny_rule_responses.html
That said, as a self-professed ignoramus about finance, I wonder whether HFT really increases liquidity in the sense of letting trades happen when people really want to (i.e. “exciting” or “unexpected” events), or whether exactly at that moment all the HFT market makers rapidly get out of the game.
[…] arms race where traders are going to extraordinary lengths to be faster than the other guy. As this article by John Baez notes, this speed race is driving companies to more and more extreme measures to get an edge on […]
There ought to be a way to bring surreal numbers into trans-quantitative finance, from the combinatorial-games perspective.
And if trans-quantitative finance is a joke, the construction should be significantly easier.
:-D
Is there any way to determine if such fast trading adds to market efficiency? That is, in the long run, do economies benefit from this robotic trading?
Chris Stucchio has a very readable blog post arguing that high frequency trading improves liquidity, and he cites this study:
• Albert J. Menkveld, High frequency trading and the new-market makersHigh frequency trading and the new-market makers, 6 February 2012.
However, he believes that the practice of keeping track of the time of bids to millisecond accuracy, together with the rule that the first bid wins (other things being equal), has traders locked in an economically useless arms race:
Interestingly, his proposal is to eliminate the ‘subpenny rule’: the rule that stock prices must be integer multiples of one cent, not fractions of a cent. The subpenny rule means that the value of being fastest is one cent per share. If stocks were traded in multiples of 0.00001 cent, that would be the value per share of being fastest.
The benefit of HFT is hard to measure when things like quote spam exist. Regulators need to focus on micro market rules to eliminate obviously negative things like quote spam.
I doubt that the ideas of restricting time or price increments are worthwhile. These ideas simply push the boundary of the HFT arms race to the time or price increment threshold and reduce price efficiency (= the certainty that the traded price is the real market price).
When you buy or sell an exchange traded fund, I’m guessing that you are almost surely using the services of a high frequency trader. These people aren’t parasites, they are providing the very useful service of being able to trade hundreds of securities with one trade, all while paying a commission of, say, $7, and also knowing that you got a good price on your purchase or sale.
I wonder, if the market rules are set to maximize price transparency and efficiency (including rules on server colocation in order to guarantee a fair market, and some control on quote spam), then wouldn’t the value of HFT be equal to the profits that the HFT firms make? :). To the extent that it’s very difficult to set such rules, then the value would be the profits less some charge for the suboptimal Nash equilibrium resulting from the lack of a “perfect market” structure. IMO, people overestimate the size of this charge.
Interesting questions, Paul Check! Just a small comment… you write:
In his post High-frequency trading: what’s wrong and how to fix it, Chris Stucchio argues the problem is that
1) offers to buy and sell stock are limited to prices that are integer multiples of a penny, but
2) the time the offer is made is measured extremely accurately, and if two offers quote the same price, the first one wins.
So, by being slightly faster than someone else you can make one penny per share.
My natural tendency would be to change 2) by keeping track of the times of bids in 1-second increments. But Stucchio, who actually works in this field, suggests changing 1), by letting prices be much smaller multiples of a penny.
So, in short, he’s arguing that dropping a restriction on price increments is a good idea.
I worry that without restrictions on either price or time increments, the natural tendency will be to approach a kind of ‘continuum limit’ where computers are buying and selling shares as often as they can afford to do so.
Essentially my comments are agreeing with his….go to arbitrary price.
The point I was making would say that there isn’t anything wrong — at all — with computers trading as much as they can afford to, since the “afford” part is a good measure of the benefit such trading conveys. But, of course, that’s under the assumption that the market is competitive and efficient. Quote spam is a good example of one of the barriers to that ideal world. I’m not 100% sure that server colocation is such a big barrier (see comments below).
Prior to electronic trading (and even still with such trading) many indsutry people point to the open outcry treasury futures market in Chicago as one of the best markets in the world. The open nature of the market means that there is a massive amount of price discovery. Given the concern over server colocation related to HFT, I’ve wondered how floor position in the open outcry market works, ie whether standing in some locations is better than others. And, if it is, then how is that managed? One could say that if the physical position is itself a market commodity then the price will adjust to reflect the economic value of being located in a better or worse position. That’s why I’m not as concerned about rules over colocation as I am with rules that promote “good” prices.
Unfortunately, in many other markets (especially OTC markets common in fixed income) there is an overlap between the market and the market makers. Even equity markets have become highly splintered, with markets owned by financial firms. As that happens, and in the absence of rules that properly promote price transparency and efficiency, then yes, financial firms’ will use every tool at their disposal to extract money out of the system (the parasitic comment you make).
Sometimes there are trade offs between price efficiency and liquidity. This happens in fixed income OTC markets. Market makers have always lobbied against price transparency, saying that it would harm liquidity. I argue that price efficiency/transparency should be the ultimate goal (eg just like in the open outcry markets), and all other issues should follow from that. Ditto for HFT, or any other market for that matter.
Although I generally hold closely to market based thinking, I believe that price transparency is so important that it might even be economically optimal to force market price data to be made available for free.
Alternatively, set the rule that the trade goes at random among the subset which has offered the best price. That will avoid the continuum issue.
It certainly requires super-good random number generation and that moves the hiring issue towards jobs for statisticians.
Drat. That isn’t me. I need a better suggestion…
One way to eliminate quote spam would be to require that quotes must be alive for some minuscule amount of time. That time could be chosen to be just long enough to virtually guarantee that someone else has time to process the information and respond. Since the computers are so fast, that would be only on the order of a few milliseconds, and since that’s such a small amount of time then the negative impact is quite small, while the positive impact is very large, ensuring that quotes are reliable.
Something similar to this quote delay happens in OTC markets, whereby traders offer and wait for customer approval before trader says “done”, at which time the transaction is legally binding. During that small gap, so long as the customer is very fast, it is very unusual to change the offer. Of course bonds are much less volatile than stocks, but you’re talking massive size (eg can be in the billions) and time amounts on the order of 10ths of a second.
All of this isn’t without social consequences – the stock market is a zero-sum game, if someone makes a million dollars, the counterparties lose a million dollars. The social function of an equity market is to capitalize productive enterprises, not to provide a favored class of people with a fountain of cash at the cost of regular investors who lack the resources to even get in the game in the first place. Deny the great majority of the population any sort of stake in their society, and disastrous social consequences will invariably follow.
As John stated, the regulatory agencies have been effectively captured – but there is a non-regulatory fix: enact a tax of a penny on each share or fraction of a share traded.
Hi! Good to see you here again after all this time! I agree that the social consequences of all this are immense. I’m very worried about them.
But I don’t think the stock market is a zero-sum game… or at least, you’d have to carefully define the sense in which it is. When the Flash Crash occurred, for fifteen minutes the economy lost a trillion dollars. That’s not a zero-sum game in the usual sense!
You write:
You’re speaking of its ‘ideal’ social function—but perhaps its actual function is more like providing a favored class of people with a fountain of cash and limited liability. In other words: maybe that pessimistic description will better help us understand what’s actually going on.
I’m afraid the governments of the US and Britain have been captured to the point where this will never happen there without some sort of ‘revolution’ or ‘collapse’. The financial crisis was apparently not severe enough to make this happen.
I agree the stock market isn’t zero-sum. My point in asking about market efficiency is that the elements of creativity and labor that make, say, modern times not zero-sum are in question. I’m not impressed with arguments that infinitely fast trading programs enhance anything humans value.
One might intuitively argue that fast trading is a social waste. Or at least, I’d like to see some proof that it is not.
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Hi! Your test worked.
“Computers can do it much faster than people.”
Traders pay money to have their computers in the same room as those of the stock exchange—a few kilometers to their own computing center in the same town is too far.
HFT, algorithmic trading, low-latency trading etc have all been criticized since they are not “real”. However, it’s been a long time since most of the trading on stock exchanges has been what many people still think it is: buy some stocks in a company you believe in and if it does well you can get a dividend and/or sell them at a profit years or decades later. This still exists, of course, but most of the trading is done to make money in some other way, which is everyone’s goal in this game, including that of those who buy stocks and sell them decades later. Things like options and futures were invented to minimize risk of stock purchases, but now they are often bought and sold in their own right, with even higher-order products, e.g. options on futures. This happened before algorithmic trading and even before computers (used as tools of traders) were introduced.
All of this will stop when people are no longer interested in using it as a means to perhaps increase their wealth. Considering that the typical attitude of the traditional stock purchaser is “I have some extra money and it should increase without me having to worry about it”, much of the criticism of the new technology is somewhat hypocritical. Anyone who is worried about his fortune disappearing in microseconds should think about what his fortune actually consists of.
A few weeks ago, I was at one of the best scientific conferences I have ever attended. One of the sponsors was RSJ. At the conference dinner, I happened (purely by chance) to be at the same table as a former colleague, the main conference organizer, one of the highlight speakers, a famous astronomer who got an honorary doctorate during the conference and a chap who went into the computing industry after he had taken up a permanent position at a Max Planck Institute because the pay was so bad (but, as his visit to this rather technical conference attests, still follows the field with interest, rather like myself in this respect). There were two seats free, which I realized later had been reserved. A young man whom I hadn’t seen at the conference came and sat down, together with a strikingly beautiful woman (obviously his wife or girlfriend). I heard someone whisper “he funded all of this” as we enjoyed our conference dinner in the castle. He was a graduate of the university there, a mathematician, and made his own fortune quite quickly. A thoroughly nice chap using his money to fund things like this wonderful conference. He has also set up a foundation which fights corruption, which, though it is worse elsewhere (and not as bad in a few places), is a big problem in the Czech Republic. (As many know, my day job now is also in the financial world (though I’m a non-financial computer person concerned with more traditional tasks, not an algorithms developer or something like that—many physicists and mathematicians work in both of these sectors, of course). I still write the occasional paper and give the occasional talk and attend the occasional conference in my spare time. Interesting that the last conference I attended was made possible by someone with whom I am, albeit indirectly, connected at my paying job.)
Glad to hear about the nice chap. He most probably made his money at the expense, either directly or indirectly, of these people: http://wearethe99percent.tumblr.com/ I hope his campaign to fight corruption produces some tangible result.
Directly? Almost certainly not. In fact, he probably employs some of the 99% (who are then no longer part of the 99%, of course). One can only lose money on the stock market if one invests there in the first place. Indirectly? Only in the sense that taxation of capital-gains income is usually less than for “honest work”. At least he is putting his millions up for a good cause (in the case of the Czech Republic, perhaps doing more good than if he were paying more taxes).
The occupiers are occupying the wrong place. Whatever one’s moral concerns, if one thinks that people are profiting from immoral earnings, the lawmakers are the ones to address, not those doing legal stuff, however immoral it might be. One really can’t fault people for doing something legal. At least, if one wants to change something, one should work to change the laws.
Also, don’t confuse the stock market with the financial world in general. Stock markets tend to be quite well regulated. Especially with computer-traded stuff, people get paid to keep records, so that bad things can be prosecuted even years later. Many, probably most or even all of the financial products which have wreaked havoc recently (even outside of the financial world; I have no sympathy for someone who comes out of a casino empty-handed) are not traded on exchanges, but are so-called OTC (over-the-counter) products. Stock exchanges would love laws to require them to be traded on exchanges (another source of income for the exchanges), but of course those who profit from them are opposed to this, mainly because the fact that they are not traded on exchanges makes this stuff less transparent.
Yes, some innocent folks might have suffered collateral damage. However, for each one of these there are probably hundreds who invested their savings in Icelandic banks or whatever (something which doesn’t just happen by mistake). Hey, they pay 7%, and my savings account just pays 1%, so I’ll go for the 7%. Why do savings accounts still exist? Because they are more secure. Anyone who can’t figure out that higher interest rates go hand-in-hand with higher risks doesn’t deserve the money he lost when such banks went down.
The real problem is bailing out such banks, and indirectly the people who invested there, due to the same greed one finds elsewhere. Again, this is a problem with the lawmakers. If one doesn’t like such stuff, vote for someone else (at least if one lives in a democracy).
“stock markets tend to be quite well regulated” You must be joking, the regulatory capture of the SEC [4] by Goldman Sachs alumni is one of the best-reported and central scandals in the Obama Administration [1], typified by the latest refusal by the Department of Justice to investigate the criminal wrongdoings of that company [2][3].
And we’re not just talking about people who choose to risk their capital by investing in Wall Street, we’re talking about people who were so foolish and intemperate as to take out residential mortgages and student loans, which is where a great deal of the fraud has occurred.
And mathematicians, working in the service of these banks, hedge funds and so on, are compensated in the millions of dollars for aiding and abetting these frauds. At some point there needs to be a serious discussion about scientific ethics, because if there is a backlash, it may not be limited to Wall Street alone.
[1] http://www.democracynow.org/2012/7/5/zero_accountability_glenn_greenwald_on_obamas
[2] http://www.salon.com/2012/08/10/obamas_goldman_sachs_surrender/
[3] http://www.levin.senate.gov/imo/media/doc/supporting/2011/PSI_WallStreetCrisis_041311.pdf
[4] http://www.peakprosperity.com/blog/bill-black-our-system-so-flawed-fraud-mathematically-guaranteed/74785
Just two points: (1) I should have said well regulated compared to financial transactions outside the stock market, which most people probably hear little about, good or bad. (2) One needs to separate the discussion of fraud etc (which are already crimes) from the question whether more regulation is needed etc. With regard to residential mortgages and student loans, most of the credit-default swaps and related products which are involved in the credit crunch are OTC things, i.e. not traded on a stock exchange.
Interesting news, passed on by Richard Elwes:
“The motive of the algorithm is still unclear”—that’s an interesting sentence, the sort of sentence I expect to hear more often.
If a rival government, say the Chinese, wanted to induce quick financial paralysis in the US, this would be the way to do it. It would be one hell of a diversion, and direct DC’s attention away from other details… Fun and amusement for very little cost, and nearly untraceable. I’m surprised this isn’t being taken seriously as a national security issue.
[…] this blog quotes a reference that ordinal theory is used in High Frequency Trading (HFT) algorithms but there […]
[I told them it was probably a joke – JB]