High Frequency Trading (HFT)

The study of HFT is a study of market parasitism.  The following introduction was adapted from blong post Risk and Reward in High Frequency Trading.

The recent paper on the profitability of high frequency traders provided some insights about the nature of this parasitism. The key mechanism is that they put themselves into position of "forced intermediaries" -- other market participants are forced to sell stock to them and then they sell it back getting a tiny profit from most traction. If they "misunderestimate" the direction of the market they sell position with loss and do it quickly minimizing overnight exposure to a bare minimum.   So they are the same type of intermediaries as theater tickets scalpers.

• a very large volume,
• a very short (usually less the intraday) holding periods,
• a very limited overnight and intraday directional exposure

From the paper:

For each day there are three categories a potential trader must satisfy to be considered a HFT: (1) Trade more than 10,000 contracts; (2) have an end-of-day inventory position of no more than 2% of the total contracts the firm traded that day; (3) have a maximum variation in inventory scaled by total contracts traded of less than 15%. A firm must meet all three criteria on a given day to be considered engaging in HFT for that day. Furthermore, to be labeled an HFT firm for the purposes of this study, a firm must be labeled as engaging in HFT activity in at least 50% of the days it trades and must trade at least 50% of possible trading days.

This small set of firms is then further subdivided into categories based on the extent to which they are providers of liquidity. For any given trade, the liquidity taker is the firm that initiates the transaction, by submitting an order that is marketable against one that is resting in the order book. The counterparty to the trade (who previously submitted the resting limit order) is the liquidity provider. Based on this criterion, the authors partition the set of high frequency traders into three subcategories: aggressive, mixed, and passive:

To be considered an Aggressive HFT, a firm must... initiate at least 40% of the trades it enters into, and must do so for at least 50% of the trading days in which it is active. To be considered a Passive HFT a firm must initiate fewer than 20% of the trades it enters into, and must do so for at least 50% of the trading days during which it is active. Those HFTs that meet neither... definition are labeled as Mixed HFTs. There are 10 Aggressive, 11 Mixed, and 10 Passive HFTs.

This heterogeneity among high frequency traders conflicts with the common claim that such firms are generally net providers of liquidity. In fact, the authors find that "some HFTs are almost 100% liquidity takers, and these firms trade the most and are the most profitable."

The authors are able to compute profitability, risk-exposure, and measures of risk-adjusted performance for all firms. The average HFT makes over $46,000 a day; aggressive firms make more than twice this amount. The standard deviation of profits is five times the mean, and the authors find that "there are a number of trader-days in which they lose money... several HFTs even lose over a million dollars in a single day."Despite the volatility in daily profits, the risk-adjusted performance of high frequency traders is found to be spectacular: 

HFTs earn above-average gross rates of return for the amount of risk they take. This is true overall and for each type... Overall, the average annualized Sharpe ratio for an HFT is 9.2. Among the subcategories, Aggressive HFTs (8.46) exhibit the lowest risk-return tradeoff, while Passive HFTs do slightly better (8.56) and Mixed HFTs achieve the best performance (10.46)... The distribution is wide, with an inter-quartile range of 2.23 to 13.89 for all HFTs. Nonetheless, even the low end of HFT risk-adjusted performance is seven times higher than the Sharpe ratio of the S&P 500 (0.31).

These are interesting findings, but there is a serious problem with this interpretation of risk-adjusted performance. The authors are observing only a partial portfolio for each firm, and cannot therefore determine the firm's overall risk exposure. It is extremely likely that these firms are trading simultaneously in many markets, in which case their exposure to risk in one market may be amplified or offset by their exposures elsewhere. The Sharpe ratio is meaningful only when applied to a firm's entire portfolio, not to any of its individual components. For instance, it is possible to construct a low risk portfolio with a high Sharpe ratio that is composed of several high risk components, each of which has a low Sharpe ratio.

To take an extreme example, if aggressive firms are attempting to exploit arbitrage opportunities between the futures price and the spot price of a fund that tracks the index, then the authors would have significantly overestimated the firm's risk exposure by looking only at its position in the futures market. Over short intervals, such a strategy would result in losses in one market, offset and exceeded by gains in another. Within each market the firm would appear to have significant risk exposure, even while its aggregate exposure was minimal. Over longer periods, net gains will be more evenly distributed across markets, so the profitability of the strategy can be revealed by looking at just one market. But doing so would provide a very misleading picture of the firms risk exposure, since day-to-day variations in profitability within a single market can be substantial.

The problem is compounded by the fact that there are likely to by systematic differences across firms in the degree to which they are trading in other markets. I suspect that the most aggressive firms are in fact trading across multiple markets in a manner that lowers rather than amplifies their exposure in the market under study. Under such circumstances, the claim that aggressive firms "exhibit the lowest risk-return tradeoff" is without firm foundation.

Despite these problems of interpretation, the paper is extremely valuable because it provides a framework for thinking about the aggregate costs and benefits of high frequency trading. Since contracts in this market are in zero net supply, any profits accruing to one set of traders must come at the expense of others:

From whom do these profits come? In addition to HFTs, we divide the remaining universe of traders in the E-mini market into four categories of traders: Fundamental traders (likely institutional), Non-HFT Market Makers, Small traders (likely retail), and Opportunistic traders... HFTs earn most of their profits from Opportunistic traders, but also earn profits from Fundamental traders, Small traders, and Non-HFT Market Makers. Small traders in particular suffer the highest loss to HFTs on a per contract basis.

The operational costs incurred by such firms include payments for data feeds, computer systems, co-located servers, exchange fees, and highly specialized personnel. Most of these costs do not scale up in proportion to trading volume. Since the least active firms must have positive net profitability in order to survive, the net returns of the most aggressive traders must therefore be substantial.

In thinking about the aggregate costs and benefits of all this activity, it's worth bringing to mind Bogle's law:

It is the iron law of the markets, the undefiable rules of arithmetic: Gross return in the market, less the costs of financial intermediation, equals the net return actually delivered to market participants.

As far as price discovery is concerned, high frequency trading is based on a strategy of information extraction from market data. This can speed up the response to changes in fundamental information, and maintain price consistency across related assets. But the heavy lifting as far as price discovery is concerned is done by those who feed information to the market about the earnings potential of publicly traded companies. This kind of research cannot (yet) be done algorithmically.

A great deal of trading activity in financial markets is privately profitable but wasteful in the aggregate, since it involves a shuffling of net returns with no discernible effect on production or economic growth. Jack Hirschleifer made this point way back in 1971, when the financial sector was a fraction of its current size. James Tobin reiterated these concerns a decade or so later. David Glasner, who was fortunate enough to have studied with Hirshlefier, has recently described our predicament thus:

Our current overblown financial sector is largely built on people hunting, scrounging, doing whatever they possibly can, to obtain any scrap of useful information — useful, that is for anticipating a price movement that can be traded on. But the net value to society from all the resources expended on that feverish, obsessive, compulsive, all-consuming search for information is close to zero (not exactly zero, but close to zero), because the gains from obtaining slightly better information are mainly obtained at some other trader’s expense. There is a net gain to society from faster adjustment of prices to their equilibrium levels, and there is a gain from the increased market liquidity resulting from increased trading generated by the acquisition of new information. But those gains are second-order compared to gains that merely reflect someone else’s losses. That’s why there is clearly overinvestment — perhaps massive overinvestment — in the mad quest for information.

NEWS CONTENTS

• 20130811 : 2012 Year In Review - Free Markets, Rule of Law, And Other Urban Legends Zero Hedge ( 2012 Year In Review - Free Markets, Rule of Law, And Other Urban Legends Zero Hedge, Aug 11, 2013 )
• 20130811 : Risk and Reward in High Frequency Trading ( Risk and Reward in High Frequency Trading, )
• 20120923 : Chicago Fed Sounds The Alarm on High Frequency Trading by Susie Madrak ( September 22, 2012 , Crooks and Liars )
• 20120908 : High-Frequency Trading of Stocks Is Two Critics' Target - ( NYTimes.com )
• 20110731 : "Time to Take Stock" by By Sell on News, a macro equities analyst. ( July 31, 2011 , naked capitalism (Cross posted from MacroBusiness) )
• 20110507 : Preventing the Next Flash Crash by EDWARD E. KAUFMAN Jr. AND CARL M. LEVIN ( May 5, 2011 , NYTimes.com )
• 20101211 : Sergey Aleynikov Guilt of Stealing Goldman Trading Code - NYTimes.com ( Sergey Aleynikov Guilt of Stealing Goldman Trading Code - NYTimes.com, Dec 11, 2010 )
• 20101211 : The Aleynikov Code " InvestmentWatch ( The Aleynikov Code " InvestmentWatch, )
• 20101009 : Markets: Very Big Multithreaded Software Apps That Crash ( Markets: Very Big Multithreaded Software Apps That Crash, Oct 09, 2010 )
• 20101009 : 60 Minutes: How HST is Changing Wall Street ( 60 Minutes: How HST is Changing Wall Street, Oct 09, 2010 )
• 20100831 : Bank of America Now Proudly Exporting HFT Market Death And Destruction To Asia by Tyler Durden ( Bank of America Now Proudly Exporting HFT Market Death And Destruction To Asia , Aug 31, 2010 )
• 20100831 : Scientific Proof That High Frequency Trading Induces Adverse Changes In Market Microstructure And Dynamics, And Puts Market Fairness Under Question by Tyler Durde ( Scientific Proof That High Frequency Trading Induces Adverse Changes In Market Microstructure And Dynamics, And Puts Market Fairness Under Question , )
• 20100831 : COMPUTERIZED FRONT RUNNING: HOW A COMPUTER PROGRAM DESIGNED TO SAVE THE FREE MARKET TURNED INTO A MONSTER by Ellen Brown ( )

Old News ;-)

[Aug 11, 2013] 2012 Year In Review - Free Markets, Rule of Law, And Other Urban Legends Zero Hedge

Risk and Reward in High Frequency Trading

A paper on the profitability of high frequency traders has been attracting a fair amount of media attention lately. Among the authors is Andrei Kirilenko of the CFTC, whose earlier study of the flash crash used similar data and methods to illuminate the ecology of trading strategies in the S&P 500 E-mini futures market. While the earlier work examined transaction level data for four days in May 2010, the present study looks at the entire month of August 2010. Some of the new findings are startling, but need to be interpreted with greater care than is taken in the paper.

High frequency traders are characterized by large volume, short holding periods, and limited overnight and intraday directional exposure:

For each day there are three categories a potential trader must satisfy to be considered a HFT: (1) Trade more than 10,000 contracts; (2) have an end-of-day inventory position of no more than 2% of the total contracts the firm traded that day; (3) have a maximum variation in inventory scaled by total contracts traded of less than 15%. A firm must meet all three criteria on a given day to be considered engaging in HFT for that day. Furthermore, to be labeled an HFT firm for the purposes of this study, a firm must be labeled as engaging in HFT activity in at least 50% of the days it trades and must trade at least 50% of possible trading days.

Of more than 30,000 accounts in the data, only 31 fit this description. But these firms dominate the market, accounting for 47% of total trading volume and appearing on one or both sides of almost 75% of traded contracts. And they do this with minimal directional exposure: average intraday inventory amounts to just 2% of trading volume, and the overnight inventory of the median HFT firm is precisely zero.

This small set of firms is then further subdivided into categories based on the extent to which they are providers of liquidity. For any given trade, the liquidity taker is the firm that initiates the transaction, by submitting an order that is marketable against one that is resting in the order book. The counterparty to the trade (who previously submitted the resting limit order) is the liquidity provider. Based on this criterion, the authors partition the set of high frequency traders into three subcategories: aggressive, mixed, and passive:

To be considered an Aggressive HFT, a firm must... initiate at least 40% of the trades it enters into, and must do so for at least 50% of the trading days in which it is active. To be considered a Passive HFT a firm must initiate fewer than 20% of the trades it enters into, and must do so for at least 50% of the trading days during which it is active. Those HFTs that meet neither... definition are labeled as Mixed HFTs. There are 10 Aggressive, 11 Mixed, and 10 Passive HFTs.

This heterogeneity among high frequency traders conflicts with the common claim that such firms are generally net providers of liquidity. In fact, the authors find that "some HFTs are almost 100% liquidity takers, and these firms trade the most and are the most profitable."

Given the richness of their data, the authors are able to compute profitability, risk-exposure, and measures of risk-adjusted performance for all firms. Gross profits are significant on average but show considerable variability across firms and over time. The average HFT makes over $46,000 a day; aggressive firms make more than twice this amount. The standard deviation of profits is five times the mean, and the authors find that "there are a number of trader-days in which they lose money... several HFTs even lose over a million dollars in a single day."

Despite the volatility in daily profits, the risk-adjusted performance of high frequency traders is found to be spectacular:

HFTs earn above-average gross rates of return for the amount of risk they take. This is true overall and for each type... Overall, the average annualized Sharpe ratio for an HFT is 9.2. Among the subcategories, Aggressive HFTs (8.46) exhibit the lowest risk-return tradeoff, while Passive HFTs do slightly better (8.56) and Mixed HFTs achieve the best performance (10.46)... The distribution is wide, with an inter-quartile range of 2.23 to 13.89 for all HFTs. Nonetheless, even the low end of HFT risk-adjusted performance is seven times higher than the Sharpe ratio of the S&P 500 (0.31).

These are interesting findings, but there is a serious problem with this interpretation of risk-adjusted performance. The authors are observing only a partial portfolio for each firm, and cannot therefore determine the firm's overall risk exposure. It is extremely likely that these firms are trading simultaneously in many markets, in which case their exposure to risk in one market may be amplified or offset by their exposures elsewhere. The Sharpe ratio is meaningful only when applied to a firm's entire portfolio, not to any of its individual components. For instance, it is possible to construct a low risk portfolio with a high Sharpe ratio that is composed of several high risk components, each of which has a low Sharpe ratio.

To take an extreme example, if aggressive firms are attempting to exploit arbitrage opportunities between the futures price and the spot price of a fund that tracks the index, then the authors would have significantly overestimated the firm's risk exposure by looking only at its position in the futures market. Over short intervals, such a strategy would result in losses in one market, offset and exceeded by gains in another. Within each market the firm would appear to have significant risk exposure, even while its aggregate exposure was minimal. Over longer periods, net gains will be more evenly distributed across markets, so the profitability of the strategy can be revealed by looking at just one market. But doing so would provide a very misleading picture of the firms risk exposure, since day-to-day variations in profitability within a single market can be substantial.

The problem is compounded by the fact that there are likely to by systematic differences across firms in the degree to which they are trading in other markets. I suspect that the most aggressive firms are in fact trading across multiple markets in a manner that lowers rather than amplifies their exposure in the market under study. Under such circumstances, the claim that aggressive firms "exhibit the lowest risk-return tradeoff" is without firm foundation.

Despite these problems of interpretation, the paper is extremely valuable because it provides a framework for thinking about the aggregate costs and benefits of high frequency trading. Since contracts in this market are in zero net supply, any profits accruing to one set of traders must come at the expense of others:

From whom do these profits come? In addition to HFTs, we divide the remaining universe of traders in the E-mini market into four categories of traders: Fundamental traders (likely institutional), Non-HFT Market Makers, Small traders (likely retail), and Opportunistic traders... HFTs earn most of their profits from Opportunistic traders, but also earn profits from Fundamental traders, Small traders, and Non-HFT Market Makers. Small traders in particular suffer the highest loss to HFTs on a per contract basis.

Within the class of high frequency traders is another hierarchy: mixed firms lose to aggressive ones, and passive firms lose to both of the other types.

The operational costs incurred by such firms include payments for data feeds, computer systems, co-located servers, exchange fees, and highly specialized personnel. Most of these costs do not scale up in proportion to trading volume. Since the least active firms must have positive net profitability in order to survive, the net returns of the most aggressive traders must therefore be substantial.

In thinking about the aggregate costs and benefits of all this activity, it's worth bringing to mind Bogle's law:

It is the iron law of the markets, the undefiable rules of arithmetic: Gross return in the market, less the costs of financial intermediation, equals the net return actually delivered to market participants.

The costs to other market participants of high frequency trading correspond roughly to the gross profitability of this small set of firms. What about the benefits? The two most commonly cited are price discovery and liquidity provision. It appears that the net effect on liquidity of the most aggressive traders is negative even under routine market conditions. Furthermore, even normally passive firms can become liquidity takers under stressed conditions when liquidity is most needed but in vanishing supply.

As far as price discovery is concerned, high frequency trading is based on a strategy of information extraction from market data. This can speed up the response to changes in fundamental information, and maintain price consistency across related assets. But the heavy lifting as far as price discovery is concerned is done by those who feed information to the market about the earnings potential of publicly traded companies. This kind of research cannot (yet) be done algorithmically.

A great deal of trading activity in financial markets is privately profitable but wasteful in the aggregate, since it involves a shuffling of net returns with no discernible effect on production or economic growth. Jack Hirschleifer made this point way back in 1971, when the financial sector was a fraction of its current size. James Tobin reiterated these concerns a decade or so later. David Glasner, who was fortunate enough to have studied with Hirshlefier, has recently described our predicament thus:

Our current overblown financial sector is largely built on people hunting, scrounging, doing whatever they possibly can, to obtain any scrap of useful information - useful, that is for anticipating a price movement that can be traded on. But the net value to society from all the resources expended on that feverish, obsessive, compulsive, all-consuming search for information is close to zero (not exactly zero, but close to zero), because the gains from obtaining slightly better information are mainly obtained at some other trader's expense. There is a net gain to society from faster adjustment of prices to their equilibrium levels, and there is a gain from the increased market liquidity resulting from increased trading generated by the acquisition of new information. But those gains are second-order compared to gains that merely reflect someone else's losses. That's why there is clearly overinvestment - perhaps massive overinvestment - in the mad quest for information.

To this I would add the following: too great a proliferation of information extracting strategies is not only wasteful in the aggregate, it can also result in market instability. Any change in incentives that substantially lengthens holding periods and shifts the composition of trading strategies towards those that transmit rather than extract information could therefore be both stabilizing and growth enhancing. Posted by Rajiv at 12/07/2012 05:42:00 AM ShareThis

[Sep 23, 2012] Chicago Fed Sounds The Alarm on High Frequency Trading By Susie Madrak

September 22, 2012 | Crooks and Liars

This is quite the mess. I'm reading lobbyist Jeff Connaughton's stunning book "Payoff: Why Wall Street Always Wins", and he goes into great detail about his stint as chief of staff to then-Sen. Ted Kaufman (D-DE) as they tried in vain to get the SEC to address this very issue. Quite the eye opener: Basically, the SEC doesn't do a damned thing unless Wall Street lets them. Add to that the fact that these trades are so complicated, so esoteric, even the traders don't always understand them - let alone the regulators. It's a casino, and brokers object to even a 50-millisecond delay. Kaufman did predict a flash crash, and the SEC did take notice - by finally agreeing to ask Wall Street for data about these trades. Good luck with that!

Why is it important? Because it means the retail trader (you) will never, ever get accurate information about the markets. It's being manipulated by these high-speed trades and you'll never really know.

That's why this Chicago Fed studyis important:

The Chicago Federal Reserve paper, How to Keep Markets Safe in the Era of High-Speed Trading, prattled of a laundry list of the most recent high frequency trading debacles including Knight Capital as well as others. Yet in spite of these increasingly frequent stock market disasters, even basic risk controls are not implemented. Why? They claim it would slow down their trading systems.

Industry and regulatory groups have articulated best practices related to risk controls, but many firms fail to implement all the recommendations or rely on other firms in the trade cycle to catch an out-of-control algorithm or erroneous
trade. In part, this is because applying risk controls before the start of a trade can slow down an order, and high-speed trading firms are often under enormous pressure to route their orders to the exchange quickly so as to capture a trade at the desired price.

While the paper focuses on events, contained within is a solid example of really bad software engineering. The Chicago Fed found code wasn't even tested, literally changes are being made on the fly on live production servers not just putting those trades at risk but the entire system as well.

Another area of concern is that some firms do not have stringent processes for the development, testing, and deployment of code used in their trading algorithms. For example, a few trading firms interviewed said they deploy new trading strategies quickly by tweaking old code and placing it into production in a matter of minutes.

Perhaps financial organizations should consider hiring some real engineers who know a thing or two about software design instead of what they are doing. No American who is worth their salt, including those specializing in advanced mathematics, would ever change, on the fly, algorithms on a live server, dealing with billions of dollars.

The study also found out of whack fictional financial mathematics, referred to as algorithms, being designed as well.

Chicago Fed staff also found that out-of-control algorithms were more common than anticipated prior to the study and that there were no clear patterns as to their cause. Two of the four clearing BDs/FCMs, two-thirds of proprietary trading firms, and every exchange interviewed had experienced one or more errant algorithms.

The report amplifies just astounding irresponsibility and engineering incompetence. Can you imagine someone in a nuclear facility implementing software changes on the fly? Can you imagine air traffic control algorithms refusing to put in safety and error checks, claiming that slows down real time air traffic routing execution?

The Chicago Fed does give some recommendations in their report:

• Limits on the number of orders that can be sent to an exchange within a specified period of time
• A "kill switch" that could stop trading at one or more levels
• Intraday position limits that set the maximum position a firm can take during one day
• Profit-and-loss limits that restrict the dollar value that can be lost.

[Sep 08, 2012] High-Frequency Trading of Stocks Is Two Critics' Target - Matt Rainey

The man wrote that the financial markets had become "treacherous waters" and suggested that the senator read "Broken Markets," which, he wrote, "exposes our disgusting and corrupt market system today."

NYTimes.com

Joseph Saluzzi in the office of Themis Trading in New Jersey. Mr. Saluzzi and his business partner, Sal Arnuk, wrote a book criticizing high-frequency trading.

TICKER tape: it's an enduring image of Wall Street. The paper is gone but the digital tape runs on, across computer and television screens. Those stock quotations scurrying by on CNBC are, for many, the pulse of American capitalism.

But Sal L. Arnuk doesn't really believe in the tape anymore - at least not in the one most of us see. That tape, he says, doesn't tell the whole truth.

That might come as a surprise, given that Mr. Arnuk is a professional stockbroker. But suddenly, and improbably, he has emerged as a leading critic of the very market in which he works. He and his business partner, Joseph C. Saluzzi, have become the voice of those plucky souls who try to swim with Wall Street's sharks without getting devoured.

From workaday suburban offices here, across from a Gymboree, these two men are taking on one of the most powerful forces in finance today: high-frequency trading. H.F.T., as it's known, is the biggest thing to hit Wall Street in years. On any given day, this lightning-quick, computer-driven form of trading accounts for upward of half of all of the business transacted on the nation's stock markets.

It's a staggering development - and one that Mr. Arnuk, 46, and Mr. Saluzzi, 45, say has contributed to the hair-raising flash crashes and computer hiccups that seem to roil the markets with alarming frequency. Many ordinary Americans have grown wary of the stock market, which they see as the playground of Google-esque algorithms, powerful banks and secretive, fast-money trading firms.

To which Mr. Arnuk and Mr. Saluzzi say: enough. At their Lilliputian brokerage firm, they are tilting at the giants of high-frequency trading and warning - loudly - of the dangers they pose. Mr. Saluzzi was the only vocal critic of H.F.T. appointed to a 24-member federal panel that is studying the topic. Posts from the blog that the two men write have been packaged into a book, "Broken Markets: How High Frequency Trading and Predatory Practices on Wall Street are Destroying Investor Confidence and Your Portfolio," (FT Press, 2012) which was published in June. They are even getting fan mail.

But they are also making enemies.

Proponents of high-frequency trading call them embittered relics - quixotic, old-school stockbrokers without the skills to compete in sophisticated, modern markets. And, in a sense, those critics are right: they are throwbacks. Both men say they wish Wall Street could go back to a calmer, simpler time, all the way back to, say, 2004 - before the old exchange system splintered and murky private markets sprang up and computers could send the Dow into 1,000-point spasms. (The bottle of Tums Ultra 1000 and the back-pain medication on Mr. Arnuk's desk here are a testament to their frustrations.)

They have proposed solutions that might seem simple to the uninitiated but look radical to H.F.T. insiders. For instance, the two want to require H.F.T. firms to honor the prices they offer for a stock for at least 50 milliseconds - less than a wink of an eye, but eons in high-frequency time.

On the Friday before Labor Day weekend, Mr. Arnuk was sitting in the office of Themis Trading, the brokerage firm he founded with Mr. Saluzzi a decade ago. It is little more than a fluorescent-lit single room; the most notable decoration is a poster signed in gold ink by the cast of "The Sopranos." Above Mr. Arnuk, the tape scrolled by on the Bloomberg Television channel. But other numbers danced on four computer screens on his desk. Mr. Arnuk kept moving his cursor across those screens, punching in figures, trying to find the best price for a customer who wanted to buy a particular stock.

His eyes scanned the stock's going price on 13 stock exchanges across the nation. The investing public is now using so many exchanges because new regulation and technology have rewritten the old rules and let in new players. It's not just the Big Board or the Nasdaq anymore. It's also the likes of BATS and Direct Edge.

Mr. Arnuk then eyed the stock's price on dozens of other trading platforms - private ones most people can't see. Known as the dark pools, they help hedge funds and other big-money players trade in relative secrecy.

Everywhere, different prices kept flickering on the screens. Computers at high-speed trading firms, Mr. Arnuk said, were issuing buy and sell orders and then canceling them almost as fast, testing the market. It can be hell on human brokers. On the tape, the stock's price was unchanged, but beneath the tape, things were changing all the time.

"They will flicker to see who is not flickering," Mr. Arnuk said of H.F.T. computers. "The guy who is not flickering is the idiot - the real investor."

From his desk a few feet away, Mr. Saluzzi chimed in: "That's how the game is played now."

ON the afternoon of May 6, 2010, shortly before 3 o'clock, the stock market plummeted. In just 15 minutes, the Dow tumbled 600 points - bringing its loss for the day to nearly 1,000. Then, just as fast, and just as inexplicably, it sprang back nearly 600 points, like a bungee jumper.

It was one of the most harrowing moments in Wall Street history. And for many people outside financial circles, it was the first clue as to just how much new technology was changing the nation's financial markets. The flash crash, a federal report later concluded, "portrayed a market so fragmented and fragile that a single large trade could send stocks into a sudden spiral." It turned out that a big mutual fund firm had sold an unusually large number of futures contracts, setting off a feedback loop among computers at H.F.T. firms that sent the market into a free fall.

Despite computers' many benefits - faster, cheaper trades, and mind-boggling analytics - they have been causing problems on Wall Street for years. Technology has fostered so-called hot money - money that quickly shifts from one stock to another, or one market to another, always seeking higher returns. Computer-driven program trading was developed in the 1980s and was a contributing factor in the 1987 market crash, though it wasn't the main culprit, as many initially thought.

Since the 2010 flash crash, mini flash crashes have occurred with surprising regularity in a wide range of individual stocks. Last spring, a computer glitch scuttled the initial public offering of one of the nation's largest electronic exchanges, BATS, and computer problems at the Nasdaq stock market dogged the I.P.O. of Facebook.

And last month, Knight Capital, a brokerage firm at the center of the nation's stock market for almost a decade, nearly collapsed after it ran up more than $400 million of losses in minutes, because of errant technology. It was just the latest high-profile case of Wall Street computers gone wild.

High-frequency traders didn't cause all of these problems. But these traders and their computers embody the escalating technological arms race raging across financial industry.

The stock market establishment says the recent mishaps distract from the enormous benefits that technology has brought. The new trading outlets have democratized the system and made it possible to trade any time, anywhere. Competition has forced exchanges and trading firms to reduce the commissions they charge. George U. Sauter, chief investment officer at the mutual fund giant Vanguard, has said the shift saved hundreds of millions of dollars for Vanguard investors.

James Angel, a professor at Georgetown University and a member of the board of Direct Edge, said Mr. Arnuk and Mr. Saluzzi were stoking irrational fears of a market that is providing good returns to investors. Mr. Angel compared them to people "who gripe that their cellphone is too complicated, ignoring the fact that 20 years ago they didn't even have a cellphone."

But Mr. Arnuk and Mr. Saluzzi say such assessments ignore the hidden costs of high-frequency trading, particularly the market instability it can create.

They say firms that dominate the market often stop trading during times of crisis, when they are needed the most. They also contend that ordinary investors are paying more for their stocks, not less, because computerized traders pick up information about stock orders and push up prices before orders can be filled. Traders of all sorts have split orders into smaller and smaller blocks, making it harder for everyone to complete some types of basic trades.

"They took one of the most simple processes in the world, matching up supply and demand, and made it such a complicated labyrinth," Mr. Arnuk said.

He and Mr. Saluzzi trace the roots of the market's current travails to a number of regulatory changes over the last two decades. But they give the starring role to a set of rules adopted in 2007 by the Securities and Exchange Commission. The rules are known as the Regulation National Market System, or Reg N.M.S.

Before those rules, computerized trading had been steadily growing, but the market was still dominated by the human traders on the floor of the New York Stock Exchange. Reg N.M.S. broke the Big Board's domination by requiring that orders be sent to the trading platform with the best price. This seemingly small change led to a proliferation of new platforms, like dark pools. It also put a premium on speed, giving an advantage to firms that could place orders first and take advantage of minuscule price differences among exchanges.

At Themis, Mr. Arnuk and Mr. Saluzzi soon noticed they were having trouble completing what previously were easy orders. When they tried to buy stock at the price listed on an exchange, the price would disappear almost as soon as they entered their order. Then it would reappear - at a penny or more higher.

The two began by voicing complaints in morning notes to clients. Soon they moved on to industry publications like Traders Magazine, then to the mainstream news media.

In July 2009, or 10 months before the flash crash, Mr. Saluzzi squared off on CNBC against Irene Aldridge, a prominent advocate of high-frequency trading. Mr. Saluzzi declared that high-frequency traders could get an early peek at buy and sell orders, giving them an edge over everyone else. The H.F.T. crowd could simply jump in front of ordinary investors, he said.

"There is nothing illegal about what you are doing," Mr. Saluzzi told Ms. Aldridge. "But, you know, it is not ethical."

Ms. Aldridge was incensed.

"How dare you accuse us of being unethical - you're unethical," she shot back. "We are cutting your margins - of brokerages like yours - because you cannot compete, because you do not have the proper skills."

As the host, Sue Herera, tried to cut to a commercial, the two shouted backed and forth.

"Yeah, hope your computer doesn't blow up tomorrow, O.K.?" Mr. Saluzzi snarled at Ms. Aldridge. "Make sure the fuses are O.K."

The line proved prophetic.

SAL ARNUK and Joe Saluzzi are unlikely Wall Street gadflies. Mr. Arnuk grew up in modest surroundings in the Bay Ridge section of Brooklyn, Mr. Saluzzi in Sheepshead Bay. They met after college in back-office jobs at Morgan Stanley and bonded over weekend softball games and commutes. Both soon realized they didn't have the connections to move up at a white-shoe Wall Street firm.

Talking to them now, it's clear that both have a certain anti-establishment bent, at least as far as Wall Street is concerned. Mr. Arnuk says he filled the wall of his dorm room at what is now Binghamton University with rejection letters from financial firms. After business school, their scrappy attitudes led them to computerized trading, the upstart part of the industry in the 1990s. They spent nearly a decade at Instinet, one of the original off exchange trading platforms.

When they struck out on their own and founded Themis in 2002, they intended to use their technological expertise to help clients navigate the markets. But soon enough, they say, the computers took over, with formulas pushing share prices up and down regardless of anything happening at the underlying company.

Mr. Saluzzi acknowledges that computerized trading has hurt firms like Themis, which executes trades on behalf of clients. Many former Themis clients now trade via algorithms, or algos, with no human involvement. But both men say human brokers can often navigate complex markets better than computers. Last year, Themis's revenue was up 10 percent, despite an overall decline in trading volume, they say. This year, revenue is holding steady.

One Themis client, Derek Laub, director of trading at Jetstream Capital, a small investment firm just outside Nashville, says he turns to Themis because Mr. Arnuk and Mr. Saluzzi provide a human touch, and help him avoid falling prey to more sophisticated H.F.T. firms. Trading through Themis costs Mr. Laub a bit more - about 1 cent a share, total - but that's still cheaper than the 3 cents or 4 cents charged by many big banks. More important, Mr. Laub says he likes Themis because it speaks for small investment firms that don't have the time or wherewithal to examine every problem in the market structure or to take on the big trading firms.

"You feel like there is at least someone out there who is going to give the other side of the argument," Mr. Laub said.

The views of Mr. Arnuk and Mr. Saluzzi are gaining more traction with industry insiders. The head of the New York Stock Exchange said this summer that the pursuit of speed had gone too far. In debates with Mr. Saluzzi, some H.F.T. executives have agreed that the fragmentation of the markets is now doing more harm than good for investors. And after the breakdown at Knight Capital, the S.E.C. called for a round table on market technology; it will be held on Oct. 2.

BUT Mr. Arnuk and Mr. Saluzzi do not think that big change is on the way. For their part, they don't want to do away with computerized trading altogether - just the frantic developments of the last few years. "I don't want to go back to 1987, but 2004 wouldn't be so bad," Mr. Arnuk says.

Their message has won them a following among many ordinary Americans who, rightly or wrongly, have concluded that the Wall Street game is rigged. Before heading out for Labor Day weekend, Mr. Arnuk opened one more example of fan mail - a letter from an Idaho man that also went to Senator Michael D. Crapo, an Idaho Republican.

The man wrote that the financial markets had become "treacherous waters" and suggested that the senator read "Broken Markets," which, he wrote, "exposes our disgusting and corrupt market system today."

Mr. Arnuk smiled. "That's going up on the wall," he said. "I consider it a badge of honor."

A version of this article appeared

[Jul 31, 2011] "Time to Take Stock" by By Sell on News, a macro equities analyst.

July 31, 2011 | naked capitalism (Cross posted from MacroBusiness)

Exactly how did we get into this mess with the capital markets?

• A situation where the global stock of derivatives is over $US600 trillion, which is about twice the capital stock of the world.
• A situation where high frequency trading is over two thirds of the transactions on the NYSE and about the same in the stock markets of the UK and Europe.

Likewise they are over half the action in foreign exchange markets and they are rapidly becoming dominant in the futures market. Andrew Haldane from the Bank of England is arguing against allowing high frequency trading - algorithms chasing algorithms chasing algorithms - from being allowed to proliferate pointing at volatility as the problem:

Speed increases the risk of feasts and famines in market liquidity. HFT [high-frequency traders] contribute to the feast through lower bid-ask spreads. But they also contribute to the famine if their liquidity provision is fickle in situations of stress.

Haldane noted that relative to gross domestic product, the equity market capitalisation of the US, Europe and Asia had not grown since 2000, suggesting that "the contribution of equity markets to economic growth … has been static".

Little wonder, when you consider that companies are putting themselves in the hands of algorithms.

I think this conclusion, which many come to, is to some extent a blind alley. Because the volume of transactions is higher - when it is claimed that it adds liquidity this is a circular argument, like saying "the more we trade the more we trade" - it should mean that "volatility" at least on basic measures, is lower. The trades are made around normative models so they will tend to re-inforce those norms. Right up until the moment when the market does not behave with regard to norms, and then they suddenly start doing weird things, such as the so called "Flash Crash". So it is probably correct to say that there is less volatility. It is also beside the point.

A better question is: Why do we think liquidity is a good thing?" Answer, because it facilitates trade around the exchange of information. "Information about what?" one might then ask. "The company in which the investment is being made," is the answer. Does algorithmic trading exchange information about the performance of the company? No, it is only working off information about trading behaviour. Ergo, it may increase "liquidity" but it is not fulfilling the purpose of liquidity.

That kind of shift to traders working mostly off what traders do, rather than assessing the value of what is being traded, has become an absolute plague. It has taken over most Western financial markets. Hedging, for example, used to be all about hedging bets to protect the underling exchanges (usually wheat, or pork bellies or physical things). Now, hedging is all about reading behaviour, which then leads to other hedging strategies that are based on reading the hedging behaviour, and so on.

So the disappearing point is part of the problem. In our "anthrosphere" we are increasingly staring at each other's navels in the financial markets, trying to make money and sustainable wealth out of ether. That is part of the problem. Regulators forgetting what the PURPOSE of financial markets is and instead just trying to stay faithful to the technical explications of that purpose, or utility. A colossal abrogation of responsibility, in other words, fuelled by thoughtlessness or intellectual laziness (Haldane is a notable exception).

But I think there is another problem. A growing mismatch in TIME between financial markets and commerce or economic activity. I can remember in the currency meltdowns of the last 20 years how the explanations in retrospect for why Russia or Thailand or Mexico or Indonesia "deserved" what they got. They were always plausible enough, if usually circular arguments.

But then you looked at what happened to those economies that had experienced crises and the impact was completely out of alignment. In a matter of weeks, there would be a massive re-rating of the currencies. No economy changes that fast. The problems, if there were problems and sometimes it was just a trading fiction, had usually accumulated for years. After the crises, the economies would take years to recover from the shock. It seemed to me that the misalignment in time is what is fundamentally wrong with this kind of financial behaviour.

The misalignment is even more extreme with high frequency trading, where micro-seconds are the basic unit. How can the exchange of information about a stock occur in such small periods? Obviously they can't. There is a mismatch. Money should be aligned with what it is supposed to be representing, and that includes aligned in its temporal structure. For at least two decades, that alignment has been progressively picked apart, and now it is reaching endemic proportions.

In terms of its intellectual origins, this has a lot to do with the quasi-scientific methods used by economists and financiers. In science, time is just a dimension of space. The point of creating scientific "rules" is to say that every TIME the rule applies. Time, in other words, has to be eliminated as a problem.

Which is why science applies so poorly to human behaviour, because humans are always changing in time. It is why scientific models have extremely limited application to markets, because every time things are different - at least in their timing. For instance, I may reasonably conclude that the $A will fall, and be right because it will probably revert back t a norm. But what I need to know to make money is the time it will happen.

What one notices about all the fundamental analyses is that, while persuasive, they are extremely limited because they don't tell you when the predicted events will occur. Those traders who sniff "the times" often do much better.

Time, in other words, cannot be eliminated from human behaviour, it is front and centre.

Which is why I would submit that the misalignment in time between financial market instruments and that which they are supposed to represent is not just extremely dangerous, it is fundamentally inhuman.

Foppe:

But then you looked at what happened to those economies that had experienced crises and the impact was completely out of alignment. In a matter of weeks, there would be a massive re-rating of the currencies. No economy changes that fast. The problems, if there were problems and sometimes it was just a trading fiction, had usually accumulated for years. After the crises, the economies would take years to recover from the shock. It seemed to me that the misalignment in time is what is fundamentally wrong with this kind of financial behaviour.

A very nice point.

One wonders what would be against executing all trades simultaneously once every second or few seconds. The stock exchanges wouldn't like it, obviously, as they could no longer earn money by selling colocated server space, and neither would the banks, but it seems nice to fantasize about stuff like that sometimes.

Mark P:

"Andrew Haldane from the Bank of England is arguing against allowing high frequency trading … from being allowed to proliferate pointing at volatility as the problem."

Well, sure, HFT has meant volatility problems, and it allows trading absolutely detached from market fundamentals - and if that's true, what's the point of such a stock market?

Most perniciously, however, HFT has allowed the creation of a Potemkin stock market over the last three years, which has in turn enabled many MSM business outlets to continually sell a 'recovering' U.S. economy where very large numbers of Americans aren't going to the wall, though in reality the wall is exactly where those Americans are going.

http://en.wikipedia.org/wiki/Potemkin_village

Washington and Wall Street have colluded happily on what would be recognized - if this iteration of the technologies and techniques involved weren't ahead of the grasp of most folks and of the regulators' brief - as market manipulation on a massive scale. The Zero Hedge crowd may be wacked out about many things, but on this particular score they are right. They are right. They are right.

And it's very telling that this administration in DC seems perfectly okay with the fact that, in return for helping to provide a (relatively) happy-face Potemkin market, the financial industry gets to use HFT as, effectively, another financial industry tax on real trading, skimming millions every day from regular pension fund and mom-and-pop investors, etc.

As the article above notes, the main argument HFT defenders offer is that it brings vastly greater liquidity to the market.

But what kind of liquidity? The article has vague complaints about HFT creating 'structural mismatches' and being 'fundamentally inhuman.' No, it's worse than that. The liquidity HFT provides is the kind that, if it were healthcare insurance, would be healthcare insurance set up so that just when you suffer an illness or injury and need it is precisely when it disappears.

Here's an interview with as an establishment figure as you can get, a former Nasdaq Stock Market president and thirty-year veteran of the industry called Alfred R. Berkeley III: -

http://www.tradersmagazine.com/news/pipeline-blocks-high-frequency-trading-al-berkeley-104059-1.html?zkPrintable=true

Berkeley: A recent TABB Group report said that 73 percent of trading is attributed to high-frequency traders.… We have optimized our market for hedge funds to make money. How do they make money? They front-run institutional trades. Traditional long-only traders have had to go into defensive mode.'

Interviewer: 'Does high-frequency trading have an impact on the quality of liquidity in the market?'

Berkeley: 'Of course it does. The best way to see that is to look at the size at the inside and see how many orders are canceled when it looks like momentum is going from the buyer to the seller. And the average trade size is just lousy.…'

Got that? The money quote is 'see how many orders are canceled when it looks like momentum is going from the buyer to the seller.' Better to think of this so-called liquidity as churn.

What sort of churn is it, though? Clearly, much of the 'liquidity' high frequency traders are adding to the mix is simply to match trades created by other HFT traders.

Furthermore, there's no way that Goldman Sachs's Sigma X, or any of the other HFT players can absolutely ensure that their algorithms are not trading with themselves.

Really, how can GS ensure it's not trading with itself - for example, either a different arm of GS or another batch of computers running another algorithm?

In fact, insider esimates are internal order matching happens all the time in dark pools. With Sigma X estimates being around 50 percent when I looked in 2009.

And this is legal -

Rule 17A-7: "Exemption of Certain Purchase or Sale Transactions Between an Investment Company and Certain Affiliated Persons Thereof.". http://www.law.uc.edu/CCL/InvCoRls/rule17a-7.html

Effectively, then, HFT players could just split their prop. desks into two or more groups and then trade a single stock back and forth. As long as the desired result is achieved - that is, off-loading the artificially ramped-up shares onto third parties at the end of the day - they don't need to care. It's the ultimate churn machine.

John Merryman

This is really just late stage cancer. The problem starts with interest rates set lower than market appreciation that creates speculative feedback loops pumping up the amount of money borrowed into existence in order to gamble, rather than invest. Now it's just the tail wagging the dog, as this enormous amount of leverage overwhelms all other political and economic functions.

Jessica

There are two deep factors at work.

1. The advances in data processing and communication have made this kind of hyper-speed trading possible. It is also in its nature very desirable for those involved. Profits over time are a function of how much you make doing something divided by how long it takes you. If you can make money in microseconds, even tiny amounts multiply out to huge amounts because they can be repeated so many times. There is no way to make that much money doing anything practical in the real world, so capital will tend to flow to this hyper-speed trading.
2. The elites in the most advanced economies have disintegrated in place over the past few decades. They are still there, but they no longer act in a coherent manner as elites as a whole. The different fragments act on their own, for their own.

This also means that they are defaulting on any and all social contracts (explicit or implicit) because there is no one there to hold up there end of the bargain. I believe that the root cause of this is that the economy has long needed to transition to centering on knowledge production (in a very broad sense), but we do not yet know how to organize a society for that purpose*. And much of the "social technology" that we have that did work in the industrial phase just gets in the way now. The challenge we face is so fundamental and demands qualities so different from those our societies developed during the industrial era that we do not even realize that we are stuck in a cul-de-sac. *

To run a knowledge-centered economy, we must do two things simultaneously: turn the knowledge loose and appropriately motivate (compensate) those who produce, maintain, and distribute it.

We can do one at a time, but not both. From this perspective, much of what we now have of intellectual production is dependent on the creation of artificial knowledge scarcity, ie ignorance.

For any Tolkien geeks, we live in an era run by orcs. What I am pointing is the world of elves that our orcs are the poor, twisted imitation of. There is no Sauron. It is orcs all the way to the top. We just need to re-elf.

Jessica:

Oh, and we live under a vile enchantment that makes many of us wonder why our elites seem to act like orcs not elves and somehow not be able to see that it is because they _are_ orcs.

Paul Tioxon:

I get to use my 2 favorite quotes.

Today's scientists have substituted mathematics for experiments, and they wander off through equation after equation, and eventually build a structure which has no relation to reality. – Nikola Tesla

The problems are solved, not by giving new information, but by arranging what we have already known. Philosophy is a battle against the bewitchment of our intelligence by means of language. – Ludwig Wittgenstein PHILOSOPHICAL INVESTIGATIONS Part I, Aphorism 109, 3rd Edition, G.E.M. Anscombe Translation.

Needless to say, algorithms are a unnatural language, but language none the less, which has now, through technological instrumentation, not only bewitched our intelligence, but our economic productivity. We have confused the ink on the page with meaning and truth.

Mozillo Underwritin'

Technology has already saved all of us, daily. Algorithms can be used as weapons if we've allow it, that's what we should see here – not overwhelming complexity, but a high speed shell game.

Goldman Fuchs is on the phone to the FBI to keep their proprietary tool hidden in the corporate coffer. Consider DRM, consider all the other information hoarding aggression from Wall Street, look at the laws they want to keep their control, 'tis yet another sign o' the times.

Sleeper

Well, the article is not really too suprising but I wonder if the relatively narrow range that the stock market has traded in 1,000 to 1,200 points or there abouts is due to the HFT skimming the profits from the market.

After all if we are to believe the the averages the market overall should grow by some 8% per year. (And really folks let's not let the 8% be a sticking point it could be 2% or 5% or some other number.) And since the market has a relatively narrow trading range the money has to go somewhere.

i

The article is spot on. The "wisdom of crowds" works when each individual is out independently gathering their own information. When the information comes not from independent research, but only from gathering the opinions of others (or inferring opinion from behavior), feedback distortion takes over and information becomes increasingly unreliable.

This more or less describes the markets today (Thanks, internet!). Worse, we've automated the process of feedback distortion with computer algorithms. The stock market, for example, no longer represents underlying value of companies in any meaningful sense of the word.

[May 07, 2011] Preventing the Next Flash Crash By EDWARD E. KAUFMAN Jr. AND CARL M. LEVIN

May 5, 2011 | NYTimes.com

ONE year ago, the stock market took a brief and terrifying nose-dive. Almost a trillion dollars in wealth momentarily vanished. Shares in blue-chip companies were traded at absurdly low prices. High-frequency traders, who use computers to look for microscopic price differences in stocks on different exchanges and other trading venues, stopped trading, while others immediately sold whatever they bought, mainly to each other, in what has been called "hot potato" trading.

We haven't had a repeat of last year's "flash crash," but algorithmic trading has caused mini-flash crashes since, and surveys suggest that most investors and analysts believe it's only a matter of time before the Big One.

They're right to be afraid. The top cop for our financial markets remains inexcusably blind to the activities of high-speed computer trading.

After the flash crash, the Securities and Exchange Commission moved quickly to apply a Band-Aid in the form of circuit breakers to limit daily price moves. Then it proposed a long-overdue consolidated audit trail, to plug the gaps in reporting requirements that prevent the efficient tracking and policing of orders and trades. It spent months painstakingly using antiquated methods to reconstruct and study the trading data during the flash crash. With the Commodity Futures Trading Commission, it convened a joint advisory committee, which presented an array of recommendations in February. And it continued to dither.

The consequences of inaction are dire. If the average investor comes to believe stocks are valued not on the basis of a company's expected future earnings but on the machinations of computers trading against other computers for speed and advantage, our stock markets will have become a casino.

The explosion in computer-based trading has occurred over the past decade as the S.E.C. adopted rules that allowed dozens of new trading venues to compete for stock orders and accelerated the move toward high-frequency trading, which now accounts for 70 percent of daily stock-trading volume.

While competition has lowered trading costs and in some cases improved efficiency, the result has been a confusing amalgam of more than 50 electronic trading networks, some of which are designed to hide large block trades, and traditional exchanges, which are governed by outmoded regulations that do not require full transparency. High-frequency traders navigate this maze with ever more sophisticated technology - and armies of computer and math specialists - to find and exploit slight price variations.

Yes, both volume and volatility in the equity markets have been declining in recent months, but the centrality of high-frequency trading has not diminished. Moreover, high-frequency traders have gone beyond trading stocks to futures, options, bonds, currencies and other asset classes - and are making incursions in foreign markets. The next flash crash could be more pervasive than last year's, as global asset markets become increasingly correlated through the convergence of computer-driven trading strategies.

Why hasn't the S.E.C. acted? Defenders would say that Congressionally imposed deadlines for instituting the Dodd-Frank overhaul of financial regulations have overwhelmed the commission and forced it to put changes to the equity markets on the back burner.

But the paralysis at the S.E.C. runs much deeper. It's been 20 years since Congress gave it the authority to require large-volume traders to make more detailed disclosures; 18 months since the commission's chairman, Mary L. Schapiro, said it would use that authority; 13 months since the agency proposed a rule to do so; and three months since the advisory committee recommended proceeding with "urgency" on the audit trail.

Meanwhile, even Ms. Schapiro has publicly expressed worry that our markets no longer adequately perform their main functions: helping companies to raise capital to innovate and grow and helping long-term investors to contribute to the American economy while building a retirement nest egg. Mutual fund outflows continued unabated after the flash crash through the end of 2010, an indication that ordinary investors are fleeing the market.

In response, the S.E.C. should work with the C.F.T.C. to establish the audit trail, which would allow real-time monitoring of electronic trading; stop trading venues from catering unfairly to high-speed traders at the expense of regular investors; make high-frequency traders bear their fair share of the costs involved in heavy, instantaneous flow of electronic messages, which would discourage strategies to stuff the system with orders that are immediately canceled; and rethink rules that give too much priority to the rapid-fire orders that high-frequency traders rely upon.

More is at stake than the confidence of small investors. A survey by the consulting firm Grant Thornton shows that initial public offerings by small companies have declined over the past 15 years. The profits to be made in supporting small-cap stocks have dried up as Wall Street has focused obsessively on leverage and high-volume trading.

One promising idea being floated is an experimental market, with rules tailored to support the capitalization of the fastest-growing companies, many of them start-ups that are drivers of job creation.

America's capital markets, once the envy of the world, have been transformed in the name of competition that was said to benefit investors. Instead, this has produced an almost lawless high-speed maze where prices can spiral out of control, spooking average investors and start-up entrepreneurs alike.

The flash crash should have sounded an alarm. Unfortunately, the regulators are still asleep.

Edward E. Kaufman Jr. was a Democratic senator from Delaware from 2009 to 2010. Carl M. Levin, a Democratic senator from Michigan, is the chairman of the Permanent Subcommittee on Investigations.

[Dec 11, 2010] Sergey Aleynikov Guilt of Stealing Goldman Trading Code - NYTimes.com

adirondax:

OK, I get the notion that Goldman wanted to go after this guy. Presumably he stole proprietary trading software. Fine. Or not fine in Mr. Aleynikov's case.

What I DON'T get is how Goldman's structured finance salesmen skated away from prosecution after knowingly selling bogus mortgage-backed securities to customers for literally years. This was nothing short of fraud. And, there was a conspiracy, presumably among Goldman's senior management, to commit the fraud. Everybody on the Street knew, particularly as time went on, that this mortgage-backed securities house of cards was going to implode. How do we know they knew? Because they took out securities positions, meaning derivatives, against the very same gems that they were selling. Derivatives that would pay out once the securities that they sold went bust.

Again, I get why this poor sod is going to do time. What I don't get is why the rest of bloody Goldman Sach's management team isn't going to be sharing a cell with him!

Shame on the NYC prosecutor's office for going after Aleynikov without also going after Goldman's senior management crew. Shame on them! The Goldman management's perpetration of fraud almost brought down the global financial system. This guy Aleynikov? His crime was petty larceny at best.

GD

If the jury unanimously believe he intentionally stole the code for profit, then he broke the law and should be punished.

On the other hand, high frequency and flash trading is the GREATEST financial crime in the history of this country. Far worse than Madoff or any Ponzi scheme because we're talking billions upon billions of dollars of millions upon millions of hard working people (essentially the same effect as Madoff, only it doesn't drain people of everything all at once). It is absurd a company should be able to review trades before they're even processed and make pennies (times many zeroes of shares). It is blatant thievery and I don't understand (and perhaps I really don't) how this hasn't been made illegal yet.

Obviously the big financial houses have the money to lobby effectively, but in the end someone has to realize it will end in financial collapse.

I assume those expensive pillows the CEO's must help them to get some sleep at night. Cause I don't see how any human being could ethically think its ok.

Tim

Can you define high frequency trading, please, for your readers? As I understand it, HFT is computerized front running, making deals before the market can see the data, and also is subject to abuse, for example, executing numerous trades to sniff out the buyer's top price thus selling at a higher amount than if the deal had been done in the open market where all buyers and sellers could see the trade.

The Aleynikov Code " InvestmentWatch

Sergey Aleynikov, a computer programmer, is accused of stealing Goldman Sach's computer code when he left the company in July 2009. His trial is about to begin. See "What We Are Not Supposed To Know". The problem with the trial is neither the defendant nor what he did or did not do. The problem is what he allegedly stole. Many market observers are tuned into this case because they are convinced that our markets have been overtaken by fraudulent high frequency trading. See "The Market Is Cornered" for a discussion on why their concerns are warranted.

Our government, through incompetence or a conflict of interest, has effectively allowed large investment banks and hedge funds to prey on investors. Not surprisingly, high frequency traders are doing an outstanding job in their depredations. If one googles 'high frequency trading', he or she will see numerous articles and videos decrying its use in ripping off mutual funds, pension funds, and retail investors. Look at the statistically impossible consecutive winning trading days and the obscene profits generated at the proprietary trading desks of large Wall Street investment banks and you will understand why there is a crime behind every fortune. Either high frequency traders are cheating or they have developed algorithms that endow computers with psychic powers heretofore unknown to humanity. If the village idiot can figure out that high frequency traders must be cheating on a galactic scale, so should the Securities and Exchange Commission. It could not be more obvious. If the SEC is not regulating and overseeing our capital markets to ensure a level playing field, why are they still in existence? Where are the cops?

It is a natural human reaction for Americans, who struggle every day to put food on their table and a roof over their heads, to be incensed at the arrogance of Wall Street firms who insist on huge salaries and bonuses no matter how much damage they inflict on the economy. What is more difficult to stomach is the fact that our government actively protects the interests of the banksters at every turn. Americans see the injustice when banks are bailed out and given guarantees that make a complete mockery of the concept of moral hazard. Americans are offended when they see our government regulatory agencies littered with former Wall Street employees. They seethe when they watch Wall Street CEOs parade into and out of the White House as if they own the joint. Americans consider it an affront when they see representatives of the major banks sitting at the table of the Federal Reserve and dispensing advice that serve their self-interest at the expense of Main Street Americans. See "Triumph of the Plutocrats".

[Oct 09, 2010] Markets: Very Big Multithreaded Software Apps That Crash

By Barry Ritholtz - October 8th, 2010, 6:03AM

At one point in history, equity markets were giant discounting mechanisms, taking in all available information about the economy, earnings, sentiment, then spitting out future expectations of value.

The proliferation of HFT and Algo traders, according to a fascinating take from Ars Technica, has changed that. Our stock markets now behave no differently than a giant multithreaded software application. And on May 6th, 2010, that software app crashed:

"To be a single multithreaded app, as opposed to an unrelated collection of multithreaded apps, the different threads must somehow interact with one another. In other words, the threads must share and jointly modify some kind of state.What state do the various apps and algorithms that run on Wall Street's machines share? At the very least, every part of the market shares the quote feed, and some parts are even more tightly coupled than that. But let's focus on the quotes.

The price of, say, AAPL at any given moment is a numerical value that represents the output of one set of concurrently running processes, and it also acts as the input for another set of processes. AAPL, then, is one of many hundreds of thousands of global variables that the market-as-software uses for message-passing among its billions of simultaneously running threads. Does it really matter that those threads are running on separate machines at different institutions?

. . . [If] the market really is essentially an enormous piece of multithreaded software, then I'm not entirely sure what kind of rabbit hole we've all gone down."

Fascinating metaphor . . .Source:
The stock market as a single, very big piece of multithreaded software
Jon Stokes
Ars Technica, October 7, 2010
http://arstechnica.com/business/news/2010/10/you-say-stock-market-i-say-ginormous-multithreaded-application.ars

Julia Chestnut:

Oh great. So now does one take the blue pill, or the red pill?

Unfortunately, this pretty accurately describes what I think of the market at this point. The question then becomes that soooooo much of modern neoliberal economic theory is based on market efficiency and perfect information getting incorporated into market prices - if this is true, what does it mean? Can one ever really put this genie back in the bottle?

dougc:

Now, consider the fact that there is 223 Trillion in outstanding US derivative exposure ,a record. It appears that TBTF are ganbling with our money again. Wordwide derivative exposure is 3X us. Sleep tight, hope the computer programs don't bite.

dlipton:

If the market is a distributed, concurrent system then it's the regulatory agencies and exchange rules that should generally be coordinating the threads. That being said, the threads (i.e. the market participants) should try to ensure their own safety.

I find it difficult to get too worked up about HFT's. At the end of the day if they occasionally introduce market inefficiency then that provides opportunities for long-term investors. If somebody wants to sell me an asset for a fraction of my perceived value I will be only too happy to oblige. It just seems unfair that the rules allow market participants to yank back quotes that are below the top of the book; orders should sweep the book.

manitoumonk:

There is nothing sinister about multi-threaded apps. Every modern web-server is multi-threaded and the world doesn't seem the worse for the wear. The operating system I'm working on has 632 threads running at this moment. The computer is still functional.

The core of the problem is simply that markets are complex and the various moving parts sometimes interact in ways that produces a surprisingly bad outcome. The fact that we use computers is irrelevant. I'm much more disturbed that prop trading is legal. It's like going into wal-mart and finding that half the people in the store are all about buying goods, then returning them 2 minutes later, over and over again.

bergsten:

October 8th, 2010 at 1:39 pm
The author makes some reasonable points (and, folks, the issue is the algorithms (think cooking recipe) and the relative speed of execution (how fast the machines are running and how quickly they are able to access and modify data - so "choice of operating system" is really irrelevant - sorry, 2+2 doesn't get a better answer under Linux than Windows, etc.).

What would make HFT's into a large, single multithreaded application is if their algorithms are virtually identical (otherwise one would expect somewhat different behavior from each).

This is very possible, given that programmers and consultants move from company to company implementing the same stuff. And, they read the same papers, and talk to each other. And their masters want to copy all of their competitors.

This is why, in aeronautics, redundant systems are created with completely different algorithms, so that if one fails (say, due to a programming bug), the others can correct it before you fly into the sun.

As things (seem to) stand now, if one goes berserk, they all do.

Screw this, I'm starting my own bank.

[Oct 09, 2010] 60 Minutes: How HST is Changing Wall Street

By Barry Ritholtz - October 7th, 2010, 5:20PM

Sunday, 60 Minutes turns its eye to HFT's impact on Wall Street.

Excerpt:

"New Jersey stock trader Manoj Narang says his firm has never had a losing week because his super computers are fast enough to capitalize on split-second opportunities in the market. Narang and other traders are using a legal but controversial technique called "high-frequency trading."

It played a role in a 15-minute, 600-point market meltdown last spring now known as the "Mini Market Crash." Correspondent Steve Kroft talks to Narang in a rare chance to see such a business up close. He also speaks to SEC Chair Mary Schapiro – who has high frequency trading in her regulatory sights – and others for a "60 Minutes" report to be broadcast Sunday, Oct. 10, at 7 p.m. ET/PT.

High frequency traders rely on mathematicians and computer experts to write electronic trading programs and they use expensive computers to run them. Many of the country's large financial institutions do high frequency trading and it is estimated that from 50 to 70 percent of all U.S. stock trades are made this way. Humans are becoming less involved.

But computers can create turmoil in the market, and the results can be devastating. The market crash last May 6 was triggered by one computer algorithm that sold $4.1 billion of securities in a 20-minute period. The high-frequency trading programs' response to that – buying many of them up and selling them just as fast – exacerbated an already bad situation.

Full article at link.

>

Source:
How Speed Traders Are Changing Wall Street
Steve Kroft
CBS, Oct. 7, 2010

[Aug 31, 2010] Bank of America Now Proudly Exporting HFT Market Death And Destruction To Asia by Tyler Durden

08/30/2010 | zero hedge

Feel like it is time to spread the market annihilation love courtesy of "any minute now" HFT-induced flash crashes? Have no fear, Bank of America is here. "High-frequency trading in the US and Europe has grabbed most attention in the market, but similar activities are quietly taking off in Asia as well." Thusly begins a pamphlet by BofA/ML's Carrie Cheung which explains the tremendous "advantages" that HFTs offer to any local market. Not mentioned is that these advantages include drastic market destabilization, and that the "attention" is of the "get that thing the hell out of here" variety. At least we get to learn some very useful facts about the proliferation of the little bloodsucking algos in the Pacific rim such as...

1. "high-frequency trading firms today account for about 20-25% of the TSE turnover - ZH translation: the TSE will crash only one third lower when the Flash Crash hits it"
2. "the market microstructure changes introduced at the same time (i.e. new tick sizes) cut the average spread of Nikkei 225 stocks by 25%, making it much cheaper to trade - ZH tranlsation: in HFT jargon, trade is a synonym for stuff cancelable quotes and/or churn",
3. "The new platform allows for higher-frequency trading, where algorithms are used to make thousands of trades in milliseconds, thereby allowing firms to profit from tiny spreads and market imbalances." - ZH translation: we make frontrunning fast and easy, or your Other People's Money back;
4. "Furthermore, the introduction of co-location services by Japanese exchanges, together with third-party proximity services, further enhances the platform for high-frequency trading firms in Japan." - ZH translation: Cisco stands to make at least one or two cents in incremental EPS by letting the biggest market manipulators frontrun and scalp at the speed of light; judging by its latest results, it needs it;
5. "It is estimated that high-frequency trading activity will account for 30-40% of liquidity by the end of 2010." - ZH translation: the crash after the next, will be about half the amplitude of the May 6 crash;
6. The Kospi Index Option is the world's most heavily traded derivative. It is highly correlated with the US markets, has a low transaction cost and hence is heavily traded by retail investors. These elements make it an attractive market for a lot of foreign investors including the highfrequency trading group. - ZH translation: Japanese housewives will first all buy together, then will be all shaken out together, losing all their money at the same time, with just Made in New York Atari making a killing;
7. China is a market most foreign investors want to access, but the entry barriers are high. However, the recent successful launch of CSI 300 futures will no doubt make it an important market to keep an eye on. The futures contract, while currently limited to just domestic traders, now has the second largest turnover in the world, following Kospi. - ZH translation: we are preparing to blow up the world.

In conclusion, use Bank of America cause their HFT expertise in setting landmines in Asian stock markets is second to none: "Asia's markets are evolving gradually. In addition, the region's growing economic power and upgrades in technology will definitely make this the next hot spot for high-frequency trading."

Full two page ad of BofA exporting WMDs to the Pacific rim:

Scientific Proof That High Frequency Trading Induces Adverse Changes In Market Microstructure And Dynamics, And Puts Market Fairness Under Question by Tyler Durde

07/12/2010 | zero hedge

Up until recently, any debate between proponents and opponents of High Frequency Trading would typically be represented by heated debates of high conviction on either side, with discussions rapidly deteriorating into ad hominem attacks and the producer screaming 'cut to commercial' to prevent fistfights. Luckily, all this is about to change. In a research paper by Reginald Smith of the Bouchet Franklin Institute in Rochester titled "Is high-frequency trading inducing changes in market microstructure and dynamics?" the author finds that he "can clearly demonstrate that HFT is having an increasingly large impact on the microstructure of equity trading dynamics. Traded value, and by extension trading volume, fluctuations are starting to show self-similarity at increasingly shorter timescales. Values which were once only present on the orders of several hours or days are now commonplace in the timescale of seconds or minutes. It is important that the trading algorithms of HFT traders, as well as those who seek to understand, improve, or regulate HFT realize that the overall structure of trading is influenced in a measurable manner by HFT and that Gaussian noise models of short term trading volume fluctuations likely are increasingly inapplicable." In other words, the author finds ample evidence that during the past decade (on the NASDAQ) and especially since the 2005 revision of Reg NMS (on the NYSE), stock trading increasingly demonstrates "self similar" fractal patterns, resulting in volatility surges, recursive feedback loops, and a market structure which is increasingly becoming a product of the actual trading mechanism. In the process, as demonstrated by a Hurst Exponent gravitating increasingly further away from 0.5 (i.e., Brown Noise territory), the Markov Process nature of stock trading is put under question, and thus the whole premise of an efficient market has to be reevaluated. Simply said: HFT has been shown to affect the fairness of trading.

The paper is, needless to say, a must read for everyone who has an even passing interest in stock trading and market regulation (alas, yes, that would mean the SEC, and Congress). And while one of the key qualities of the paper is presenting the history and implications of High Frequency Trading, and its rise to market dominance primarily as a result of the revision of Reg NMS, allowing stock trading to become a free for all for every algo, and ECN/ATM imaginable, the key findings are what makes it unique. In analyzing stochastic processes and fractal phenomena, and concluding that the Hurst Exponent of transactions that involve less than 1,500 shares per trade (and especially less than 250 - a distinct subdomain relegated to HFT strategies) is no longer 0.5, the author validates the skepticism of all those who for over a year (such as Zero Hedge) have claimed that the direct and increasing involvement of HFT is an de-evolutionary process that is leading to increasing market fragmentation, self-sameness, destabilization, and volatility, offset merely by allegedly improved liquidity, which incidentally disappears on a moment's notice when the negative side-effects of HFT overwhelm the positive, such as was the case on May 6. Furthermore, the authors find that the type of fractal recursive feedback loops inspired by increasing HFT participation lead to spikes in correlation: "Correlations previously only seen across hours or days in trading time series are increasingly showing up in the timescales of seconds or minutes." And due to the implied fractal nature of trading (think standing waves, fern leaves, sandy beaches, and all other goodies unleashed upon the world courtesy of Benoit Mandelbrot), it appears investors now have to consider such quixotic issues as Lorenzian Attractors when it comes to simple trading. What is most troubling, is that micro similarities, as postulated by non-linear theory, tend to rapidly evolve into massively scaled topological disturbances, and thus a few simple resonant trades can rapidly avalanche into a major market destabilizing event.... such as that seen on May 6.

While the math of the article is a little daunting, and the author appears to derive a peculiar satisfaction from throwing the Riemann Zeta function in the general mathematical stew (incidentally, with the prevalent IQ of Zero Hedge readers being sufficiently high to allow at least a valiant effort at proving the Riemann Hypothesis, we hope some of our more industrious readers take it upon themselves to venture and pocket the generous proceeds from the Millennium Prize, for which we will be content to receive a mere pittance as a donation for proffering this forum), the observations and conclusions are water tight:

Given the complex nature of HFT trades and the frequent opacity of firm trading strategies, it is difficult to pinpoint exactly what about HFT causes a higher correlation structure. One answer could be that HFT is the only type of trading that can exhibit trades that are reactive and exhibit feedback effects on short timescales that traditional trading generates over longer timescales.

Another cause may be the nature of HFT strategies themselves. Most HFT strategies can fall into two buckets Lehoczky and Schervish (2009):

(i) Optimal order execution: trades whose purpose is to break large share size trades into smaller ones for easier execution in the market without affecting market prices and eroding profit. There are two possibilities here. One that the breaking down of large orders to smaller ones approximates a multiplicative cascade which can generate self-similar behavior over time Mandelbrot (1974). Second, the queuing of chunks of larger orders under an M/G/1 queue could also generate correlations in the trade flow. However, it is questionable whether the "service time", or time to sell shares in a limit order, is a distribution with infinite variance as this queuing model requires.

(ii) Statistical arbitrage: trades who use the properties of stock fluctuations and volatility to gain quick profits. Anecdotally, these are most profitable in times of high market volatility. Perhaps since these algorithms work through measuring market fluctuations and reacting on them, a complex system of feedback based trades could generate self-similarity from a variety of yet unknown processes.

Since firm trade strategies are carefully guarded secrets, it is difficult to tell which of these strategies predominate and induces most of the temporal correlations.

When it comes to the interplay of optimal order execution and statistical arbitrage, it can easily be seen why large block splitting into child orders could conceive a self-similar trading pattern that reverberates across the market, in an increasingly micro-correlated and fractal marketplace. In the course of events on May 6, it is perfectly feasible that as many mutual funds commenced dumping large blocks of stock, assorted algorithms had to work overtime to split these orders into millions of small trade blocks. And with statistical arbitrage models programmed to game and front-run large order blocks by diving the intentions of repeated micro orders, it becomes all too clear how a rapid selling event can rapidly culminate into a bid-less environment where both the stat arb and order execution HFT algorithms are all on the same side of the boat. Consider the market action from the past several days as indicative of micro volume accumulation by HFTs, which is only offset by mega volume dumping - once all the HFTs are forced to unwind and go to cash, the actual principal liquidity providers who in their desperation become liquidity takers, suddenly find themselves with no recourse but to hit any bid. Which is why the NYSE explanation of Liquidity Replenishment Points is nothing but complete BS - the market meltdown had nothing to do with selective order routing to non-NYSE venues, and everything to do with a fractal implosion, in which, as Nassim Taleb would explain, the Hurst Exponent briefly went from 0.5 to infinity minus 1, and the entire market became correlated with itself.

Of course if the paper is correct, and the empirical evidence presented in it is sufficient to eliminate doubt, it means that in the coming years we will have an exponentially growing number of days in which May 6-type event will recur over and over.

The paper's conclusion:

Given the above research results, we can clearly demonstrate that HFT is having an increasingly large impact on the microstructure of equity trading dynamics. We can determine this through several main pieces of evidence. First, the Hurst exponent H of traded value in short time scales (15 minutes or less) is increasing over time from its previous Gaussian white noise values of 0.5. Second, this increase becomes most marked, especially in the NYSE stocks, following the implementation of Reg NMS by the SEC which led to the boom in HFT. Finally, H > 0.5 traded value activity is clearly linked with small share trades which are the trades dominated by HFT traffic.

In addition, this small share trade activity has grown rapidly as a proportion of all trades. The clear transition to HFT influenced trading noise is more easily seen in the NYSE stocks than with the NASDAQ stocks except NWSA. The main exceptions seem to be GENZ and GILD in the NASDAQ which are less widely traded stocks. There are values of H consistently above 0.5 but not to the magnitude of the other stocks. The electronic nature of the NASDAQ market and its earlier adoption of HFT likely has made the higher H values not as recent a development as in the NYSE, but a development nevertheless.

Given the relative burstiness of signals with H > 0.5 we can also determine that volatility in trading patterns is no longer due to just adverse events but is becoming an increasingly intrinsic part of trading activity. Like internet traffic Leland et. al. (1994), if HFT trades are self-similar with H > 0.5, more participants in the market generate more volatility, not more predictable behavior.

There are a few caveats to be recognized. First, given the limited timescale investigated, it is impossible to determine from these results alone what, if any, long-term effects are incorporating the short-term fluctuations. Second, it is an open questions whether the benefits of liquidity offset the increased volatility. Third, this increased volatility due to self-similarity is not necessarily [TD: but very well could be as described above] the cause of several high profile crashes in stock prices such as that of Proctor & Gamble (PG) on May 6, 2010 or a subsequent jump (which initiated circuit breakers) of the Washington Post (WPO) on June 16, 2010. Dramatic events due to traceable causes such as error or a rogue algorithm are not accounted for in the increased volatility though it does not rule out larger events caused by typical trading activities. Finally, this paper does not investigate any induced correlations, or lack thereof, in pricing and returns on short timescales which is another crucial issue.

Traded value, and by extension trading volume, fluctuations are starting to show self-similarity at increasingly shorter timescales. Values which were once only present on the orders of several hours or days are now commonplace in the timescale of seconds or minutes. It is important that the trading algorithms of HFT traders, as well as those who seek to understand, improve, or regulate HFT realize that the overall structure of trading is influenced in a measurable manner by HFT and that Gaussian noise models of short term trading volume fluctuations likely are increasingly inapplicable.

As for evidence, we refer readers to the paper itself, but in a nutshell, the authors find that over the years, on both the NYSE (after Reg NMS revision in 2005) and on the Nasdaq (from before, as the Nasdaq was the original spawn of HFT strategies), as the prevalent share bucket moved from greater than 1,000 shares per trade, to 250 or less, direct evidence of increasing HFT dominance, especially coupled with previous Tabb group evidence that over 70% of all trading is conducted by HFT, the Hurst Exponent of all trading increasingly moved away from 0.5, and has hit as high as 0.7 in some case: a stunning result which puts the entire stochastic nature of stock markets in question! (see charts below).

Charting the average size per trade since 2002:

And charting the Hurst Exponent as calculated by the authors in a variety of Nasdaq and NYSE stocks:

We are confident that this paper will serve as the guiding light to much more comparable research, due to the unique approach the author takes in analyzing stock behavior. In moving away from a traditional and simplistic Gaussian frame, Smith isolates the very nature of the problem, which like any other non-linear system, and thus prone to Black Swanness, has to be sought in the plane of fractal geometry. Luckily, the author provides the one elusive observation which many market participants (at least those whose livelihoods are not tied into the perpetuation of the destructive HFT processes) had long sensed was on the tips of their tongues, yet the only comprehensible elucidation was the trite and overworn "the market is broken." At least now we know that this is a fact.

Unfortunately, as the paper requires slightly more than first grade comprehension and math skills, it will never be read by anyone at the SEC, or those in Congress, who are pretending to be conducting Financial Regulation Reform, when the items described in this paper are precisely the things that any reform should be addressing.

And while we again urge everyone to read the full paper, below we present the section of the paper that does a terrific job in explaining the arrival of HFT, its development over the ages, and its parasitic role in market structure.

Appendix:

A brief history of the events leading up to high frequency trading

In 1792, as a new nation worked out its new constitution and laws, another less heralded revolution began when several men met under a Buttonwood tree, and later coffee houses, on Wall St. in New York City to buy and sell equity positions in fledgling companies. An exclusive members club from the beginning, the New York Stock Exchange (NYSE) rapidly grew to become one of the most powerful exchanges in the world. Ironically, even the non-member curbside traders outside the coffee houses gradually evolved into over-the-counter (OTC) traders and later, the NASDAQ. A very detailed and colorful history of this evolution is given in Markham and Harty (2008); Harris (2003).

Broadly, the role of the exchange is to act as a market maker for company stocks where buyers with excess capital would like to purchase shares and sellers with excess stock would like to liquidate their position. Several roles developed in the NYSE to encourage smooth operation and liquidity. There came to be several types of market makers for buyers and sellers known as brokers, dealers, and specialists. The usual transaction involves the execution of a limit order versus other offers. A limit order, as contrasted to a market order which buys or sells a stock at the prevailing market rate, instructs the purchase of a stock up to a limit ceiling or the sale of a stock down to a limit floor. Brokers act on behalf of a third-party, typically an institutional investor, to buy or sell stock according to the pricing of the limit order. Dealers, also known as market-makers, buy and sell stock using their own capital, purchasing at the bid price and selling at the ask price, pocketing the bid-ask spread as profit. This helps ensure market liquidity. A specialist acts as either a broker or dealer but only for a specific list of stocks that he or she is responsible for. As a broker, the specialist executes trades from a display book of outstanding orders and as a dealer a specialist can trade on his or her own account to stabilize stock prices.

The great rupture in the business-as-usual came with the Great Depression and the unfolding revelations of corrupt stock dealings, fraud, and other such malfeasance. The Securities and Exchange Commission (SEC) was created by Congress in 1934 by the Securities Exchange Act. Since then, it has acted as the regulator of the stock exchanges and the companies that list on them. Over time, the SEC and Wall Street have evolved together, influencing each other in the process.

By the 1960s, the volume of traded shares was overwhelming the traditional paper systems that brokers, dealers, and specialists on the floor used. A"paperwork crisis" developed that seriously hampered operations of the NYSE and led to the first electronic order routing system, DOT by 1976. In addition, inefficiencies in the handling of OTC orders, also known as "pink sheets", led to a 1963 SEC recommendation of changes to the industry which led the National Association of Securities Dealers (NASD) to form the NASDAQ in 1968. Orders were displayed electronically while the deals were made through the telephone through"market makers" instead of dealers or specialists. In 1975, under the prompting of Congress, the SEC passed the Regulation of the National Market System, more commonly known as Reg NMS, which was used to mandate the interconnectedness of various markets for stocks to prevent a tiered marketplace where small, medium, and large investors would have a specific market and smaller investors would be disadvantaged. One of the outcomes of Reg NMS was the accelerated use of technology to connect markets and display quotes. This would enable stocks to be traded on different, albeit connected, exchanges from the NYSE such as the soon to emerge electronic communication networks (ECNs), known to the SEC as alternative trading systems (ATS).

In the 1980s, the NYSE upgraded their order system again to SuperDot. The increasing speed and availability computers helped enable trading of entire portfolios of stocks simultaneously in what became known as program trading. One of the first instances of algorithmic trading, program trading was not high-frequency per se but used to trade large orders of multiple stocks at once. Program trading was profitable but is now often cited as one of the largest factors behind the 1987 Black Monday crash. Even the human systems broke down, however, as many NASDAQ market makers did not answer the phones during the crash.

The true acceleration of progress and the advent of what is now known as high frequency trading occurred during the 1990s. The telecommunications technology boom as well as the dotcom frenzy led to many extensive changes. A new group of exchanges became prominent. These were the ECN/ATS exchanges. Using new computer technology, they provided an alternate market platform where buyers and sellers could have their orders matched automatically to the best price without middlemen such as dealers or brokers. They also allowed complete anonymity for buyers and sellers. One issue though was even though they were connected to the exchanges via Reg NMS requirements, there was little mandated transparency. In other words, deals settled on the ECN/ATS were not revealed to the exchange. On the flip side, the exchange brokers were not obligated to transact with an order displayed from an ECN, even if it was better for their customer.

This began to change, partially because of revelations of multiple violations of fiduciary duty by specialists in the NYSE. One example, similar to the soon to be invented 'flash trading', was where they would "interposition" themselves between their clients and the best offer in order to either buy low from the client and sell higher to the NBBO (National Best Bid and Offer; the best price) price or vice versa.

In 1997, the SEC passed the Limit Order Display rule to improve transparency that required market makers to include offers at better prices than those the market maker is offering to investors. This allows investors to know the NBBO and circumvent corruption.

However, this rule also had the effect of requiring the exchanges to display electronic orders from the ECN/ATS systems that were better priced. The SEC followed up in 1998 with Regulation ATS. Reg ATS allowed ECN/ATS systems to register as either brokers or exchanges. It also protected investors by mandating reporting requirements and transparency of aggregate trading activity for ECN/ATS systems once they reach a certain size.

These changes opened up huge new opportunities for ECN/ATS systems by allowing them to display and execute quotes directly with the big exchanges. Though they were required to report these transactions to the exchange, they gained much more. In particular, with their advanced technology and low-latency communication systems, they became a portal through which next generation algorithmic trading and high frequency trading algorithms could have access to wider markets. Changes still continued to accelerate.

In 2000, were two other groundbreaking changes. First was the decimalization of the price quotes on US stocks. This reduced the bid-ask spreads and made it much easier for computer algorithms to trade stocks and conduct arbitrage. The NYSE also repealed Rule 390 which had prohibited the trading of stocks listed prior to April 26, 1979 outside of the exchange. High frequency trading began to grow rapidly but did not truly take off until 2005.

In June 2005, the SEC revised Reg NMS with several key mandates. Some were relatively minor such as the Sub-Penny rule which prevented stock quotations at a resolution less than one cent. However, the biggest change was Rule 611, also known as the Order Protection Rule. Whereas with the Limit Order Display rule, exchanges were merely required to display better quotes, Reg NMS Rule 611 mandated, with some exceptions, that trades are always automatically executed at the best quote possible. Price is the only issue and not counterparty reliability, transaction speed, etc. The opening for high frequency trading here is clear. The automatic trade execution created the perfect environment for high speed transactions that would be automatically executed and not sit in a queue waiting for approval by a market maker or some vague exchange rule. The limit to trading speed and profit was now mostly the latency on electronic trading systems.

The boom in ECN/ATS business created huge competition for exchanges causing traditional exchanges (NYSE & Euronext) to merge and some exchanges to merge with large ECNs (NYSE & Archipelago). In addition, the competition created increasingly risky business strategies to lure customers. CBSX and DirectEdge pioneered 'flash trading' on the Chicago Board of Exchange and the NYSE/NASDAQ respectively where large limit orders would be flashed for 50 milliseconds on the network to paying customers who could then rapidly trade in order to profit from them before public advertisement. Many of these were discontinued in late 2009 after public outcry but HFT was already the dominant vehicle for US equity trading as shown in figure 1. HFT thrives on rapid fire trading of small sized orders and the overall shares/trade has dropped rapidly over the last few years is shown in figure 2. In addition, the HFT strategy of taking advantage of pricing signals from large orders has forced many orders off exchanges into proprietary trading networks called 'dark pools' which get their name from the fact they are private networks which only report the prices of transactions after the transaction has occurred and typically anonymously match large orders without price advertisements. These dark pools allow a safer environment for large trades which (usually) keep out opportunistic high frequency traders. The basic structure of today's market and a timeline of developments are given in figure 3 and figure 4. For more detailed information, see Stoll (2006); McAndrews and Stefandis (2000); Francis et. al. (2009); Mittal (2008); Degryse et. al. (2008); Palmer (2009)

Full paper link here.

COMPUTERIZED FRONT RUNNING: HOW A COMPUTER PROGRAM DESIGNED TO SAVE THE FREE MARKET TURNED INTO A MONSTER by Ellen Brown

April 22, 2010 | webofdebt

While the SEC is busy investigating Goldman Sachs, it might want to look into another Goldman-dominated fraud: computerized front running using high-frequency trading programs.

Market commentators are fond of talking about "free market capitalism," but according to Wall Street commentator Max Keiser, it is no more. It has morphed into what his TV co-host Stacy Herbert calls "rigged market capitalism": all markets today are subject to manipulation for private gain.

Keiser isn't just speculating about this. He claims to have invented one of the most widely used programs for doing the rigging. Not that that's what he meant to invent. His patented program was designed to take the manipulation out of markets. It would do this by matching buyers with sellers automatically, eliminating "front running" – brokers buying or selling ahead of large orders coming in from their clients. The computer program was intended to remove the conflict of interest that exists when brokers who match buyers with sellers are also selling from their own accounts. But the program fell into the wrong hands and became the prototype for automated trading programs that actually facilitate front running.

Also called High Frequency Trading (HFT) or "black box trading," automated program trading uses high-speed computers governed by complex algorithms (instructions to the computer) to analyze data and transact orders in massive quantities at very high speeds. Like the poker player peeking in a mirror to see his opponent's cards, HFT allows the program trader to peek at major incoming orders and jump in front of them to skim profits off the top. And these large institutional orders are our money -- our pension funds, mutual funds, and 401Ks.

When "market making" (matching buyers with sellers) was done strictly by human brokers on the floor of the stock exchange, manipulations and front running were considered an acceptable (if morally dubious) price to pay for continuously "liquid" markets. But front running by computer, using complex trading programs, is an entirely different species of fraud. A minor flaw in the system has morphed into a monster. Keiser maintains that computerized front running with HFT has become the principal business of Wall Street and the primary force driving most of the volume on exchanges, contributing not only to a large portion of trading profits but to the manipulation of markets for economic and political ends.

The "Virtual Specialist": the Prototype for High Frequency Trading

Until recently, most market making was done by brokers called "specialists," those people you see on the floor of the New York Stock Exchange haggling over the price of stocks. The job of the specialist originated over a century ago, when the need was recognized for a system for continuous trading. That meant trading even when there was no "real" buyer or seller waiting to take the other side of the trade.

The specialist is a broker who deals in a specific stock and remains at one location on the floor holding an inventory of it. He posts the "bid" and "ask" prices, manages "limit" orders, executes trades, and is responsible for managing the uninterrupted flow of orders. If there is a large shift in demand on the "buy" side or the "sell" side, the specialist steps in and sells or buys out of his own inventory to meet the demand, until the gap has narrowed.

This gives him an opportunity to trade for himself, using his inside knowledge to book a profit. That practice is frowned on by the Securities Exchange Commission (SEC), but it has never been seriously regulated, because it has been considered necessary to keep markets "liquid."

Keiser's "Virtual Specialist Technology" (VST) was developed for the Hollywood Stock Exchange (HSX), a web-based, multiplayer simulation in which players use virtual money to buy and sell "shares" of actors, directors, upcoming films, and film-related options. The program determines the true market price automatically, by comparing "bids" with "asks" and weighting the proportion of each. Keiser and HSX co-founder Michael Burns applied for a patent for a "computer-implemented securities trading system with a virtual specialist function" in 1996, and U.S. patent no. 5960176 was awarded in 1999.

But things went awry after the dot.com crash, when Keiser's company HSX Holdings sold the VST patent to investment firm Cantor Fitzgerald, over his objection. Cantor Fitzgerald then put the part of the program that would have eliminated front-running on ice, just as drug companies buy up competing patents in order to take them off the market. Instead of preventing front-running, the program was altered so that it actually enhanced that fraudulent practice. Keiser (who is now based in Europe) notes that this sort of patent abuse is illegal under European Intellectual Property law.

Meanwhile, the design of the VST program remained on display at the patent office, giving other inventors ideas. To get a patent, applicants must list "prior art" and then prove that their patent is an improvement in some way. The listing for Keiser's patent shows that it has been referenced by 132 others involving automated program trading or HFT.

Since then, HFT has quickly come to dominate the exchanges. High frequency trading firms now account for 73% of all U.S. equity trades, although they represent only 2% of the approximately 20,000 firms in operation.

In 1998, the SEC allowed online electronic communication networks, or alternative trading systems, to become full-fledged stock exchanges. Alternative trading systems (ATS) are computer-automated order-matching systems that offer exchange-like trading opportunities at lower costs but are often subject to lower disclosure requirements and different trading rules. Computer systems automatically match buy and sell orders that were themselves submitted through computers. Market making that was once done with a "specialist's book" -- something that could be examined and audited -- is now done by an unseen, unaudited "black box."

For over a century, the stock market was a real market, with live traders hotly bidding against each other on the floor of the exchange. In only a decade, floor trading has been eliminated in all but the largest exchanges, such as the New York Stock Exchange (NYSE); and even in those markets, it now co-exists with electronic trading.

Alternative trading systems allow just about any sizable trader to place orders directly in the market, rather than routing them through investment dealers on the NYSE. They also allow any sizable trader with a sophisticated HFT program to front run trades.

Flash Trades: How the Game Is Rigged

An integral component of computerized front running is a dubious practice called "flash trades." Flash orders are permitted by a regulatory loophole that allows exchanges to show orders to some traders ahead of others for a fee. At one time, the NYSE allowed specialists to benefit from an advance look at incoming orders; but it has now replaced that practice with a "level playing field" policy that gives all investors equal access to all price quotes. Some ATSs, however, which are hotly competing with the established exchanges for business, have adopted the use of flash trades to pull trading business away from the exchanges. An incoming order is revealed (or flashed) to a trader for a fraction of a second before being sent to the national market system. If the trader can match the best bid or offer in the system, he can then pick up that order before the rest of the market sees it.

The flash peek reveals the trade coming in but not the limit price – the maximum price at which the buyer or seller is willing to trade. This is what the HFT program figures out, and it is what gives the high-frequency trader the same sort of inside information available to the traditional market maker: he now gets to peek at the other player's cards. That means high-frequency traders can do more than just skim hefty profits from other investors. They can actually manipulate markets.

How this is done was explained by Karl Denninger in an insightful post on Seeking Alpha in July 2009:

"Let's say that there is a buyer willing to buy 100,000 shares of BRCM with a limit price of $26.40. That is, the buyer will accept any price up to $26.40. But the market at this particular moment in time is at $26.10, or thirty cents lower.

"So the computers, having detected via their 'flash orders' (which ought to be illegal) that there is a desire for Broadcom shares, start to issue tiny (typically 100 share lots) 'immediate or cancel' orders - IOCs - to sell at $26.20. If that order is 'eaten' the computer then issues an order at $26.25, then $26.30, then $26.35, then $26.40. When it tries $26.45 it gets no bite and the order is immediately canceled.

"Now the flush of supply comes at, big coincidence, $26.39, and the claim is made that the market has become 'more efficient.'

"Nonsense; there was no 'real seller' at any of these prices! This pattern of offering was intended to do one and only one thing -- manipulate the market by discovering what is supposed to be a hidden piece of information -- the other side's limit price!

"With normal order queues and flows the person with the limit order would see the offer at $26.20 and might drop his limit. But the computers are so fast that unless you own one of the same speed you have no chance to do this -- your order is immediately 'raped' at the full limit price! . . . [Y]ou got screwed for 29 cents per share which was quite literally stolen by the HFT firms that probed your book before you could detect the activity, determined your maximum price, and then sold to you as close to your maximum price as was possible."

The ostensible justification for high-frequency programs is that they "improve liquidity," but Denninger says, "Hogwash. They have turned the market into a rigged game where institutional orders (that's you, Mr. and Mrs. Joe Public, when you buy or sell mutual funds!) are routinely screwed for the benefit of a few major international banks."

In fact, high-frequency traders may be removing liquidity from the market. So argues John Daly in the U.K. Globe and Mail, citing Thomas Caldwell, CEO of Caldwell Securities Ltd.:

"Large institutional investors know that if they start trying to push through a large block of shares at a certain price – even if the block is broken into many small trades on several ATSs and markets -- they can trigger a flood of high-frequency orders that immediately move market prices to the institution's disadvantage. . . . That's why institutions have flocked to so-called dark pools operated by ATSs such as Instinet, and individual dealers like Goldman Sachs. The pools allow traders to offer prices without publicly revealing their identities and tipping their hand."

Because these large, dark pools are opaque to other investors and to regulators, they inhibit the free and fair trade that depends on open and transparent auction markets to work.

The Notorious Market-Rigging Ringleader, Goldman Sachs

Tyler Durden, writing on Zero Hedge, notes that the HFT game is dominated by Goldman Sachs, which he calls "a hedge fund in all but FDIC backing." Goldman was an investment bank until the fall of 2008, when it became a commercial bank overnight in order to capitalize on federal bailout benefits, including virtually interest-free money from the Fed that it can use to speculate on the opaque ATS exchanges where markets are manipulated and controlled.

Unlike the NYSE, which is open only from 10 am to 4 pm EST daily, ATSs trade around the clock; and they are particularly busy when the NYSE is closed, when stocks are thinly traded and easily manipulated. Tyler Durden writes:

"[A]s the market keeps going up day in and day out, regardless of the deteriorating economic conditions, it is just these HFT's that determine the overall market direction, usually without fundamental or technical reason. And based on a few lines of code, retail investors get suckered into a rising market that has nothing to do with green shoots or some Chinese firms buying a few hundred extra Intel servers: HFTs are merely perpetuating the same ponzi market mythology last seen in the Madoff case, but on a massively larger scale."

HFT rigging helps explain how Goldman Sachs earned at least $100 million per day from its trading division, day after day, on 116 out of 194 trading days through the end of September 2009. It's like taking candy from a baby, when you can see the other players' cards.

Reviving the Free Market

So what can be done to restore free and fair markets? A step in the right direction would be to prohibit flash trades. The SEC is proposing such rules, but they haven't been effected yet.

Another proposed check on HFT is a Tobin tax – a very small tax on every financial trade. Proposals for the tax range from .005% to 1%, so small that it would hardly be felt by legitimate "buy and hold" investors, but high enough to kill HFT, which skims a very tiny profit from a huge number of trades.

That is what proponents contend, but a tiny tax might not actually be enough to kill HFT. Consider Denninger's example, in which the high-frequency trader was making not just a few pennies but a full 29 cents per trade and had an opportunity to make this sum on 99,500 shares (100,000 shares less 5 100-lot trades at lesser sums). That's a $28,855 profit on a $2.63 million trade, not bad for a few milliseconds of work. Imposing a .1% Tobin tax on the $2.63 million would reduce the profit to $26,225, but that's still a nice return for a trade that takes less time than blinking.

The ideal solution would fix the problem at its source -- the price-setting mechanism itself. Keiser says this could be done by banning HFT and installing his VST computer program in its original design in all the exchanges. The true market price would then be established automatically, foreclosing both human and electronic manipulation. He notes that the shareholders of his former firm have a good claim for voiding out the sale to Cantor Fitzgerald and retrieving the program, since the deal was never consummated and the investors in HSX Holdings have never received a penny for the sale.

There is just one problem with their legal claim: the paperwork proving it was shipped to Cantor Fitzgerald's offices in the World Trade Center several months before September 2001. Like free market capitalism itself, it seems, the evidence has gone up in smoke.

Dear DK and Friends

For decades, professional investment advisers have continued to teach reliance on "value investing" and "buy and hold" as long-term guides to successful investment. Chief economists and market pundits for financial institutions continue to urge us to keep focused on "market fundamentals" rather than sell when jostled by disruptive events, expecting "efficient markets" to generate a "fair price" in the whirlwind of market trading.

Your recent briefings that covered high frequency trading raised serious doubts about these traditional concepts of how markets work in the highly computerized, hyper trading world of today.

Dark Pools and Flash Orders

High-Frequency (HF) traders thrive on a combination of asymmetric information advantages and extremely short-term profit objectives. Because of their high volume activity, HF traders have information on trades taking place in the "dark pools" of privately arranged transactions. They are also able to initiate almost limitless "flash orders" to ascertain the depth and breadth of the market, and identify if there are willing buyers at some level above most recent trades. Flash orders are small "immediate or cancel" orders, valid only for microseconds that carry little risk. By ferreting out buyer limits, HF traders have vastly greater knowledge of all aspects of the markets' depth and breadth than individuals or passive investors like pension plans.

HF Modus Operandi

Computerized trading dominates today's stock markets. Functioning within that world, HF trading casts a long shadow over value investing and market-determined prices. HF traders achieve profitability by skimming bid-ask spreads across a vast volume of transactions conducted in increments of millionths of a second throughout a trading day. Profitability does not depend on any assessment of the future value of any given security. The duration of holding a share is usually only a few seconds during which the bid-ask spread can be captured. HF traders position themselves as an intermediary between buyer and seller, extracting a small charge from every transaction with arguable benefit to either buyer or seller. The bid-ask spreads may sometimes be narrowed, but the primary determinants are the prices at which an HFT can gather and then distribute shares rapidly. Moreover, HF traders avoid carrying a position after market close, avoiding any exposure to the prospects of any business over night.

Skewing Market Prices

HF trading tends to be more profitable when markets are rising so that the bid-ask spread is maximized as HF traders fill any gap between buyers and sellers. When markets fall, there is a strong incentive to levitate markets back up to the levels prevailing before the sag, making profitable distribution of shares accumulated during the decline. On days of thin trading volume this can readily be achieved by well-timed surges of buys of ETFs such as SPY (S&P 500 ETF). Such surges can trigger automatic buy responses of the many algorithmic trading models on which other investors and traders rely. In sum, HF trading tends to operate with an upward market bias. While the differences may only be pennies per day, over time this upward bias likely lifts share price above the level that would otherwise materialize, potentially skewing true asset value.

Systemic Risk from Illusory Liquidity

HF trading tends to be less profitable during downturns, as the sale of purchased shares becomes more difficult in a falling price environment. Broker-dealers who are designated "market makers" are constrained by regulatory requirements that they must stay active and provide a bid when requested. In effect, HF traders also function as market makers but have no comparable obligations. If they sense an aberration in trading activity, particularly an abrupt downward movement in prices, they are free to withdraw from trading. In a rapid market decline, their absence is likely to amplify the rate of descent. When active, their voluminous transactions create an illusion of ample liquidity and balance between sellers and buyers. When they step away, this illusion is instantly dispelled. Thus, HF traders may often help moderate or smooth market volatility, but since they retain freedom of action to withdraw at their own discretion, they pose systemic risk.

Likelihood of Another Flash Crash

During the "flash crash" of May 6 a number of HF trading entities stepped away and liquidity disappeared. The May 6 flash crash only lasted a few minutes - but a future flash crash could well last much longer. In retrospect, it is highly doubtful that May 6 was the first time a number of HF traders stepped out. It would be irresponsible to view the May 6 flash crash as a onetime event with extremely low probability of recurrence.

Distortion of Market Correction

The process of HF trading gives the appearance of a huge, seemingly limitless array of buyers at any given moment, even on days of concern that markets might be overvalued or vulnerable to negative developments like the recent euro crisis. On such days, when traditional buyers absent themselves, negative market corrections may be avoided, delayed, or mitigated by the levitation of HF trading. The greater the time between true market corrections, the greater the distortion in price and the bigger the likely correction when HF levitation ends. Since major corrections invariably overshoot, the outcome will likely be uglier the longer the computer-driven postponement.

Conclusion

Essentially, HF trading functions as a positive feedback loop. Applied scientists and systems specialists treat positive feedback loops as inherently unstable. Each positive response generates stepped up repetition of the same actions. Positive feedback loops result in an ever expanding balloon, but like all balloons, risk of bursting increases with size. Some observers suggest that the risks of catastrophic market outcomes have become so great that regulators must ban HF trading. Trying to reverse technological progress has never been a very successful endeavour. Given the fundamentally different objectives of HF traders, their unlimited freedom of action, and their apparent dependence on positive feedback loops, regulators might be wise to devise compensating negative feedback mechanisms. Some commentators have suggested introduction of minimum holding periods for non broker-dealers. Alteration of incentives might be achieved by introduction of a sliding scale of fees or taxes according to volume and speed of trading. Or, if HF traders decide to withdraw they might not be allowed to resume trading for a specified period of days. That at least would reduce the evident risk of a market plunge resulting from arbitrary decisions to halt HF trading. The goal of regulators is not to get rid of HF trading but rather to realign its incentives to the objective of eliminating systemic risk.

All the best

Harald Malmgren and Mark Stys

Dr Harald Malmgren is Chief Executive of Malmgren Global and also currently the Chairman of the Cordell Hull Institute in Washington, DC, a private, not-for-profit "think tank". He is an internationally recognised expert on world trade and investment flows who has worked for four US Presidents. His extensive personal global network among governments, central banks, financial institutions, and corporations provides a highly informed basis for his assessments of global markets. At Yale University, he was a Scholar of the House and Research Assistant to Nobel Laureate Thomas Schelling. At Oxford University, he studied under Nobel Laureate Sir John Hicks, while earning a DPhil in Economics. After Oxford, he began his academic career in the Galen Stone Chair in Mathematical Economics at Cornell University. Dr Malmgren commenced his career in government service under President John F Kennedy, working with the Pentagon in revamping the Defense Department's military and procurement strategies. When President Lyndon B Johnson took office, Dr Malmgren was asked to join the newly organised office of the US Trade Representative in the President's staff, where he had broad negotiating responsibility as the first Assistant US Trade Representative. He has also served as principal adviser to the OECD Wise Men's Group on opening world markets, under the chairmanship of Jean Rey, and he served as a senior adviser to President Richard M Nixon on foreign economic policies. President Nixon then appointed him to be the principal Deputy US Trade Representative, with the rank of Ambassador. In this role he served Presidents Nixon and Ford as the American government's chief trade negotiator in dealing with all nations. In 1975 Dr Malmgren left government service, and was appointed Woodrow Wilson Fellow at the Smithsonian Institution. From the late 1970s he managed an international consulting business, providing advice to many corporations, banks, investment banks, and asset management institutions, as well as to Finance Ministers and Prime Ministers of many governments on financial markets, trade, and currencies. He has also been an adviser to subsequent US Presidents, as well as to a number of prominent American politicians of both parties.

Mark Stys is Chief Investment Officer of Bluemont Capital Advisers. He was formerly a senior bond trader with Fidelity Capital Markets, ultimately appointed Head of Fixed Income and International Strategy. He is a past member of the NASD Fixed Income Pricing Committee and frequent presenter for the NASD Town Hall meetings. A graduate of the United States Naval Academy, he was an aviator in the United States Marine Corps, and continues to function as Adviser to the United States Marine Corps' Strategic Initiatives Group.

[May 25, 2010] Is The SEC Still Working For Wall Street By Simon Johnson