Havia apetite pela Luz Saúde. Preço é que não convenceu

[jlmf]

"It's quiet out there; too quiet. But if you were watching carefully this morning, everyone's favorite government-subsidized bank - Citigroup - flash-crashed to the tune of a $1.2bn market-cap loss in a fraction under 100 milliseconds..."

http://www.zerohedge.com/news/when-it-a ... onds-looks

[Automech]

On Wall Street, the Rising Cost of Faster Trades

Impressionante esta parte:

some firms have found that data moves too slowly through fiber optic cables. In response, several companies are currently developing networks to transmit data by microwave.

[VirtuaGod]

A Zen Moment With Wall St.'s Most Amazing Chart

[VirtuaGod]

On Wall Street, the Rising Cost of Faster Trades

[LTCM]

EVERY computer-user knows the feeling of dread when a brand new piece of software causes the entire system to crash. Shareholders in Knight Capital, an American equity broker, now realise how expensive such glitches can be. On August 1st Knight Capital started to use a new software programme to execute its trades. Within an hour the programme had caused turmoil in the market, sending errant buy-and-sell orders that cost Knight $440m. Shares in the company plunged on the day and, by August 6th, shareholders were forced to accept a rescue that heavily diluted their stakes (see article).

Most trades these days are conducted by computer and are completed without fuss. As in other fields, technology has reduced costs, in particular the spread between the bid and offer prices. If lower trading costs encourage more investors to own shares, then the cost of capital for companies will fall, which is good news for the whole economy.

But there are drawbacks. The Knight glitch was just the latest in a series of cock-ups that have been linked to computerised trading. The most serious of these was the “flash crash” of May 2010, when the Dow Jones Industrial Average plunged 1,000 points within minutes and shares in Accenture, a consultancy, were briefly marked down to a preposterous one cent. Such events make investors fearful of trusting their nest-eggs to the stockmarket; Knight was the biggest handler of trades by small investors. The cost of capital could go up, not down.

Then there is the systemic risk. This time round, it was only Knight Capital that failed; what if it had been a much larger firm? The crisis of 2008 casts a long shadow. Not only did it show that financial companies can quickly implode, but the subsequent government rescues were highly unpopular with voters. Politicians might hesitate before bailing out another big financial firm, especially if the cause was reckless trading.

This newspaper seldom finds itself on the side of restraining either technology or markets. But in this case there is a doubt whether the returns justify the risk. Society needs a stockmarket to allocate capital efficiently, rewarding the best companies with higher share prices. But high-frequency traders are not making decisions based on a company’s future prospects; they are seeking to profit from tiny changes in price. They might as well be trading baseball cards. The liquidity benefits of such trading are all very well, but that liquidity can evaporate at times of stress. And although high-frequency trading may make markets less volatile in normal times, it may add to the turbulence at the worst possible moment.

Trade in haste, repent at leisure

So what is to be done? The world is not going back to the days of face-to-face trading with prices written on whiteboards by hand (a system that was controlled by a cosy cartel of dealers). But the Securities and Exchange Commission is right to suggest that automated programmes should be fully tested before they are used in live trading, and that voluntary guidelines on automated trading should be mandatory.

The regulators could go further. In October 1987 Wall Street suffered Black Monday, when the Dow Jones Industrial Average fell 23% in a day. An early form of programmed trading, called portfolio insurance, was to blame. In the aftermath “circuit breakers” were introduced, allowing trading to be halted when the market suffered a big fall. The same rules could be applied when the market seems excessively volatile, or when volume spikes exponentially. The most successful investor in history, Warren Buffett, says his ideal holding period for shares is for ever. So it surely will not do much harm to investors if, on occasion, they have to wait a second or two before dealing.

http://www.economist.com/node/21560258/print

[LTCM]

The trading firm Knight Capital recently rushed to develop a computer program so it could take advantage of a new Wall Street venue for trading stocks.

But the firm ran up against its deadline and failed to fully work out the kinks in its system, according to people briefed on the matter. In its debut Wednesday, the software went awry, swamping the stock market with errant trades and putting Knight’s future in jeopardy.

The fiasco, the third stock trading debacle in the last five months, revived calls for bolder changes to a computer-driven market that has been hobbled by its own complexity and speed. Among the proposals that gained momentum were stringent testing of computer trading programs and a transaction tax that could reduce trading.

In the industry, there was a widespread recognition that the markets had become more dangerous than even specialists realized.“What is starting to become clear is that the costs in terms of these random shocks to the system are occurring in ways that people never anticipated,” said Henry Hu, a former official at the Securities and Exchange Commission and a professor at the University of Texas in Austin.

Knight, founded in 1995, is a leading matchmaker for buyers and sellers of stocks, handling 11 percent of all trading in the first half of this year, according to the data firm Tabb Group. Knight lost three-quarters of its market value in the last two days, in addition to losing $440 million from the errant trades, and was scrambling to find financing or a new owner.


The S.E.C. applied limited safeguards on trading after the “flash crash” of 2010 sent the broader market plummeting in a matter of minutes. But big investors like T. Rowe Price, members of Congress and former regulators said Thursday that the S.E.C. and the industry had been too complacent and needed to do more to understand and control the supercharged market.

The high-speed firms like Knight, which connect directly to the servers of the exchanges and are capable of executing thousands of trades a second, are responsible for more than half of all activity in American markets. Companies that have benefited from the fragmentation and computerization of the markets have largely managed to fend off tighter controls by pointing to the steady decline in the cost of trading stocks.

Some large, institutional investors, like Vanguard, have said that the increased volume of trading has made it easier to get in and out of stocks, lowering the ultimate costs for individuals who invest in popular vehicles like mutual funds.

But even people who had previously defended the advances in trading technology said on Thursday that too many problems had been overlooked.

In Knight’s breakdown on Wednesday, as well as in the botched initial public offerings of Facebook in May and BATS Global Markets in March, the problems were caused by new computer programs that had not been adequately tested. Currently regulators have no protocol for signing off on new software programs like the one Knight rolled out.

http://dealbook.nytimes.com/2012/08/02/ ... -expected/

[PMACS]

Knight Explores Options on $440 Million Trade-Error Loss

Knight Capital Group Inc. (KCG) said losses from yesterday’s trading breakdown are $440 million, almost quadruple its 2011 net income and more than some analysts had estimated, and the firm is exploring strategic and financial alternatives. Its stock has lost 66 percent in two days.

Knight said it will continue its trading and market-making today as it considers its options. Yesterday’s issue was related to the installation of trading software and resulted in the company sending “numerous erroneous orders,” the Jersey City, New Jersey-based firm said today. The stock tumbled 50 percent to $3.46 at 9:36 a.m. New York time today.

Shares of Knight, one of the largest U.S. market makers, plunged 33 percent in record volume yesterday as investors speculated on how much the breakdown that sent stocks swinging as much as 151 percent will cost the company. Analysts at JPMorgan Chase & Co. estimated yesterday that Knight’s loss would be as much as $170 million, while Raymond James & Associates Inc. said the amount could be “hundreds of millions.”

“Although the company’s capital base has been severely impacted, the company’s broker/dealer subsidiaries are in full compliance with their net capital requirements,” Knight said today. “The company is actively pursuing its strategic and financing alternatives to strengthen its capital base.”
140 Stocks

The New York Stock Exchange reviewed trading in 140 stocks from Molycorp Inc. (MCP) to AT&T Inc. yesterday as the market’s open was disrupted. Trades that occurred during the height of the volatility were canceled in six securities, where prices swung at least 30 percent in the first 45 minutes.

Knight’s market-making unit executed a daily average of $19.5 billion worth of equities in June with volume of 3.1 billion shares, according to its website.

The $440 million loss compares with net income of $115.2 million in 2011 on revenue of $1.4 billion, data compiled by Bloomberg show.
‘More Monitoring’

“This loss is larger than we expected,” Rich Repetto, a New York-based analyst with Sandler O’Neill & Partners LP, wrote in an e-mail. “More monitoring and safeguards need to be built into these trading algorithms of both market makers and exchanges.”

As stock swings mounted yesterday, the company told some clients of its market-making business that a “technical issue” was affecting its systems and advised them to route orders elsewhere, according to e-mails from spokeswoman Kara Fitzsimmons yesterday. The issue was confined to that unit and its other operations were unaffected, she said.

The errors were caused by a malfunction in a trading algorithm, according to a person at Knight who asked to remain anonymous because the matter hasn’t been publicized.

While Knight reported July 18 that second-quarter earnings exceeded analyst projections, sales fell short by 1.7 percent. Cash and short-term investments rose 55 percent to $7.5 billion in the second quarter of 2012, and the company’s debt amounted to 46.4 times total assets, compared with 64 a year ago, data compiled by Bloomberg show.

http://www.bloomberg.com/news/2012-08-0 ... llion.html

[LTCM]

How It All Happens

Let's start with a simple trade: Greg Thompson, a Scottrade customer, is sitting in his office in St. Louis and puts in a market "buy" order (an order to buy at whatever the best price is) for 100 shares of IBM.

He pushes the button, and the order is executed. A second or two later, he gets a confirmation back: he has bought 100 shares of IBM [IBM Loading... () ] at the current price, $128.56.

"I enjoy the challenge, it's a lot of fun, and sometimes I can make some money," says Thompson.

But wait: what just happened here? Where did this order go? How was it executed? Who sold the stock to him?

Man vs. Machine - A CNBC Special Report

Scottrade is a discount broker. It buys and sells shares using market makers like Knight Capital, UBS, Citadel and Citigroup [C Loading... () ]. To get to those market makers, Scottrade and all other brokers have an electronic order routing system.

How do they and their competitors decide who to send the order to? The criteria include speed, price, and quality of the service.

Discount brokers do receive payments from market makers for order flow, though brokers like Scottrade say it is not a criteria for deciding where orders are sent.

Let's say Scottrade's order routing system determines that Knight Capital has the best combination of payment, speed and price and routes the order to them. Knight sells Scottrade 100 shares immediately. Mr. Thompson's order is now filled—he owns 100 shares of IBM, at $128.56.

Key Points
Do this millions of times each day and you can make moneyBlame it on the march of technology and the SEC's decision to encourage competition

But that's not the end of the story. Where did Knight get the 100 shares from?

In most cases, Knight and other market makers internalize the order—they match off the order to buy 100 shares with another order to sell 100 shares that is already in their system. "The vast majority of the time, we buy and sell from our own inventory. In some cases, we go out to some other venue to get those shares," says Jamil Nazarali, Senior Managing Director, Global Head of the Electronic Trading Group at Knight.

Among those other venues or choices: They can send the order out to an exchange or a dark pool (but this will cost them money), or they could also stay short the stock and hope they can buy it back in a short time at a lower price.

Only the last choice will likely make them money.

Here's how: Let's say they hold on to the stock for a few seconds and are able to buy it at $128.55. They sold it to Thompson for $128.56, so Knight will make a profit of $1.00 (100 shares times the one penny-per-share profit).

But Knight will also pay a rebate (payment for order flow) to Scottrade and other discount brokers. These payments vary, but are typically a tenth of a cent per share. Let's say in this case Knight pays a rebate of $0.10 to Scottrade for the order, leaving a total profit of $0.90 ($1.00 - $0.10).


Doesn't sound like much (remember, most of the trades don't make money) but do this millions of times each day and you can make money. But you need huge volume.

Pump Up the Volume: Connecting Buyers and Sellers

Indeed, these types of trades do happen millions of times a day: retail customers like Thompson interact with online brokers (AmeriTrade, Schwab, ETrade, Scottrade, etc.) who route orders to market makers, who in turn match orders against their own supply or interact with exchanges (NYSE, Arca, NASDAQ, BATS, Direct Edge).

Now let's see how this order of Thompson's might interact with other players.

Outside Philadelphia, Gus Sauter walks one of the trading floors of Vanguard, one of the largest mutual fund companies in the United States. Sauter is Vanguard's Chief Investment Officer and this particular trading desk trades more than 10 million shares of stock a day, including many shares of IBM.

The goal of Sauter and his trading desk is to get the lowest execution cost, and he has several choices when he has to buy or sell stocks like IBM. He can execute a particularly large order manually by directing all or parts of it to specific trading venues. Or, he can bundle orders to buy and sell many different stocks into a "basket" that will be executed as a single computer program.

He can also choose to use an an algorithm and a smart order routing system, which will likely chop up an order to buy or sell a specific stock (like IBM) into small pieces (100 orders of 100 shares each, for example), and will then direct those orders to whatever venue offers the best combination of speed and price.

So it's likely that part of any order to buy or sell IBM will end up in different locations: at a market maker like Knight Capital or UBS [UBS Loading... () ], exchanges like the NYSE, NASDAQ, or BATS, or dark pools like Liquidnet. "We might rifle through all of those trading venues in a matter of a fraction of a second and get our trades executed that way," says Sauter.

Clearly, Sauter's trade is considerably more complicated than Thompson buying IBM at Scottrade.

Sauter may include specific instructions on how the order is to be executed. For example, some mutual fund and pension fund managers want to make sure their trades are executed at the Volume Weighted Average Price (VWAP), which is the dollar value of all the shares traded in that stock divided by the volume. This is a measure to ensure that price execution is at least as good as the average.

Sauter says he has an even higher standard for his orders. He wants to make sure that the stock is bought or sold at the price he or his fund managers want to buy or sell it at, not the market price. If a Vanguard fund manager wants to sell IBM at $128.60, for example, he may want his broker to make sure he sells at that price, and not, say, at $128.58 (this is called "implementation shortfall").

Other factors beside speed and price may also influence the decision of asset managers. Some may want to send order flow to a specific firm in exchange for services—analyst research, trader commentary, access to conferences and meetings. In exchange, the firm may provide execution to an asset manager at very low cost.

"There are just so many different choices we have and we look for the one that's going to minimize the transaction costs that we're going to incur," Sauter says.

A hundred miles away, in the middle of New Jersey, Manoj Narang is sitting at his desk at Tradeworx, a high-frequency trading company.

Narang trades using statistical arbitrage, where traders are short one security and long another, based on historical performance.

For example, IBM historically trades in a certain relationship with the S&P 500. When it trades above that relationship, Narang's computers may put in large orders to sell IBM and buy the S&P (all in a fraction of a second) assuming the relationship may revert to its historic mean.

Narang says they trade 50 to 100 million shares of stock a day, including many trades in IBM, but the day I am there is a relatively slow one in August. It is 3pm ET, an hour before the market closes, and Narang's firm has traded 21 million shares, for a net profit of $7,000.

Narang and other high-frequency traders execute their trades through direct access. The computers are linked to servers very close to those of the major exchanges. Why? Because the pricing inefficiencies last for only a fraction of a second, so speed is paramount.

"When you have opportunities as small as a tenth of a cent per share, they tend to come and go very quickly. Maximum speed to the exchanges is desirable, so we put our servers physically at the enchants," says Narang.

Bottom Line: Technology, Liquidity, Complexity

So what is happening here? Three customers—Thompson, who wants to buy 100 shares of IBM, Sauter, a mutual fund manager who will be buying or selling tens of thousands of shares or more of IBM, and Narang, a high frequency trader who will also be buying and selling thousands (perhaps millions) of shares of IBM—are all interacting in different spaces: in the computers of market makers who match off the orders, on exchanges, and in alternative trading systems like dark pools.

All three of these orders could interact with each other. All three of these customers, in their own way, are adding liquidity—but there are a lot more places for them to trade.

How did things get so complicated? You can blame it on the relentless march of technology and a decision by the SEC to encourage competition among exchanges.

[LTCM]

Here are some of the most notorious examples of computer-driven snafus. Welcome to the new stock market. Mind the gaps.

The Flash Crash obviously the most notorious example of computerized trading run amuk. On the afternoon of May 7, 2010, stocks started dropping, fast. The DJIA fell nearly 1,000 points in a matter of minutes. It recovered most of the losses, but still closed down 342 points. Rather than being the result of a specific error or system breakdown, the crash seemed to just be an extreme example of how high-frequency trading can affect the market. The definitive explanation for what happened that day hasn’t yet come.

BATS IPO BATS had built an all-electronic exchange that over several years became the market’s third-biggest exchange. When the company decided to go public, it proudly decided to list the IPO on its own exchange. But the move was a disaster. The company encountered myriad problems with its platform, with bids on BATS shares plunging to pennies within seconds of its first trades. The break-downs hit other stocks as well, most prominently Apple. BATS withdrew the IPO, and as of today remains a private company.

Facebook’s IPO This one’s fresh in everybody’s mind. Nasdaq won the rights for Facebook’s highly sought after listing. But the company’s debut was quickly driven into the ranks of notoriety. Nasdaq’s systems were quickly overwhelmed, and the stock was frozen for an hour. Traders were completely in the dark and confused; some tried to cancel trades, some kept entering the same trades, and later got stuck with more stock than they wanted. Nasdaq has pledged $62 million in compensation, but it’s not likely to be enough: UBS alone claims $356 million in losses.

The Sawtooth Trade We wrote about this one two weeks ago on MarketBeat. Trading in four blue-chip stocks, Apple, McDonald’s, Coke, and IBM, exhibited a very deliberate, very odd sawtooth pattern; rising and falling in half-hour increments throughout the day. It didn’t achieve the notoriety of these other events, but it did quite nicely illustrate the effects of computerized trading.

http://blogs.wsj.com/marketbeat/2012/08 ... ays-snafu/

[LTCM]

Eheheheh, esta ainda é melhor do que a correlação entre a produção de manteiga no Bangladesh e o S&P500 que o Paulos fala no livro dele.

But data-mined numbers can be so irresistible that, as Mr. Leinweber puts it, "they are one of the leading causes of the evaporation of money, especially in quantitative strategies."

Mr. Leinweber got so frustrated by "irresponsible" data mining that he decided to satirize it. After casting about to find a statistic so absurd that no sensible person could possibly believe it could forecast U.S. stock prices, Mr. Leinweber settled on annual butter production in Bangladesh. Over an 13-year period, he found, this statistic "explained" 75% of the variation in the annual returns of the Standard & Poor's 500-stock index.

By tossing in U.S. cheese production and the total population of sheep in both Bangladesh and the U.S., Mr. Leinweber was able to "predict" past U.S. stock returns with 99% accuracy.

[Elias]

Latest Market Glitch Shows 'Trading Out of Control'
By Jeff Cox | CNBC – 29 minutes ago

Wednesday morning's stock snafu had a familiar ring to it - mysterious volume in trades that simply could not have been made by a human comes surging out of nowhere, causing brief but acute market mayhem.
By now, many players on trading floors have gotten used to the disruptions that can come from the highly automated new world of high-frequency trading.
But that doesn't mean they like it.

"This algorithmic trading is kind of out of control," Phil Silverman, managing partner at Kingsview Capital, said as officials at the New York Stock Exchange tried to make sense of what happened. "It seriously hurts investor confidence."

By mid-afternoon, no one still quite knew exactly why about 150 stocks experienced a blinding surge in market volume, causing momentary disruptions in the prices of nine Dow components and a slew of others across various categories.

Authorities involved in reviewing the matter said Knight Capital, a trading outfit that employs algorithms used in high-frequency trading, said it experienced "technology issues" with its market-making procedures.

Ultimately, the broader market reacted little to the disruption, which was limited by circuit breakers and mechanisms at the NYSE to help contain the damage of HFT mistakes.

Traders, though, have grown weary of the problems and say the high-speed envionment has changed the market in a bad way.

"When markets would have a big move, when things were really crazy, I would go out into the street and talk to people and they knew. Now, you get these big moves and people just don't care anymore," Silverman says. "They don't want to be a part of it, the high-frequency thing. The algorithmic situation needs to be looked at. We need to understand it better."

Firms create algorithms to buy and sell stocks according to formulas and market conditions. The high-speed robots trade with each other, seeking in transactions that can take microseconds to capitalize sometimes on fractions of a penny in stock moves.

While proponents say the rapid trading helps create liquidity and price discovery, regular investors have been fleeing the market, in part due to macro worries and in part because they don't feel they can compete in the automated trading world.

Dave Lutz, the managing director of U.S. trading at Stifel Nicolaus in Baltimore, cautions investors not to over-react to events like the Knight mistake.

"A lot of people seem to think it was human error. At the end of the day it wasn't necessarily a failure of systems," he said. "It's not a reason for people to lose confidence in the markets."

Still, had a human presence been involved somebody at least could have flagged the Knight trades as improper and perhaps stopped them before they hit the market.
But Lutz counters that the mistake was
nowhere on par with the May 6, 2010 Flash Crash, where an error caused the Dow to lose nearly 1,000 points in a few minutes, or any of the other recent trading fiascoes.

"On the surface, it doesn't seem like it's any of that," he said. "It seems like it was simple human errors, and that's been happening since they've been trading underneath the maple tree."

http://finance.yahoo.com/news/latest-ma ... 47006.html

[Automech]

Eheheheh, esta ainda é melhor do que a correlação entre a produção de manteiga no Bangladesh e o S&P500 que o Paulos fala no livro dele.

[migluso]

LOL...

Malditos robots, pescam tudo, até revistas cor de rosa... Algoritmos tão complexos e inteligentes e afinal não são capazes de filtrar as notícias apenas nos meios de comunicação da especialidade...

São uns cuscos esses robots...

[LTCM]

Whatever you may think of how Anne Hathaway and her co-host James Franco did as hosts of the newer, younger, hipper Oscars, one thing appears to be certain: When Anne Hathaway makes headlines, the stock for Warren Buffett's Berkshire-Hathaway goes up. Think of Berkshire-Hathaway shares (BRK.A) as a really expensive version of the IMDb's StarMeter (which actually is designed to go up and down as actors make the news). But a bedrock member of the New York Stock Exchange? The evidence would indicate as much.

On the Friday before the Oscars, Berkshire shares rose a whopping 2.02%. And on the Monday just after the Academy Awards, they rose again, this time 2.94%. But it's not just an Oscar bounce, or something Warren Buffett may have said in the newspaper, or even necessarily something the company itself is doing (i.e. rumors afoot to buy Costco). Just look back at some other landmark dates in Anne Hathaway's still young career:

Oct. 3, 2008 - Rachel Getting Married opens: BRK.A up .44%
Jan. 5, 2009 - Bride Wars opens: BRK.A up 2.61%
Feb. 8, 2010 - Valentine's Day opens: BRK.A up 1.01%
March 5, 2010 - Alice in Wonderland opens: BRK.A up .74%
Nov. 24, 2010 - Love and Other Drugs opens: BRK.A up 1.62%
Nov. 29, 2010 - Anne announced as co-host of the Oscars: BRK.A up .25%

My guess is that all those automated, robotic trading programming are picking up the same chatter on the internet about "Hathaway" as the IMDb's StarMeter, and they're applying it to the stock market. Of course, this isn't necessarily bad news for the investor. After all, can you imagine what might have happened to Berkshire stock if Warren Buffett had appeared nude in Love and Other Drugs rather than Anne Hathway? Perhaps it's best if we don't think about it.

[LTCM]

The chaotic listing of Facebook Inc. FB +6.09% on the Nasdaq stock market last month was the latest example of how computer-trading systems can go haywire. The social network's botched IPO came hard on the heels of another embarrassing glitch. In March, BATS Global Markets, a computer-driven exchange, failed to list its own stock due to a software bug.

Mishaps such as these are damaging the confidence of small investors in the integrity and reliability of stock markets, critics say.

The root of retail investors' end of the love affair with the stock market can be traced back to May 6, 2010, the day of the now-infamous "flash crash."

A dark pool is an electronic platform where investors trade shares privately, away from more transparent stock exchanges. What do they have to hide? Lam Thuy Vo shines a light on dark pools.

In the space of a few, hair-raising minutes, a breakdown in the market triggered by failures in computer-trading systems across the country caused stocks to plunge about 10%. Despite extensive probes by regulators, the cause of that sudden crash remains a mystery.

The flash crash left a scar on the market. Investors have taken money out of the U.S. stock market funds in 17 of the 25 months since then, withdrawing a net $137 billion, according to Lipper


Panic Ticks

Thomas Peterffy had seen it all. The Black Monday crash of October 19, 1987, the 1998 collapse of the giant hedge fund Long-Term Capital Management, the implosion of the dot-com bubble in 2000 and 2001, the credit crisis of 2008.


But what was unfolding on the afternoon of May 6, 2010 was different. This was fast. This was high-speed trading.

The founder of Interactive Brokers Group Inc. IBKR +0.07% and Timber Hill, a sophisticated computer-driven trading operation, was monitoring the market from a private study on his luxurious estate in Greenwich, Conn.

Chaos was breaking out amid a burst of riots on the streets of Athens, Greece. Stocks had been on their heels all day. But now things were getting much worse. Down about 2% at 2:30 p.m. Eastern, the market had started to plunge rapidly.

Mr. Peterffy picked up the phone and called Timber Hill's trading desk, several miles away in downtown Greenwich.

"What the heck is happening?" he said.

"Don't know," a rattled trader replied.

"Well find out!" Peterffy shouted.

As the Timber Hill traders scrambled to find the cause of the problem, they started seeing a wave of "panic ticks" on their screens—warning signs indicating that their positions were moving so rapidly that they were risking big losses.

By 2:40 p.m., the number of panic ticks exploded. Mr. Peterffy called the trading desk again to see if anyone knew what was happening.

No one did.

Tradebot
In a bland, cube-shaped building on the outskirts of Kansas City, Dave Cummings watched from his corner office as the stock market unraveled like a ball of yarn.

The founder of Tradebot Systems, one of the world's most advanced high-frequency trading operations, wasn't sure what to make of the downward draft. The heavy volume was scrambling trading systems, leading to disparities in prices quoted on various exchanges. The decline became so sharp that it made Mr. Cummings worry that it wasn't going to right itself.

Like many others, he worried that a "fat finger" mistake by a trader—Wall Street slang for someone who pressed the wrong button or put too many zeros into a sell order—had triggered a cascade that was turning into a vicious feed-back loop.

If there was an erroneous trade, that meant Tradebot's systems, which tracked all corners of the market for signals about future conditions, were operating on bad information. If Tradebot kept trading, it might spread the turmoil elsewhere, like a contagious virus.
Digitalized and Decimalized

As the stock market plunged, then Senator Ted Kaufman (D., Del.) was presiding as chair of the Senate. A wave of chatter rippled through the chamber as the senators, clicking on their handheld devices, stared in amazement at news of a major crash in the stock market.

Mr. Kaufman had been one of the fiercest critics of the computer-driven machines that had taken over the market. But he never thought he would see anything like what had just occurred.

Addressing his colleagues from the floor, he explained how the market had shifted from a floor-based system to one that was "digitalized and decimalized."

"People came into the market and began to develop these high-speed computers," he said. "Human beings were no longer doing the trading, computers were. They developed these algorithms. It ran automatically. It grew and grew. There is no way to know what is going on. No one knows what is happening in these exchanges when this trading is going on. We have a very dangerous situation."
Pools of Darkness

In the weeks and months following the flash crash, a fierce debate erupted over what had become of the stock market. Angry words were exchanged in the halls of Capitol Hill, on financial television shows and at trading firms in New York and Chicago.

Congress held panel discussions. The Securities and Exchange Commission grilled the previously unknown chieftains of the high-speed merchants, including Mr. Cummings of Tradebot and Mr. Peterffy of Timber Hill.

The complex, labyrinthine nature of the market vexed ordinary investors. Years ago, before the rise of electronic networks, most trading took place at the New York Stock Exchange and Nasdaq.

BY 2012, trading occurred in roughly seventy different venues, including giant hedge funds and banks. So-called "dark pools," private markets in which trading took place away from public exchanges such as the NYSE, accounted for more than 10% of all U.S. stock trades, according to Tabb Group.

As the markets slid into discrete pools of darkness, investors, too, had been left in the dark.

Write to Scott Patterson at scott.patterson@wsj.com

A version of this article appeared June 11, 2012, on page C1 in the U.S. edition of The Wall Street Journal, with the headline: Breakdown: A Glimpse Inside the 'Flash Crash'.

[LTCM]

A minha pergunta é se se consegue saber, de alguma forma, se existem fundos a utilizar a tecnologia vendida (alugada ?) por esta empresa ? Por mera curiosidade sobre a pessoa, gostava de ver a performance de algum fundo que usasse o(s) sistema(s) deles.

Não se consegue, parte do sucesso dos fundos reside naquilo que é secreto.

[Automech]

Isto é mais uma pergunta sobre algorithmic trading do que sobre HFT, mas não vale a pena a abrir um tópico novo.

Descobri, por mero acaso, que um dos foristas que mais gostava de ler no elitetrader (MAESTRO) chama-se na realidade Alex Bogdan e é fundador de uma empresa chamada Quantitative Alpha Trading, cotada na bolsa canadiana.

Os posts deles eram bastante interessantes e revelavam um conhecimento bastante profundo pela metodologia usada pelos quant funds.

A minha pergunta é se se consegue saber, de alguma forma, se existem fundos a utilizar a tecnologia vendida (alugada ?) por esta empresa ? Por mera curiosidade sobre a pessoa, gostava de ver a performance de algum fundo que usasse o(s) sistema(s) deles.

[atomez]

Stock trading 'fractures' may warn of next crash

Might a fleeting and little understood aspect of stock market dynamics hold the key to warding off financial crashes? That is the tantalising suggestion to emerge from a group of physicists who have been studying stock movements.

The study is the first to focus on an ultra-fast feature of market dynamics that the team, led by Neil Johnson at the University of Miami in Coral Gables, calls a "fracture". Fractures happen when the price of a stock briefly shoots up or down, often before returning to its original level. They take place so quickly, sometimes lasting less than half a second, that they can be invisible to any human following the price. "If you blink you miss it," says Johnson. His research shows that there seems to be a link between these fractures and sudden stock market crashes, known as "black swans".

If fractures are a source of instability, computerised trading algorithms may be to blame. Use of these algorithms, which make automated trades in milliseconds, has mushroomed in recent years. Competition between rival algorithms is so great that one company is spending $300 million to build a transatlantic cable that will shave 6 milliseconds off the time it takes to exchange signals between the financial hubs of London and New York. But finance experts fear that one or more out-of-control algorithms could cause a crash, as may have happened in the so-called Flash Crash of May 2010.

Johnson's research, which was posted online on 8 February, is based on price logs from over 60 different markets collected by Eric Hunsader of Nanex, a Chicago-based company that sells streaming market data. Johnson and Hunsader trawled through the data and found that fractures are remarkably common – 18,520 took place between 2006 and 2010.

Intriguingly, the number of daily fractures increased about a week before the stock market crash of September 2008, and also before a sudden but smaller crash in May 2010, which is still not fully understood. Johnson thinks that the build-up of fractures can in some cases destablise the entire market, much as the accumulation of tiny cracks can lead to catastrophic failures in structures such as aircraft wings. "You're seeing something starting to break open," says Johnson.

Fracture forecasts

The link between fractures and stock market crashes requires further investigation, but suggests it might be possible to build an early-warning system based on the rate at which fractures occur. "Johnson makes a compelling case," says Dave Cliff, an expert in complex systems at the University of Bristol, UK. "Developing [his] analysis techniques into methods or tools for reliably predicting crashes is a very appealing prospect." Forecasting every crash is probably impossible, adds Cliff, but the research could lead to a system that at least alerts regulators to incipient instability. "This work could turn out to be a major first step in that direction."

"There is a huge amount of interconnected algorithms that cannot be controlled by regulators," says Tobias Preis, a researcher at Boston University in Massachusetts and founder of Artemis Capital Asset Management in Holzheim, Germany.

When Johnson analysed the frequency at which fractures of different size and duration occur, he found that fractures lasting one second or less follow a different statistical pattern to longer ones. The one-second cut-off is significant, says Johnson, since it is about the time it takes a human trader to weigh up a piece of evidence and make a decision. On shorter timescales computers control market dynamics since they can make decisions in mere milliseconds.

This ultra-fast computing-controlled trading regime is barely recognised, let alone controlled by any government regulator with an interest in preventing crashes. "Nobody really knows what's going on down there," says Johnson. "It's like the wild west."

[atomez]

Steve Kroft gets a rare look inside the secretive world "high-frequency trading," a controversial technique the SEC is scrutinizing in which computers can make thousands of stock trades in less than a second.


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[LTCM]

Código: Selecionar todos

On Wednesday, Getco said it reached an agreement to buy most of Bank of America Corp.'s floor-trading operation at the New York Stock Exchange. While terms of the deal weren't disclosed, the Chicago-based company said it will become the exchange's second-largest designated market-maker, handling about a third of all daily stock trades there. It will buy and sell bellwether stocks including General Electric Co., Wal-Mart Stores Inc. and McDonald's Corp.

"We're moving onto a bigger canvas," Getco co-founder Stephen Schuler said in an interview.

The move is a dramatic shift for Getco, one of the biggest companies using computer models to eke out profits at high speed from minute fluctuations in the prices of stocks, futures and options. In beefing up its presence on the NYSE floor, the firm aims to expand its trading business at the exchange while burnishing its reputation with investors that still prefer to route trades through specialists.

Instead of trying to persuade investors to bypass trading floors, Getco intends to use its technology to supply more competitive prices to the NYSE floor, attracting more business there and boosting its profile among financial institutions it hopes to land as buyers of trading services.

The company believes it can profit from the business because its floor personnel will use the same systems that power Getco's automated trading, scanning dozens of platforms to help assess supply and demand for a given stock, said Dave Babulak, Getco's head of strategic initiatives.

The firm's quiet evolution from obscure Midwestern trader to prominent market maker underlines the way electronic-trading platforms have transformed the world's stock markets and pushed old-line markets like the NYSE to adapt.

"It's another affirmation of the new generation of automated liquidity providers becoming dominant in today's market," said Justin Schack, managing director for Rosenblatt Securities. "They're really going to have a chance to shine here."

As recently as the 1990s, the NYSE floor was teeming with specialists who executed trades on behalf of their firms. Their role diminished in recent years due to the rise in electronic trading—the number of specialist firms working the floor has dwindled to four from 35 at the beginning of the past decade.

Goldman Sachs Group Inc., one of the four firms working the NYSE floor, in January wrote down $305 million in the value of its own market-making business, which it pegged at $391 million in the third quarter of 2010.

But many investors still prefer to trade through specialists, and Getco sees this transaction as a way to get their business and enhance its standing on Wall Street. Specialist firms bear responsibility to buy and sell in their assigned securities, smoothing trading imbalances and explaining market movements to share issuers.

The deal will reduce Bank of America's day-to-day presence on the NYSE floor to a handful of people from roughly two dozen, said a person familiar with the situation. The remaining brokers are part of a separate business that still executes trades for the company. Bank of America will now have an NYSE presence similar to that of rival J.P. Morgan Chase & Co.

Getco, which already maintains a presence on the NYSE floor following a similar deal in early 2010, will now have between 45 and 50 specialists on the floor, up from about 20.

Mr. Schuler said he and co-founder Dan Tierney envision Getco as a "100-year company," with plans to develop a roster of institutional customers and expand its slate of stock-trading services into new markets like bonds and currencies.

The firm formulated the strategy two years ago and has added to its management team and pursued deals as part of a long-term plan that could one day see Getco float shares in an initial public offering, though such a move isn't currently under consideration. "Right now, we don't need it, so it's not on our radar, but it could be in the future," Mr. Schuler said.

The company operates on more than 50 exchanges and trading venues around the world and typically ranks among the top five participants on electronic markets run by NYSE Euronext, as well as futures platforms like CME Group Inc. and Deutsche Börse AG's Eurex unit.

Getco is expanding its profile with both issuing companies and money managers that buy and sell stocks at a time when regulators are scrutinizing high-frequency trading. Their concerns center on the potential power of their systems to abruptly shift prices.

Mr. Schuler said Getco has also thought about one day applying to become a primary dealer with the Federal Reserve, which would allow the firm to participate in Treasury auctions.


http://online.wsj.com/article/SB1000142 ... 51256.html

[migluso]

http://www.zerohedge.com/news/its-offic ... rld-record

1 minuto e 10 segundos é a caricatura perfeita...

<iframe width="420" height="315" src="http://www.youtube.com/embed/bdkTrfPOlXA" frameborder="0" allowfullscreen></iframe>

[LTCM]

Haverá algum site que mostre uma lista de fundos que se baseiam em HFT e respectivas rentabilidades ? Já andei à procura e não consegui encontrar.

Não existe tal listagem os “players” dedicados só ao HFT (ainda) são muito pouco uns 25-30.

Global Electronic Trading Co, Jane Street Capital LLC, Hudson River Trading LLC, Wolverine Trading LLC, Jump Trading LLC, Automated Trading Desk, Tradebot Systems, Tradeworx Inc., Virtu Financial, RGM Advisors, IMC, Lime Brokerage, (…) são privados, dissimulados, inteligentes e relativamente desconhecidos ou até mesmo ocultos, não tem qualquer interesse em revelar as rentabilidades.

Alguns dos mais sofisticados hedge funds, quantitativos, multi-estratégia e criadores de mercado, como Renaissance Technologies LLC, Citadel Investment Group LLC, Millennium Partners, Tower Research Capital, DE Shaw, Worldquant, Telesis Capital LLC, Knight Capital Group, (...) todos tem “divisões” de HFT.

E claro todos os suspeitos do costume com os seus muito lucrativos “Proprietary Trading Desk’s”.

Bank of America Merrill Lynch
JP Morgan
Barclays Capital
BNP Paribas
Citigroup
Credit Suisse
Goldman Sachs
Deutsche Bank
Nomura
UBS
(...)

[MarcoAntonio]

Since the industrial revolution, we've had an irrational fear of technology.

Isto posto assim é um disparate: o receio da tecnologia nada tem de irracional per se e não há nada de errado em querermos regular a utilização que fazemos da tecnologia.

Talvez se eu "pegar" no autor e o colocar no centro da central nuclear de fukushima ele saia de lá disparado a correr e reveja o seu argumento...

Despite its undeniable ability to make life better, many of us remain paranoid that technological advances will end up destroying or replacing us.

Inegavelmente, a tecnologia também torna a nossa vida pior noutros aspectos que não aqueles em que ele está de momento a pensar, ignorando-os talvez em nome da posição que depois quer defender ao longo do resto do texto.

E não existe nenhuma evidência indiscutível que não conseguimos destruir-nos a nós próprios, enquanto existem indícios que sugerem que realmente podemos.

Ainda não aconteceu, é certo, mas o autor parece que só ficará convencido de qualquer forma no dia que acontecer. Não será um bocado tarde nessa altura para parar, pensar, reavaliar e gerir os riscos?

Scapegoating high-frequency trading will undoubtedly lead to more such controls, creating precisely the market dislocations regulatory public servants aim to end.

Em alternativa, temos o laxismo regulatório que contribuiu por exemplo à crise do sub-prime e, por arrasto, tudo o que se lhe seguiu...

[Automech]

Haverá algum site que mostre uma lista de fundos que se baseiam em HFT e respectivas rentabilidades ? Já andei à procura e não consegui encontrar.

[Automech]

High-Frequency Trading Fears Do Not Compute
By JONATHAN HOENIG

Since the industrial revolution, we've had an irrational fear of technology. Despite its undeniable ability to make life better, many of us remain paranoid that technological advances will end up destroying or replacing us. From "Modern Times" to "The Matrix," we're all familiar with this scary scenario.

It's also evident in the stock market, where not too long ago orders on the floor of the New York Stock Exchange (NYX: 27.73, -0.43, -1.53%) or Chicago Mercantile Exchange (CME: 272.07, 0.21, 0.08%) were scribbled on little slips of paper and hand-delivered by runners to traders at posts or in pits. Investing was expensive, cumbersome and slow.

Just as in every other aspect of life, technology has revolutionized markets for the better. It's now hard to imagine paying $90 in commissions to buy a stock, not to mention waiting 10 minutes for a call back confirming the trade. But while investors have come to expect the immediate transactions and liquid markets that technology affords, we also worry that technology might be rigging, or ruining, the market itself.

Take high-frequency, or computer-driven, trading, which analysts, news anchors and even investors themselves routinely blame for creating volatility in the market. May's "flash crash" was roundly pinned on high-frequency-traders, along with more recent swings in the market. The growth of such trading has prompted the Securities and Exchange Commission to discuss adding an even more disarraying prescript of limits and controls, the existing slate having already halted trading in a dozen stocks last week alone, including Exxon Mobil (XOM: 74.55, 0.54, 0.73%). Now U.S. prosecutors have joined the SEC in looking into "potentially manipulative" trading by high speed firms, according to published reports.

But high-frequency-trading is trading, not a smash-and-grab robbery. Whether it's humans executing orders face-to-face or computers acting on the instructions of humans is irrelevant: Investors buy and sell securities based on their own strategies and outlook, all with the intention of making a profit. It doesn't matter if you're trading with a five-minute outlook or a five-year outlook; with a little old lady in Shelbyville, Mo., or a server farm in Secaucus, N.J., computerized trading facilitates liquidity, price discovery and more productive markets.




And as a recent study from researcher Bespoke demonstrates, wild gyrations existed in the stock market long before high-frequency-trading. Over the past 50 trading days, the average daily percentage move in the Dow Jones Industrial Average has been around 0.90%., not far from levels seen over much of the past 111 years. Spikes in volatility have always been present in markets, and with the exception of the 2008 financial crisis, the biggest and longest lasting jump came in the early 1930s, long before the ballpoint pen, let alone computers and high speed trading, were even invented.

Similar fears about technology's impact on the stock market were voiced back in the mid-1990s, when "SOES Bandits," traders using a then-rudimentary electronic trading system, began providing liquidity in Nasdaq (NDAQ: 25.27, 0.13, 0.52%) stocks where entrenched market makers had long protected a de facto monopoly. "SOES bandits add to volatility because they pile into and out of stocks in rapid order," reported Investor's Business Daily in November of 1995, just as SOES trading had grown to 7% of Nasdaq's volume. Those fears dissipated once the market went up for five straight years. Funny how nobody has an issue with computer trading when stocks rise, only when they sell off.

I've written before about how market regulations, from trading halts to artificial price limits to bans on short selling and derivatives have a demonstrably negative impact on markets, making them more volatile, illiquid and prone to outright collapse.

Scapegoating high-frequency trading will undoubtedly lead to more such controls, creating precisely the market dislocations regulatory public servants aim to end.

Jonathan Hoenig is managing member at Capitalistpig Hedge Fund LLC.
http://www.smartmoney.com/invest/stocks ... 429032735/