For Superfast Stock Traders, a Way to Jump Ahead in Line – WSJ.com

By SCOTT PATTERSON and JENNY STRASBURG

Haim Bodek was a Wall Street insider at Goldman Sachs and UBS before launching his own [high-frequency] trading firm.

Mr. Bodek approached the Securities and Exchange Commission last year alleging that stock exchanges, in a race for more revenue, had worked with rapid-fire trading firms to give them an unfair edge over everyday investors.

He became convinced exchanges were providing such an edge after he says he was offered one himself when he ran a high-speed trading firm—a way to place orders that can be filled ahead of others placed earlier. The key: a kind of order called “Hide Not Slide”………

via For Superfast Stock Traders, a Way to Jump Ahead in Line – WSJ.com.

How to keep markets safe in the era of high-speed trading | Chicago Fed

By Carol Clark

With the chance of an order passing though controls at so many levels, how can things go wrong? One possibility Chicago Fed researchers found is that most of the trading firms interviewed that build their own trading systems apply fewer pre-trade checks to some trading strategies than others. Trading firms explained that they do this in order to reduce latency.

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. In fact, one firm interviewed had two incidents of out-of-control algorithms. To address the first occurrence, the firm added additional pre-trade risk checks. The second out-of-control algorithm was caused by a software bug that was introduced as a result of someone fixing the error code that caused the first situation.

The study also found that erroneous orders may not be stopped by some clearing BDs/FCMs because they are relying solely on risk controls set by the exchange. As noted earlier, however, risk controls at the exchange may be structured in such a way that they do not stop all erroneous orders.

via Chicago Fed Letter (PDF)

BD = broker-dealer

FCM = futures commission merchant

NYSE to Pay $5 Million Penalty to SEC – WSJ.com

By CHAD BRAY

NYSE Euronext NYX +2.23% agreed to pay a $5 million penalty to settle allegations by the Securities and Exchange Commission that technology issues at the New York Stock Exchange gave some customers an “improper head start” on trading information. The case marks the first time the SEC has ever brought a case that resulted in a monetary penalty against an exchange.

via NYSE to Pay $5 Million Penalty to SEC – WSJ.com.

ASX revenue from high frequency trading soars

A new data center, catering for high-speed trading, is becoming a major revenue-source for the ASX. My concern is that this could change the entire focus of the ASX, outweighing revenue from traditional stock market trading. Tom Steinert-Threlkeld at the Securities Technology Monitor writes:

The Australian Securities Exchange Group said Thursday that its revenue from Technical Services in its 2012 fiscal year topped the amount of revenue it received from stock market trading……

The growth in Technical Services revenue came as the company introduced different order types and execution services, and completed a state-of-the art data center. That data center operates at high speed and handles high volumes of trading orders, from computers belonging to trading firms that are located inside its walls. ASX said it was hosting 59 clients in the new data center as of June 30.

via Stock Trading Revenue Topped by Technology at Australia Exchange.

 

Nanex ~ High frequency traders at work [video]

High Frequency Traders (HFT) jam thousands of quotes in MasterCard stock at the millisecond level on May 16, 2012.
From Eric Hunsader – Nanex

Entire video shows about 5 seconds of time, slowed so you can see what goes on at the millisecond level.
Each box represents one exchange. The SIP (CQS in this case) at the bottom shows the National Best Bid/Offer.

Watch how much Best Bid/Offer changes in a fraction of a second. The shapes represent quote changes which are the result of a change to the top of the book at each exchange. The time at the top of the screen is the time of the last quote or trade update in Eastern Time HH:MM:SS:mmm (mmm = millisecond).

Every exchange must process every quote from the others — for proper trade through price protection. This complex web of technology must run flawlessly every millisecond of the trading day, or arbitrage (HFT profit) opportunities will appear. If any of the connections are not running perfectly, High Frequency Traders can profit from the price discrepancies that result. It is easy for HFTs to cause delays in one or more of the connections between each exchange.

New Research Busts High-Frequency Trading and Dark Pool Myths — CMCRC

Press Release: Capital Markets Cooperative Research Centre

CMCRC, the Australian independent academic centre for capital market research, has found that high-frequency trading (HFT) actually benefits capital market structures and performance, while dark pools may have damaging effects.

Speaking at an event in Beijing, Professor Frino outlined his research that showed that HFT activity adds real liquidity to markets and has no impact on price volatility — surprising findings, as HFT has regularly been accused of negatively impacting these measures of market quality.

“High frequency traders now account for more than 50 percent of trading volume in some global markets, whereas seven years ago it was virtually absent from markets,” Professor Frino said. “Alongside this trend is an explosion in so-called ‘dark pools,’ in which investors are executing their trading in invisible or non-transparent markets. Dark pools are making trading on exchanges less relevant.”

via New Research Busts High-Frequency Trading and Dark Pool Myths — CMCRC – Yahoo! Finance.

BBC News – High-frequency trading and the $440m mistake

……There are two rather more predatory strategies. One is called algo-sniffing. Here, a super-fast computer tries to find other computers going about their everyday business of buying or selling shares, and figures out what they’re going to do and when.

The algo-sniffer can then get ahead of the game and exploit the slower computer. And of course you could have algo-sniffer-sniffers and algo-sniffer-sniffer-sniffers in a high-frequency arms race. No wonder speed can be so important.

And finally, a particular sub-category of the algo-sniffer is the spoofer, which deliberately makes fake offers designed to lure other computers to show their hands, then cancels the offers. Spoofing might be illegal, or at least against the rules of stock exchanges, but it’s hard to prove that it’s going on.

Andrew Haldane, executive director for financial stability at the Bank of England:

“What we have out there now is this complex array of multiple mutating interacting machines, algorithms. It’s constantly developing and travelling at ever higher velocities. And it’s just difficult to know what will pop out next. And that’s not an accident waiting to happen, that’s an accident that has been happening with increasing frequency over the last few years.”

via BBC News – High-frequency trading and the $440m mistake.

Plans for curbs on high-speed share trading | The Australian

ASIC deputy chairman Belinda Gibson says automated trading needs robust controls. The corporate watchdog has blamed high-frequency trading for a big jump in the number of issues referred for investigation in the June half-year.

“This type of trading, and algorithms generally, continue to be of concern,” Ms Gibson said. “The measures we are proposing will strengthen our protection against the type of disruption we have recently seen in other markets.”

via Plans for curbs on high-speed share trading | The Australian.

How High Frequency Trading Robots Are Creating a Bumpy Ride for Main Street – NASDAQ.com

By Barbara Cohen

While HFTs may argue that they bring liquidity to the Market, they cannot dispel the concerns that liquidity comes at a very high price to investors – increased volatility. In a report issued in September 2011, associate professor Frank Zhang of Yale University stated that once an instrument’s share volume exceeds 50%, trading becomes basically a “hot potato,” as HFTs trade the same positions, passing them back and forth amongst themselves. Inter-firm trading all but eliminates “Price Discovery,” determining share price by normal supply and demand factors, such as news events or positive/negative earnings releases.

Inter-firm high frequency trading also wreaks havoc for Main Street investors because of “cross spreading.” So many liquid stocks, such as BAC and MSFT, now execute in milliseconds, resulting in extreme “competition” for Main street investors. Queues to enter and exit are significantly longer, with hundreds of shares waiting to execute. Long queues force Main Street investors into the vulnerable position of having to buy at the offer or sell at the bid, a trading method known as “crossing the spread.”

via How High Frequency Trading Robots Are Creating a Bumpy Ride for Main Street – NASDAQ.com.

West Australian: Small investors getting burnt

Computer-based trading has meant that the market is no longer fair, writes David Tasker.

The Australian Securities Exchange is seen by many as one of the most transparent markets in the world, a place where everyone is informed at the same time and where investors big and small can trade shares on equal terms.
The ASX says of itself and its own standards:”By providing systems, processes and services needed for a fair, orderly and transparent market, ASX inspires confidence in the markets.” Unfortunately, the emergence of computer-based trading has meant that the market is no longer fair, orderly or transparent and therefore confidence in the market is at an all-time low. These online trading houses are making vast sums of money and the mum and dad investors, who are the lifeblood of the exchange, are being severely disadvantaged. In Australia, it is believed that computer-based trading accounts for up to 30 per cent of the total volume on the ASX and in the micro-cap/ mid-cap area of the market it may be as much as 50 per cent of trading volume.

High Frequency Trading

Computer-based trading is not new — it has existed in the US and other international markets for years — but we have only seen the emergence of this type of trading on the ASX in the past year. In essence, there are two types of computer-based trading platforms, algorithmic trading and high frequency trading. Both are managed by complex computer programs that have no interest in the core drivers of investment decisions, such as a company’s assets, its management or its prospects — only the ability to generate profit from trading. Algorithms create masses of small orders which can be observed being traded in certain patterns throughout the day and are used to acquire, or dispose of, large parcels of shares in a manner so as to not affect the market in those shares.

Here is where it becomes a problem. High-frequency trading participants also use algorithms to firstly detect another algorithm trying to orderly dispose or acquire shares, then preys on the big order it has found that is being executed into the market. The high-frequency trading algorithm will then begin to place orders into the market that are in front of the original algorithm, forcing the original algorithm to buy at higher and higher prices. Meanwhile, the HFT algorithm has been buying shares ahead of the original algorithm and then selling them at a higher price, all the while using the original algorithm to drive the price into its favour. This sets the original buyer at a disadvantage because it has created an unfair and false market.

The same situation can occur while pushing the price of the stock downwards. An HFT algorithm acts fast when it sees these orders. It “flashes” its offers and bids into the market in milliseconds so that they are almost impossible to transact except via other HFT orders. When they come against each other or find each other acting in unison, there is no manual override. Recently this was seen in the US where Knight Capital lost $US440 million and is also what is believed to have caused the 2010 flash crash when the US market dropped 1000 points and then recovered within minutes. Billions of dollars were wiped out, gone, investments destroyed, retirement funds wrecked, lives altered.

But where it really begins to turn nasty is when two or more HFT algorithms begin to work against one another, resulting in the share price being forced in a more extreme manner — either up or down. In unfavourable economic times, when normal market investors are thinner than usual, the direction is more than likely to be in the downwards direction.Which companies are most affected? High-volume, mining companies who make up almost half of those listed on the ASX (950 out of 2200 ASX listed companies) are particularly vulnerable. Some would say this is the market in action and liquidity is being created. The problem is genuine participants are being used as cannon fodder: Institutional brokers are also being affected, having to depend on HFT at micro commissions which offset their ability to run a traditional equities brokerage.

The winner is the professional trading houses and in a zero-sum game like the bad market we are in, retail investors are potentially the big losers — they can’t operate as fast and don’t have the huge computer power available and straight to market execution systems that these guys have. Up to 50 per cent of trading in smaller ASX-listed companies is being done by computers with no interest in the company, its assets, its people or its prospects and at a speed far superior to human trade. If an operator manually entered HFT-type trades, they would be penalised for manipulative trading — why should there be one rule for man and another for machines programmed by man?

David Tasker is the national director of Investor relations at Professional Public Relations