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.

Asia: India recovers but China & Japan bearish

India’s Sensex broke resistance at 17500, signaling a primary up-trend. Expect an advance to 18500*. Rising 13-week Twiggs Money Flow — above zero — indicates strong buying pressure.

Sensex Index

* Target calculation: 17.5 + ( 17.5 – 16.5 ) = 18.5

NSE Nifty is testing resistance at 5350. Breakout would confirm the Sensex primary up-trend. Rising 63-Day Twiggs Momentum is promising but we need a trough above zero to signal a strong up-trend. Target for the breakout would be 5650*.

NSE Nifty Index

* Target calculation: 5350 + ( 5350 – 5050 ) = 5650

Understanding Momentum

Momentum is an oscillator, so you would expect equal peaks if the trend is constant. If oscillating above zero, it would be a constant up-trend; below zero, a constant down-trend; with zero at the mid-point, a ranging market. Divergence should ideally show a clear transition from one to the other or at least a sharp difference in the height of peaks or troughs. A trendline drawn under rising momentum will indicate that momentum is accelerating; a trendline break would indicate slowing acceleration — not necessarily a reversal.

Japan’s Nikkei 225 index is testing resistance at 9000 but 13-week Twiggs Money Flow continues to warn of strong selling pressure, with a peak below zero. Breakout above 9000 is unlikely, but would signal an advance to 10000. Failure of support at 8200 would indicate another test of the 2008/2009 lows at 7000*.

Nikkei 225 Index

* Target calculation: 8000 – ( 9000 – 8000 ) = 7000

China’s Shanghai Composite Index retreated below support at 2150; follow-through below 2100 would indicate a decline to 2000*. Declining 63-day Twiggs Momentum continues to signal a primary down-trend.

Shanghai Composite Index

* Target calculation: 2250 – ( 2500 – 2250 ) = 2000

Hong Kong’s Hang Seng Index is more bullish, consolidating above resistance at 20000. Follow-through would indicate an advance to 22000*.  Recovery of 63-Day Twiggs Momentum above zero would suggest a primary up-trend.

Hang Seng Index

* Target calculation: 20 + ( 20 – 18 ) = 22

Singapore’s Straits Times Index is similarly consolidating above former resistance at 3040. Rising 63-day Twiggs Momentum — above zero — indicates the primary up-trend is intact. Calculated target is 3300* but the trend channel suggests resistance at 3200.

Singapore Straits Times Index

* Target calculation: 3000 + ( 3000 – 2700 ) = 3300

Slower Growth in Asia Brings Down Stocks – NYTimes.com

By THE ASSOCIATED PRESS

Published: August 13, 2012

Stocks fell Monday as evidence piled up that the global economic slowdown was hurting Asia.

Japan’s economy grew in the second quarter at a 1.4 percent annual rate, slower than many analysts had expected. Last week, China released dismal figures on retail sales and exports in July. Traders were disappointed that Beijing failed to introduce stimulus measures over the weekend……

via Slower Growth in Asia Brings Down Stocks – NYTimes.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

Gary Shilling: Global Slowdown, Only Time Can Heal the Economy

Gary Shilling: If we have a consumer-led recession it will be very different to previous post-WWII recessions which were always led by the Fed.

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Which Country Has the Best Government? – SPIEGEL ONLINE

The Craft of Ruling: Which Country Has the Best Government?
By Bernhard Zand

American political scientist Charles Kupchans claims that there is a “mismatch between the growing demand for good governance and its shrinking supply,” putting Western powers under pressure. He says it’s no coincidence that the political systems in the US, Europe and Japan are all discovering their limits almost simultaneously. Their traditional tools, such as their currency control instruments, have repeatedly proven to be powerless when faced with the sheer might of global financial groups. Likewise, democratic governments, which rely on the approval of their electorate, “have proved far better at distributing benefits than at apportioning sacrifice.” Worse still, many likeminded Western democracies no longer see eye-to-eye on how to solve global problems, from climate change to the isolation of Iran.

via Good Governance Series: Which Goverment Is Best – SPIEGEL ONLINE.