Event Processing blog

John Bates Recognized as Financial Technology Leader by Institutional Investor

Today we’d like to congratulate our own CTO John Bates on his recognition as one of Institutional Investor’s top Tech 50: The Difference Makers. This is the second year that John’s work with Progress Apama and Complex Event Processing has been recognized by Institutional Investor as a top financial technology leader. This is an especially exciting award, given that Progress was the highest-ranking technology provider on this year’s list.

Institutional Investor recognizes each leader for their vision and agility in translating innovation into operational and competitive advantage. They recognize John’s membership on the U.S. Commodity Futures Trading Commission's technology advisory committee and Progress’s contribution to performance gains. Due to economic outlook, technologists today have to “do more with less”, says Institutional Investor, and John’s work with Progress Apama and Complex Event Processing contributes to that process.

They also recognize Progress’s work in two geographical hot spots, China and Brazil, which has been a hot topic in the capital markets world lately. They quote Bates saying, "Countries like China and Brazil are starting to accelerate their adoption of algo trading.”

Congratulations John, we’re proud to have you on our team!

 

Only You Can Prevent Flash Crashes

Faster than a forest fire, the May 6th, 2010 flash crash was a breathtaking nearly-1000-point drop-then-surge on the Dow Jones Industrial Average that shocked traders and the general public to their core. Unlike Smokey the Bear, who can sniff out and fight fires before they start to flame, US regulators only became aware of the flash crash after it was over. The flash crash left scorch marks that have scarred the reputation of the bulwark U.S. stock market and singed investor confidence.

Regulators were completely stumped as to the cause. Months of investigations unearthed one very important piece of information: the regulators were unprepared and ill-equipped to deal with this kind of event. They had no method of sniffing out the smoke that could lead to a flash crash fire.

A year ago, the flash crash revealed the first significant sign of growing pains in a new generation of trading. This new generation introduced the capacity to let computer models do the dealing; it allowed clever traders with clever programmers to build complex algorithms that buy and sell in the blink of an eye. All of this progress was made with little thought to the possible repercussions of a mistake.

Thus it was that on May 6th, 2010 when a mutual fund in Kansas entered a rather large ($4.1bn) sell order in E-mini S&P 500 futures contracts on the CME, the reverberations were felt throughout the marketplace. The order sparked a totally human panic on a day when fear was in the air and sentiment was leaning toward the bearish. The fire was then fanned by algorithmic trading strategies and HFT, causing an unprecedented drop within minutes and wiping out $1 trillion in market value before recovering. That a simple mistake could take the market down so fast was unthinkable.

Since the original flash crash we have seen dozens of smaller ones, which barely warranted a thimbleful of ink in the press:

• A mini flash crash nearly wiped out ten ETFs on Nasdaq OMX and NYSE Euronext on March 31st. The exchanges (quicker off the mark this time than on the May 6th flash crash) cancelled some of the trades in 10 out of 15 Focus Morningstar ETFs that had just been launched. Some of them tumbled by 98% before circuit breakers kicked in. The culprit appeared to have been a human being with fat fingers;  ETF market maker Knight Capital Americas took the blame.
• Last September the CME Group plugged some new contracts into Globex to try them on for size and they mistakenly went live. They were almost instantly traded - for about six minutes. Futures brokers noticed oddly anomalous spread price activity during that period, when trading is usually slow, and CME pulled them off.
• In the oil market last year high frequency trading firm Infinium Capital Management's brand new trading program malfunctioned and racked up a million-dollar loss in about a second, The new algorithm went live four minutes just before markets closed on Feb. 3rd and fired off 2000-3000 orders per second before being shut off. It caused a spike in trading volumes by nearly eight times in less than a minute and the oil price surged $1 then slid $5 over the course of the next two days.

And as energy and other asset classes outside equities - commodities, FX, derivatives - become increasingly automated there will be more flash crashes. Increased interdependence of asset classes will lead to cross asset flash crashes – a domino effect where the crashes 'splash' across asset classes, possibly wreaking havoc for market participants and regulators.  As regulators said following the flash crash: "a complex web of traders and trading strategies"  links the fragmented multitude of markets here in the U.S.    

Band-aids have been applied by the SEC; circuit breakers that prevent further trading when a stock moves more than 10% during a five-minute period. Market makers have been strong-armed to ensure they don't disappear when the market wobbles. The joint CFTC-SEC Advisory Committee on Emerging Regulatory Issues has made 14  recommendations on the May 6 Flash Crash including: implementing a limit-up/limit-down system, more extensive market access rules, studying the impact of maker-taker pricing and cancellation rates, and looking at a more cost-efficient audit trail.

These are a good start, but far from address the underlying problem. Like Smokey the Bear, regulators need a way to sense the smoke before the fire takes hold of the marketplace. Luckily there exist responsive and intelligent algorithms that can sense and react instantaneously to market anomalies and anticipate interruptions to liquidity. These rapid response algorithms could help to prevent the next flash crash by alerting risk and compliance managers of impending issues, or by changing trading strategies to accommodate market glitches. They can smell the virtual smoke and help to put out the fire before it starts.

On top of smarter algos, there are a few other splash crash prevention measures:

• Diligent backtesting – using historic data and realistic simulation to ensure many possible scenarios have been accounted for. A backtesting process needs to be streamlined of course – as short time to market of new algos is key. 
• Real-time risk monitoring - building a real-time risk firewall into your algo environment. Just like a network firewall stops anomalous network packets reaching your computer, so a risk firewall should stop anomalous trades getting to trading venues. 
• Real-time market surveillance. Even if trades do not breach risk parameters, they may breach compliance rules, regulations or may be perceived by a regulator as market manipulation.

Everyone needs to be proactive in using the correct tools to monitor algorithmic trading. Sensing and responding to market patterns before the aberrations or errors have a chance to move prices is the right thing to do - in all asset classes. Brokers need better pre-trade risk controls to prevent fat fingered trades from getting to market. Algorithmic trading means that the market moves too fast for exchanges or other venues to detect problems before they impact prices.  The detection of abusive patterns must happen in real-time, before any suspicious behaviour has a chance to move the market. This approach should be taken on board not just by the regulators, but by the industry as a whole. Only you can prevent flash crashes. 

 

Fixing the Fat Fingered Faux Pas Epidemic

The age of electronic execution has brought with it a niggling problem - fat fingered trading. A fast-paced, stressful trading environment creates an ideal incubator for hatching mistakes. They are often simple mistakes and involve pressing the wrong key on the keyboard, possibly at the wrong time and/or even for the wrong thing.

Anecdotal evidence would have us believe that fat fingered trading is rife. Real-life fingers pushing the wrong buttons include incidents as recent as January when human error caused the Canadian dollar to slump in Asian trading hours. The U.S. dollar shot up from around C$0.99 to over C$1.0030 against the Canadian dollar before immediately dropping back down, Reuters reported. The spike in the rate had little long-term impact on the market as a whole. These sorts of mini-flash crashes happen on a regular basis in many instruments. 
Higher profile fat fingers include:

·         In September 2006 a Bank of America trader’s keyboard was set up to execute an order when a rugby ball landed on it and executed the $50 million trade ahead of schedule. 
·         In June 2005 a Mizuho Securities Trader sold 610,000 shares at 1 yen instead of 1 share at 610,000 yen at a loss of approximately $225 million.
·         In October 2002 a Bear Sterns trader caused a 100 point drop in the Dow Jones Index after entering a 4 billion share sell order rather than 4 million. 
·         In May 2001 a Lehman Brothers dealer in London wiped £30 billion off the FTSE when he inadvertently keyed in £300 million for a trade instead of £3 million, causing a 120-point drop in the FTSE 100.

Human error is part of being human. But what about algorithmic error? Algos, created by humans, can also have fat finger days. Last year the New York Stock Exchange fined Credit Suisse Securities $150,000 for failing to control an algorithm that went haywire in 2007 flooding the exchange trading system with hundreds of thousands of erroneous orders.

Honest mistakes are one thing, but there are also an increasing number of incidents of rogue traders, fraud and greed-gone-wrong. One famous rogue was the 2009 so-called drunken trader - a broker at PVM Futures who clocked up a $10 million loss from trading while intoxicated. A much larger and more grandiose deception occurred in 2008 when Jérôme Kerviel was discovered to have hidden losses valued at approximately €4.9 billion at Société Générale. And a commodities trader at MFG lost $141.5 million in 2007 on a big short position in wheat futures because his management had turned off the trading limit controls. They claimed that the controls “slowed things down” in a classic greed-gone-wrong story. 

Looking at this compendium of fat finger or algorithmic errors and fraudulent or rogue trading, I think we have been lucky so far that their impact has not been more serious. The scary thing is that things could have gone a lot more wrong. The flash crash illustrated how quickly things can move and how inter-related the markets are. In 2010 we have seen incidents in equities, futures, FX and oil markets. A cross-asset “splash crash” that cascades across multiple markets is theoretically possible – whether it’s accidental or even premeditated. 

Fears of algorithmic terrorism, where a well-funded criminal or terrorist organization could find a way to cause a major market crisis, are not unfounded. This type of scenario could cause chaos for civilization and profit for the bad guys and must constitute a matter of national security.

So what can be done? Better real-time monitoring and market surveillance, real-time risk and internal policing – by trading firms, trading venues and regulators. The markets should be free – but protected. Real-time visibility as to what is going on and real-time response to make course corrections when needed is crucial. Discovering or predicting problems and then being able to take immediate corrective action may help to save the world. 
 

Beware the Splash Crash

We have had the flash crash, the breathtaking 1000-point drop-then-surge that happened on May 6th, 2010. In the near future we will have a new worry - prepare for the “Splash Crash”, which will cross asset barriers in a single bound.

As asset classes outside equities - energy, commodities, FX, derivatives - become increasingly automated there will be more flash crashes. Increased interdependence of asset classes will lead to cross asset flash crashes – a domino effect where the crashes 'splash' across asset classes, possibly wreaking havoc for market participants and regulators.  

As regulators said following the flash crash: "a complex web of traders and trading strategies" links the fragmented multitude of markets here in the U.S.  And, like dominoes, when one goes the rest follow. The dominos are no longer limited to one asset class. Algorithms are becoming increasingly sophisticated, encompassing all of the elements that may impact a trade in a certain instrument. If a trader wants to take a substantial position in a foreign equity, for example, there are many ingredients that can affect its market price.

Consider news events such as the BP oil spill or the current political crises in Egypt and Tunisia. The impact of these events has illustrated the close relationship between the oil price, equities, foreign exchange, commodity futures and the bond markets. Extreme and possibly unexpected events coinciding can trigger a cascade. We saw with the flash crash how instability in European economies caused nervousness in the market and then an algorithm did something unexpected – causing a cascading effect across futures and equities markets. As the cross-dependencies grow and algorithms become more inter-twined, so the risks for a “splash crash” grow.

It’s not hard to consider a splash crash scenario given the growing inter-linking of markets. For oil companies, such as BP, equity trader’s positions can be affected by the price of the pound and UK interest rates, as well as the dollar and any countries currencies where it is exploring or supplying oil. Oil prices will impact the bottom line, therefore the share price. Political events such as wars in oil-producing countries are important, as are disruptive events such as oil spills, and can impact oil, equity, bond, commodity future and foreign exchange prices. What if China's economy falters and its oil consumption is predicted to fall? Oil prices globally fall, dragging the US dollar higher. Oil derivatives predicting that prices would stay high for the next year or two or three also fall. Share prices for the whole oil sector including BP, Exxon Mobil, Texaco, Chevron, Philips, Sinochem, etc. collapse. Debt markets are stunned and bond rates rally.

All of these factors can be programmed into an algorithm that monitors and makes trading decisions on the BP position. If large banks and hedge funds also have substantial positions in BP, the dollar, the debt and the derivatives and they also have algorithms that will kick in when certain parameters are met. If enough instability and unexpected conditions occur and then one of these algorithms does something strange or unexpected, the cascading impact could be enormous across all asset classes. For example, massive automated sell orders for oil shares, energy futures and derivatives and buy orders for USD and Treasuries. Trading systems could clog up, limited bandwidth could choke orders, exchanges could freeze up - splashing across all of the affected asset classes. Pandemonium.

Splash Crash Prevention Tips

Luckily there exist ever more responsive and intelligent algorithms that can react instantaneously to market anomalies and anticipate interruptions to liquidity. These rapid response algorithms could help to prevent the next flash crash by alerting risk managers of impending issues, or by changing trading strategies to accommodate market glitches.

On top of smarter algos, there are a few other splash crash prevention measures:

• Use real-time pre-trade analytics and risk management. If the mutual fund in question on May 6th or its executing broker had done a thorough back-test of its trading strategy, using some of the dire indicators present, it might have thought twice about selling so aggressively - possibly preventing the crash.
• "Light up" the algorithmic trading process. Visibility during the trading process is crucial. Surveillance technology exists than can monitor the markets for anomalous behaviour and alert the parties involved if it is spotted. Give the regulators the tools, too. 
• Homogenize trading rules across all exchanges and ECNs. When one halts trading they all halt - for the same amount of time.

 

US and UK to Lose Ground as Algorithms and HFT Emigrate

High frequency and algorithmic trading will blossom in emerging markets such as Brazil and India, possibly signalling the end of US and UK dominance in financial markets.

Even as regulators in the US and Europe debate over how to regulate algorithmic and high frequency trading (HFT), firms in emerging markets such as Brazil and India are embracing the trading practices. US and UK proprietary trading firms and hedge funds are opening offices in emerging markets centers, partly to take advantage of these budding opportunities. But there is more than greener pastures calling them; stricter regulations in the US and UK may force large banks and hedge funds to trade in - or move to - more lightly regulated regimes. This mass regulatory arbitrage emigration could signal the end of US and UK dominance in financial markets.

Brazil is attracting HFT like bees to honey. The world’s tenth largest economy, Brazil's exchange, BM&FBovespa, trades everything from cash stocks to commodity futures. The exchange has recently undertaken steps to further automate trading in an effort to capitalise on investor interest and gain more business from outside the country. Almost 90% of trading is now done electronically and about 10% on the floor. Demand for connectivity and trading access to the Brazilian market is increasing; exchanges are helping to upgrade Brazilian exchange platforms and bridge the gap between Brazilian markets and non-Brazilian traders (and vice versa). Technology vendors are building ticker plants for real-time, low latency market data as well as adding connectivity and algorithmic trading capabilities. And brokers are clamouring to join up with, or buy, Brazilian brokerage firms to help smooth the path for non-Brazilian customers - which by law must have local representation.

Algorithmic trading in India is also taking off. Spending on software for algorithmic trading is going to be easily worth $100 million in two years. The market share of algo trade will rise from 15 per cent at present to 50 per cent in the next three years. The number of trades on the NSE (National Stock Exchange) are 10 times that of the London Stock Exchange. Both NSE and BSE (Bombay Stock Exchange) are offering co-location facility; smart order routing and mobile trading has now been allowed, too. Also, commodity exchanges are catching up on algo trading. It is being put to use in foreign exchange derivatives too. That’s an enormous reason to do algorithmic trading. Smart order routing will force inefficiency out of the market, reduce price discrepancies between the two main equity exchanges and increase competition. (NSE’s process of validating every algo was putting a significant brake on its growth. The process is unsustainable and will be short-lived.)

Turkey’s main bourse, the Istanbul Stock Exchange, was the latest to open up to HFT and algo trading, according to the FT. Mexico is opening up, as are Asia Pacific markets in Japan, Australia, Singapore and Hong Kong. Bulge bracket banks, large hedge funds, and buy-side firms are all gearing up for the next onslaught of HFT in these areas, which may take business away from the more regulated markets.

Few of these markets are as heavily regulated as the US and Europe for this kind of trading. But regulated or not, any market that embraces HFT and algos has an obligation to make sure that they will not cause new issues such as flash crashes. Mandatory pre-trade risk and market surveillance should be there within the regulators and the exchanges. Regulators have had a rear-view mirror approach when it comes to understanding market software. They do not have the capability to know what is happening on a real time basis. The technology that SEC, the US stock market regulator, was using was two decades old. Regulators have to catch up here. All parties in the trading cycle should take more responsibility to ensure appropriate risk control and surveillance. Then perhaps algo trading can be fluid, with risk managed across borders. And the dominant players will go with the flow, retaining their HFT crowns.

 

Red Flags in Morning, Firms Take Warning

A pattern is emerging within new financial services regulations where regulators and financial services firms deploy monitoring technology to "red flag" potential issues such as risk, position limits, errors and manipulation. The "red flags" raised would then alert the relevant personnel or authorities.......... See the full post here

CEP in 2011 and Beyond....

As we approach the end of 2010 and we begin to see a tiny crack of light at the end of the financial crisis tunnel, there are many theories as to which technologies will lead us into the next phase of advancement in financial markets. Stubborn issues with latency, high frequency trading, real-time risk management, and market gaming/fraud continue to dog the industry and provide fertile ground in which new and existing technologies can innovate. In fact, technology consultancy Ovum said in its 2011 Trends to Watch report for financial markets (http://tinyurl.com/2vv42sh) noted that Complex Event Processing is one technology to watch. 

CEP will be the lifeblood for financial services as regulation increases, markets further fragment, and algorithmic trading becomes engrained in all asset classes. A recent Progress Software survey across industries showed that only eight per cent of enterprises globally are able to report business information in real-time. Without instant visibility into business activity organisations cannot possibly determine what is or is not working and then set the right course of action.

In financial markets, in particular, a lack of visibility between exchanges, ECNs, dark pools, brokers, banks, buyside and trading firms is causing breakdowns in the system. When you see increasingly frequent events setting markets on their ear such as the May 6th flash crash, insider trading activity, fat fingered errors and rogue algorithms, it becomes crystal clear that something needs to be done. 

Progress, with its Apama products, is committed to financial markets along with other, newer markets such as aviation and telecommunications that are opening up to CEP. If you would like further information about the future of CEP and would like to speak to one of the two founders of Progress Apama— yours truly or my colleague Dr. Giles Nelson—then please contact us. 

 

Arming the Regulators

According to a Wall Street Journal article (http://tinyurl.com/2vds85m), a CFTC internal report found that the regulator has major communication problems between its enforcement and market oversight divisions. The article says this impedes "the overall effectiveness of the commission's efforts to not only detect and prevent, but in certain circumstances, to take enforcement action against market manipulation."

 

The SEC has admitted in the past to being hamstrung by budget limitations, as has the CFTC, in its attempt to detect fraud and market anomalies. In the UK, the Financial Services Authority likened the struggle to "chasing a Ferrari whilst riding a bicycle." I have mentioned before (http://tinyurl.com/36yp2cc) that regulators have fallen behind in scrutinizing the markets because they are at the mercy of annual budgets set by painful negotiations with Congress. The regulators have been at a disadvantage and are now running to catch up.

 

Regulators are now working on new rules under the Dodd-Frank Act anti-manipulation and anti-fraud provisions that will give them greater powers to pursue and enforce lawbreakers.

•            Section 753 of the Dodd-Frank Act significantly expands the CFTC's authority to pursue fraudsters and market manipulators in OTC and exchange-traded swaps, commodity and futures contracts.

•            Section 763(g) says that the SEC has authority to pursue fraud, deception, and manipulative conduct in connection with security-based swaps.

 

The new rules may help the SEC and CFTC to enforce the law, but there are many other obstacles preventing them from catching market manipulation, fraud or fat fingered trading errors before they damage the markets. Cross-firm communication is clearly one. A lack of oversight, central monitoring and surveillance capabilities are others.

 

Wall Street banks and hedge funds pour vast amounts of money into hiring the best quantitative analysts to work for them and buying the latest and greatest technology. Regulators cannot match the investments made by the industry they are supposed to police.

 

There is a solution. Market surveillance and monitoring technology exists that can 'see' major price and volume spikes in particular instruments, how often they happen and maybe even why, and whether a pattern in market behavior caused them. Such monitoring can flag up liquidity concerns and monitor how liquidity moves across venues, which is highly relevant to the flash crash. Monitoring can also spot unusual patterns that might be triggered by rogue algos or rogue traders. In these scenarios, key information can appear on real-time dashboards, or heat maps, showing the "hotness" of particular instruments or potential worrying patterns. Intelligent algorithms can detect when patterns repeat themselves, possibly signaling a problem or trend. These algos can be programmed to 'learn' from scenarios, whereby they can be encoded so that the detection, alerting and response to such a scenario can be automated.

 

According to the Center for Responsive Politics, the army of Wall Street lobbyists is growing exponentially (http://tinyurl.com/3aydrpe) and marching to Washington in an attempt to temper the Dodd-Frank bill. No matter how much the bill changes in the future, regulators will still be responsible for making the markets safe for investors. Regulators will need technology on their side.

 

Breaking the Machines

(This piece originally appeared on TabbForum - linked here)

 

The furore over high frequency trading and rogue algorithms is turning these important trading tools into fodder for the mainstream media. As part of the Commodity Futures Trading Commission's Technology Advisory Committee (TAC), I had high hopes that my colleagues and I would be an instrumental part of solving some of these issues that very publically dog our markets, including mechanisms for detecting or even preventing another flashcrash, stopping algorithms going out of control and curbing rogue traders. I believe the vanguard of such market improvements is not draconian restrictions on trading algorithms but rather regulator-led best practices and market policing. If the right measures are implemented and suitably publicized, it would address the market’s nervousness and have algorithms smelling fragrant once more.

 

I was thus a little disheartened by the second TAC meeting last week (Technology: Achieving the Statutory Goals and Regulatory Objectives of the Dodd-Frank Act). Given the public fear that algorithms and high frequency trading are evil, I was concerned when one commissioner even went so far as to ask the question in his opening remarks as to whether algorithms should be banned completely. If this ever did happen in the US, heaven help our economy. I would equate such an action to the Luddites – a group in 19^th Century Britain that broke machines to protest against the industrial revolution. Algorithms are not evil; there are many positive aspects of algorithms and HFT. They minimize the market impact of large trades, lower the cost of execution, make more open and efficient markets, allow trading venues to evolve faster, encourage entrepreneurship and increase trader productivity, among many other things. Banning what is essentially the new industrial revolution, and now an integral part of electronic trading, could take us beyond a double dip recession and back into the dark ages.

 

A few key points came out in the flash crash report that really need to be emphasized. A key one is that there is a difference between algorithmic execution strategies and high frequency trading strategies. The former are manually set up and are designed to break up a large trade, typically executed in a broker on behalf of a buy-side customer. The latter are much more automated and continuously look for trading opportunities to act on, typically operated by a prop shop or hedge fund. The latter sounds scarier – but it was actually the former – or one particularly extreme instance of the former - that got the lion’s share of the blame in the joint SEC-CFTC report. HFT was pretty much exonerated. It was really human error in the way the execution algo that traded the E-mini was set up that was at fault. In fact one of the TAC participants actually made the point that many of the HFT algos had smarter monitoring built in – which made them pull back from the market when it started to go haywire. Yes that withdrew liquidity – but the HFT algos behaved sensibly given the circumstances.

 

Commissioner Scott O’Malia asked the question whether a rogue algorithm is the same as a rogue trader. Great question! An algorithm does not “decide” to go rogue, unlike a human rogue trader who is more deliberate. Usually a rogue algo is a mistake – such as Infinium’s algo that went wrong and fired thousands of orders into the market in February (http://www.reuters.com/article/idUSTRE67O2QQ20100825) or CME’s test algo that fired phantom orders into the market in September (http://www.ft.com/cms/s/0/706c45dc-c00a-11df-9628-00144feab49a.html). But rogue algos can threaten the well-being of a marketplace just as a rogue trader can. Rather than banning or restricting HFT and algos it would be much more productive to look at how they and the market can benefit from effective controls.

 

Some suggestions that I made on the TAC as to how we might provide more confidence around algo trading are as follows:

 

Firstly, market participants should be mandated to do better back-testing and algo monitoring to help prevent rogue algorithms and scoundrel traders from entering the market. Testing the execution algo that went wrong on May 6^th under realistic market conditions might have prevented it going live. More intelligent monitoring might have made it pull out of the market before it did deep damage. Real-time monitoring can detect and respond immediately to dangerous market conditions, “fat finger” or algo errors and trading risk exposures being exceeded.  As illustrated by the HFT algos that stepped out of the market on May 6th – some firms have better monitoring technology than others! The CFTC and SEC could provide best practices guidance and maybe even recommend data sets, simulators and pre-production processes to help with this.

 

Secondly, Exchanges should continue to enhance their monitoring and surveillance systems. Clearly we’ve not perfected it yet given that a rogue algo within the CME managed to fire in phantom orders as recently as September. Also, to ensure consistent response to market crises, all trading venues in a particular asset class should have consistent circuit breakers, which operate under the same circumstances. This would avoid some of the problems discussed in the flash crash report.

 

And the CFTC (as well as the SEC) needs to be "mission control" to monitor across all markets and provide an early warning system. If firms believe they can be watched in real time they will be much more careful. Unfortunately, the CFTC’s Chairman suggests that there is no budget for such technology and that they will have to rely solely on controls by the exchanges and trading venues. This is unacceptable. The importance of trading to our economy means that ensuring confidence in our markets combined with allowing the world’s most advanced forms of algo trading - with the necessary safety measures to prevent meltdowns - is a matter of national security! The regulators are the US Marshalls to HFT's Wild West. The CFTC should go to Congress and make the case for a bigger budget. And they should strike while the iron is hot.

 

The flash crash may have been a mixed blessing, having pointed out many market structure issues that the regulators should be striving to correct or control. Until that day American stock markets were the envy of the world, the model for modern trading -- fast, stable, efficient and for the most part transparent (http://tinyurl.com/29bpr4r). That perception has changed and the rest of the world is aiming to avoid, not mimic, our model. It is critical that the US take the necessary steps to remain the shining example of capital markets. The technology is there, it simply needs to be used. Most importantly we must not allow negative publicity to lead us into Luddite-style regulation and break the machines that are fuelling this new industrial revolution.

 

When Does a Rogue Become a Scoundrel?

Now that the Dodd-Frank Wall Street Reform Act is signed into law, there lies a mountain of work ahead for regulators. Making sense of the 2,000+ page document and turning it into viable recommendations and regulations will be an arduous process.

 

The Commodity Futures Trading Commission's second Technology Advisory Committee meeting titled “Technology: Achieving the Statutory Goals and Regulatory Objectives of the Dodd-Frank Act,” will be held on October 12, 2010 at 1:00 p.m., in Washington, D.C. (http://tinyurl.com/2vfdp4n). At the meeting, my committee colleagues and I will discuss some of these goals and objectives. Specifically, as a result of the SEC & CFTC's report on the May 6th flash crash, CFTC Commissioner Scott O'Malia has said that he wants to take a look at whether algorithms that cause disruption in markets - rogue algorithms - should be treated as if they were rogue traders.

 

Commissioner O’Malia said in the announcement of the October 12 meeting: “While I do not believe that the flash crash was the direct result of reckless misconduct in the futures market, I question what the CFTC could have done if the opposite were true. When does high frequency or algorithmic trading cross the line into being disruptive to our markets? And, along those same lines, who is responsible when technology goes awry? Do we treat rogue algorithms like rogue traders?"

 

This is an interesting topic. When does an algorithm 'go bad'? Is it the algorithm's fault? Of course not, an algorithm does not decide to go rogue. It is down to human error - either in the programming or the execution thereof. In the case of the flash crash a mutual fund chose a 'dumb' execution algorithm preset with inappropriate parameters to execute a large futures sell order in a market that was - by all accounts - ready to plummet. This circumstance illustrates how rogue algorithms can evolve as an unintended consequence of circumstance and/or human misjudgment.

 

When a trader goes rogue it is more deliberate. It can be because he is losing money and hiding it - as in the case of Jerome Kerviel at SocGen, or maybe he had too much to drink at lunchtime and was feeling invincible - like Steve Perkins at PVM. The former lost the bank over $6bn, the latter lost his brokerage $10m. These were very human errors, effectively the work of scoundrels.

 

What rogue traders and rogue algorithms have in common is that both can, in many circumstances, be detected early - or even prevented - through the use of better technology. Comprehensive pre-trade analysis, including backtesting algorithms under a wide range of circumstances, could have prevented the 'dumb' May 6th algo from having its way with the market. Thorough real-time risk management and monitoring could have spotted Kerviel's limit-busting trading patterns and his hiding the trades. Pre-trade risk controls would have kicked the PVM trader out of the system before he got in too deep.

 

It is no longer acceptable to blame rogues and scoundrels for market anomalies or for banks, brokers and buyside firms losing money. The technology is there, it simply needs to be used.