With Progress Software Corporation’s recent acquisition of Apama’s ESP technology and Algorithmic Trading Strategy Platform, interest in the field is unlikely to wane.
Estimates suggest that 60 per cent of US buy-side firms use algorithmic trading – the automated execution of orders according to a predefined strategy to meet a specific benchmark.
One difficulty with algorithmic trading is definition: the term is used to describe various functions and support with regard to market structure. Rules-based trading and smart routing are other terms used to describe the practice. They are based nevertheless on computer programs written to take advantage of the huge flows of data, an area that is also growing exponentially. Although the depth of research in the area is gradually increasing, information within the public domain on the performance of algorithmic trading systems has been patchy.
In contrast to program trading, whereby institutions typically buy or sell bundles of shares collectively in values of $1m (€780,000) or more, algorithms deal with trades on individual stocks and help to break up large blocks. Reducing explicit trading costs (commissions, stamp duty), algorithmic trading systems can cap implicit costs, too, such as market impact and opportunity cost. In the US, it can cost less than one cent per share to trade electronically compared with perhaps six times as much for full-service trades that include research.
Europe plays catch-up
With the take-up of algorithmic trading systems believed to be about 30 per cent among European buy-side firms, the gap with North America is expected to narrow. A 2004 survey by Jean-René Giraud, chief executive officer at Edhec-Risk Advisory, based on 68 institutions managing more than €4000bn, revealed that 58 per cent of European buy-side firms process up to half of their trading volumes using algo trading programs.
The use of these systems is now graduating from hedge funds and Wall Street’s trading desks to mutual funds and pension fund managers. Projections on the industry’s growth make for interesting reading.
TowerGroup, a financial consultancy based in Massachusetts, forecast in its report Algorithmic Trading: Unlocking the Secrets of Black Box Trading that total US buy-side trading would triple between 2003-2006 and trading volumes would double over the same period. Aite Group, a research house, predicts that more than 40 per cent of total US equities trading on all markets by 2008 will be executed using algorithms – up from 25 per cent today.
Growing interest and adoption across the investment spectrum, however, clouds the fact that this relatively new solution offering buy-side traders quicker, cheaper and better executed trades has been greeted with caution in some quarters.
The fact that hedge funds and quant houses took the plunge first reflects their more open-minded approach. Given that many started life with a small complement of staff but needed to build up large trading volumes explains much of the attraction. For this community adopting algorithmic trading was a card that could increase electronic transaction volumes without needing to add traders.
There was also a kind of evolutionary logic for some hedge funds because algorithmic trading systems were the next point in their thinking. “If you look at the hedge fund community, many of them have built their own order management systems, their own trading techniques and own alpha models. As a result they have a very quantitative approach,” says Alasdair Haynes, chief executive officer of ITG Europe, an agency broker and member of the London Stock Exchange.
“Typically, when we talk to them, they want to know how the algorithm is built, see the white papers and talk to the scientists. Once a level of confidence is established, they are more inclined to adopt the technology. This is more difficult where the audience is from a more traditional background, but does not necessarily mean they will not take [algo trading tools] on board – it just takes longer to believe in the power of the technology,” says Mr Haynes.
ITG Europe offers a range of trading services covering all aspects of the execution cycle from pre-trade to post-trade analysis.
Inertia on the buy-side appears to have centred on having trust in the technology as much as on the technology providers themselves. Baring Asset Management, the London-based investment management firm, recently decided to run a feasibility study on algorithmic trading to assess the benefits.
Today, virtually every broker with an algorithmic trading engine has distribution deals with vendors that sell desktop systems to the buy-side. Access to algorithms can be made available through order management systems (OMS), trading and market data systems.
Algorithmic advantages
The move by Banc of America Securities to cut the number of traders by over a half in the past two years while boosting overall equity trading volume by 150 per cent in the same period shows the advantages of treading an algorithmic path.
The lack of clear understanding of the return-on-investment in deploying this technology is cited as one impediment to wider adoption, along with users’ difficulties in finding the right algorithm provider. The potential for data mining and so-called reverse engineering of algorithms to decipher particular trading strategies is also a concern.
Following the International Petroleum Exchange’s move to a fully electronic system from a bastion of open outcry that lasted several decades, the debate over technology versus traders in the exchange space has been raging. Whether algorithmic trading systems could lead to any outright putsch on the human trading front might seem far fetched, but it has caused some reflection.
Colleen Devine, senior consultant at consulting firm Citisoft, says: “It has been suggested that as trading technologies continue to evolve, the role of the trader will disappear. However, at this point in time, their role at an investment management firm is more important than ever.
“As the amount of trading technology increases, traders must be able to utilise that technology in the optimal way by understanding what is happening in the markets and knowing the strengths/weaknesses of the tools at their disposal. Just as the algorithmic trading models need to adjust with the markets, the strategy of how to utilise trading technology needs to evolve as well, and currently there are no algorithms available for this. This is where the human element becomes the key to a successful trading desk, regardless of its technological development,” she says.
Regulation issues
On the regulatory front in the US, the NASD, a private-sector provider of financial regulatory services, has started to collect documents and carry out interviews with traders from several of the leading broking firms to gain a better understanding of algorithmic trading programs generally and their potential for abuse (for instance, a leakage of information to the disadvantage of certain parties). The process is at an extremely early stage, but driving the initiative is a desire to assess growth of non-intervention trading following some low rumblings.
That said, the buy-side will have to get accustomed to living with algorithms because more are on their way. However, easing the strain and costs associated with trading small packets of shares (nuisance trades) while freeing up money managers to make their next intellectual decision about what they should do with portfolios should be viewed as no bad thing.
