ALGORITHMIC TRADING’S IMPACT on the cash equities market has been huge, especially considering the relatively small proportion of the total trading volume for which it accounts. Although there is much confusion about the technique, most market participants seem to agree that it will be used increasingly frequently. Financial services consultancy Celent estimates that by 2008 up to 25% of all trades by volume will be executed using an algorithm, up from about 18% today.
Since algorithmic trading began to take off as an execution tool in 2000, the average trade size on the London Stock Exchange has fallen from £60,000 to just over £20,000 ($34,000). The fall in the average trade size is widely attributed to the use of algorithms because one of the most basic things they all do, regardless of the particular trading strategy, is to divide an order into many smaller ones, as a small trade is less likely to have an impact on the market price than a large one. Although to an extent this is also what any human trader concerned with market impact does, computer algorithms divide orders into many smaller trades than any human trader would ever find it efficient to do.
Although it is clear that algorithms have made it possible for the average trade size to get smaller and smaller, this has to be seen in the wider context of the post-2000 bear market and regulatory-driven obsession with execution quality.
Obsession with quality
The need to eke out every drop of alpha in order to flatter returns and the drive towards unbundling have forced fund managers to care about execution quality and brokers to prove their worth. The obsession with execution quality has lent impetus to the use of algorithms, because by definition they are the outcome of a systematic and carefully considered approach to trading.
In the US, regulatory intervention, in the form of decimalization, has also had a big impact on the average trade size.
“Liquidity is still out there,” says Mike Plunket, president of electronic agency broker Instinet. “It’s just not completely visible. It used to be that what you could see was what you could get. Now what you see may not mean a darn thing. Everyone wants larger trade sizes but put an algorithm in their hands and they’ll use it to break their orders into small lots because you just can’t send out a large block any more. Algorithmic trading has become a self-fulfilling prophecy.”
Given the impact algorithmic trading has had on trade sizes to date, its projected growth leads some in the market to wonder just how much more trade sizes can fall. “The only things that stand in the way of trade sizes falling to single shares are regulation and cost optimization,” says Plunket. “If they were ever to give single shares the same status as they give round lots there’d be nothing to prevent trade sizes falling to single digits.”
Algorithmic trading’s tendency to turn single orders into many smaller ones is an important factor underlying the increasing tension between exchanges and their users. Whereas brokers and investment banks charge their clients on the basis of the total value of an order, exchanges generally charge users on a per trade basis. The cost of trading on the exchange is borne by brokers and eats into their profits. This cost also acts as a limiting factor on the temptation to design a broker’s algorithm to make trades as small as possible.
The 73% fall in the average trade size on the London Stock Exchange’s main order book since 2000 is dramatic, but it has been even more extreme on exchanges that offer greater volume discounts. Exchanges and their owners are arguably the biggest and most immediate beneficiaries of algorithmic trading.
Last month, all three main exchange groups in Europe posted bumper results, driven largely by increases in the volume of cash equities trading. Deutsche Börse reported a 20% rise in quarterly revenue to €417.8 million. Revenue from cash equities trading rose 38% to €66.2 million from €48 million a year earlier because of higher trading volume. The number of transactions on its Xetra platform rose 39% to 21.8 million. Euronext reported a 14.1% rise in third-quarter sales to €234.3 million, as cash trading revenues surged by almost 36%, while the London Stock Exchange announced a 24% increase in operating profits to £50.8 million with turnover up 15%.
The fall in trade sizes has profound implications for how people trade and for how the secondary market behaves. “Overall algorithmic trading has great and very positive implications the secondary market,” says Rainer Riess, managing director at Deutsche Börse. “Automated orders now account for more than 40% of the overall number of trades on Xetra and we've seen liquidity grow strongly because of it. The size of trades may have gone down but the overall liquidity based on what's available in the book has increased.
“Algorithms trade smaller sizes because the machines break up the orders, but they also take advantage of the many small opportunities that manual traders wouldn't because of the difficulty of doing so many trades and because the profit from individual opportunities may be small. This is why price quality improves; that is less market impact from trading and a gain in terms of overall efficiency for the market. We actively try to entice this kind of order flow by offering tiered discounts to programmes where the exchange price is part of the algorithm because we believe it is very beneficial flow for overall market quality.”