Using algorithmic trading can shave up to 11 basis points from your costs, a new study from ITG* has found, but warns that performance levels between brokers can be far from uniform especially as order sizes increase.
It is estimated that algorithmic trading, the automated execution of orders according to a predefined strategy to meet a specific benchmark, is used by an estimated 60% of US buy-side firms and this percentage is set to grow. The take up in Europe is currently thought to be about half of that in the US, but is again expected to rise dramatically.
FIRST LARGE SCALE STUDY
However, despite being the âhot topicâ of the moment, little research has been carried out in this field until now. To date, only one other study has evaluated algorithmic trading, based on trade data for approximately 7,000 orders from only one client. The ITG study evaluated over 2.5 million orders, consisting of about 10 billion shares (valued at over $80 billion) traded in 2004, from more than 40 institutions. The ITG study looked not only at the performance of algorithmic trading versus non-algorithmic trading but also compared the performance of different algorithmic systems offered by brokers. The performance of six brokers was analysed, but their identity has not been disclosed.
ITG is uniquely placed to carry out this research because of its expertise in analysing trading data. Its post-trade analysis system TCAÂ® is one of the industryâs most advanced tools. ITG also offers ITG SmartServersÂ®â its own suite of algorithmic trading products.
Commenting on the publication of the study, CEO of ITG Europe Alasdair Haynes, said:
"This study shows that algorithmic trading can play an important part in helping firms achieve Best Execution, but that users have to be discerning as to which product they choose and under which circumstances it is appropriate for them. This is clearly an area of trading that is set to grow and we feel that itâs vital for the industry to increase its knowledge of rules-based trading â hopefully this study will contribute to a greater understanding of the dynamics of this market."
The key findings:
- Algorithms can reduce the cost of trading
- Average performance differences across providers for very small orders are few, but gaps between providers grow as order size grows
- All algorithms are not created equal â there are indications that certain algorithms perform better than others at higher volume levels
- Certainty of outcome â as important as quality of outcome â varies widely between brokers