Buy-side use of algorithms is shifting quickly as brokers aggressively deliver an expanding range of customisation services and modularised solutions that allow the buy side to control and
Buy-side use of algorithms is shifting quickly as brokers aggressively deliver an expanding range of customisation services and modularised solutions that allow the buy side to control and manage different electronic trading components, according to a report by the capital markets research and strategic advisory firm Tabb Group.
Before the end of 2008, at least 30 per cent of all algorithm flow will be sent through customised strategies, up from 18 per cent today, as brokers continue to offer customisation to a broader set of clients, according to Tabb Group senior research analyst Adam Sussman.
Sussman is author of a new research note, The Modular Algorithm: The Growing Choice in Buy-side Execution Strategies, which forecasts that the buy-side’s use of canned algorithms, which amounted to 58 per cent of the total in 2005, will account for less than half of all algorithm flow by the end of next year.
‘The current usage of various algorithms and direct market access tools is not the ideal state for the buy side, but rather the optimal selection based on its current options,’ Sussman says in the report.
He argues that for algorithm providers, customisation further feeds the product pipeline for canned algorithms, re-engages buy-side clients on a personal level – something that had been lost as FIX replaced the telephone and entertainment rules became more stringent – and differentiates brands on a crowded shelf of products.
‘In the end, this is a buy-side issue because what traders really want is a tool that allows them to control an order using a wide range of variables, a tool that permits them to map the portfolio manager’s objectives into an executive strategy,’ Sussman says.
‘This means an algorithm with a true sense of purpose. Instead of merely wanting all the data they look at incorporated into an algorithm, they want the algorithm to look and react to the data in a specific way.’
Another result of the growing choices among buy-side execution strategies is a steep decline in resources that hedge funds are willing to spend building execution-only algorithms. ‘The bare minimum today to build an algorithmic infrastructure is USD1.3 million, with recurring annual costs of USD900,000 and personnel costs account for nearly half of that cost,’ Sussman says.
In 2005, he argues, there was little choice for a hedge fund to build its own algorithms. But with customisation services and modular technologies, Tabb Group believes that proprietary algorithmic usage will decline from 88 per cent of all hedge fund algorithmic flow to 67 per cent by the end of next year.
Sussman notes that several quantitative hedge funds chose to split scheduling and routing responsibilities, with the scheduling component kept in-house because deciding when to route is dependent upon proprietary data such as the expected alpha among a list of stocks. However, these funds are outsourcing routing decisions to their brokers.
‘The latest generation of algorithms automates this functionality through the use of a ‘would’ option that trades according to a participation strategy but would simultaneously hunt for additional liquidity among dark pools,’ he says.
The 20-page research paper covers recent progress in the equity algorithmic space, trends in algorithmic functional areas, hedge funds’ algorithmic flow distribution, the role of customisation within this process such as algorithm development kits, the beta release of FIXatdl (FIX algorithmic trading definition language) and complex event processors and future product enhancements based on the custom work being done today.
The information for the report was collected from conversations conducted with buy-side traders and electronic trading executives at sell-side firms in July and supported by analysis of primary data drawn from existing Tabb Group research. The firm was founded in 2003 and uses the interview-based research methodology developed by founder Larry Tabb.
