The development of algorithms over the near term will follow three distinct paths, according to Rob Maher, head of Advanced Execution Services (AES) sales in Europe at Credit Suisse.
The first is the creation of algorithms with multi-asset-class trading capabilities that support the more complex trading strategies often deployed by buy-side firms as they diversify their portfolios. “We are building some interesting tools that combine algorithms across asset classes, allowing you to trade, for example, equities and foreign exchange in combination, options and equities, or equities and futures with all different types of parameters and goals,” says Maher.
“Of course, this doesn’t mean that the algorithms behave 100% identically across these asset classes; only that the goals and risk tolerance settings remain the same,” he explains. “Nor only are the algorithms tailored by asset class but also down to instrument level to ensure best execution.” Maher cites the example of Credit Suisse’s BorderCross product. “BorderCross allows clients to dynamically access best prices on an FX-adjusted basis in both Canadian and US equity markets,” he says. “We trade in both markets, pass back FX-adjusted prices and hedge out the FX exposure to allow settlement in a single currency.”
A second area of algorithmic development is the incorporation of anti-gaming protections into dark-liquidity-seeking algorithms. “With the proliferation of dark pools seen in the US now coming to Europe, there is a tremendous amount of concern about protecting orders and avoiding negative selection,” he says.
Although dark pools often have their own anti-gaming protections built in, Maher feels this is not always enough. “We have learned from experience that dark pools are not able to police themselves in many instances,” he says. “It’s ultimately up to us as the execution service providers to protect our clients’ orders. In Europe, with only a handful of legitimate dark pools, anti-gaming is less of an issue at the moment, but as the market fragments further and liquidity moves around, it is going to be more important.”
Finally, Maher asserts that customisation, while nothing new, will be increasingly important as client requirements become more complex and sophisticated. “It is moving away from simply putting the building blocks together with an algorithm provider, where you bundle different strategies to solve a client’s individual goal, towards more sophisticated approaches, such as taking direct input from clients, taking alpha factors and other things, to build something that is much more integrated into their investment process,” he explains.
The ‘next generation’ has much to offer, says Maher, but, without an effective smart order router, algorithms cannot fulfil their potential. “The number one thing that clients should be demanding is that execution does not just come down to the algorithm but also smart order routing, granting access to all pools of liquidity in an intelligent fashion,” he says. “As liquidity fragments, if your algorithms aren’t getting access to the right liquidity pools you’re not doing your job.”