Goldman Sachs has launched a Basket Algo, which gives clients the ability to take numerous FX trades and then trade them as a basket.
“The launch of this algo came from really recognising the pinch points of clients’ workflows and understanding what they’re trying to achieve,” David Wilkins, global head of e-FX sales at Goldman Sachs, tells Profit & Loss. “And I want to make it very clear: this is not any kind of simple trade batch uploader. Indeed, we think this is an entirely new way to trade FX.”
The essential thesis behind the algo is that deeper examination of client workflows and trading activity shows that although these firms tend to execute trades on an individual basis, in many cases, they don’t need to be, and it would in fact be cheaper and more efficient for them to instead execute them as a basket. Although the algo was initially designed with asset managers in mind, Wilkins says that staff at Goldman Sachs quickly realised that it could prove beneficial to a much wider range of clients, including corporates, hedge funds and even banks.
“Any firm that has a large number of FX trades coming into them tends to split them down into their component pieces, but actually in the beginning it was probably something that was, or resembled, a basket,” he says.
Wilkins adds that the benefits of using the new Basket Algo are threefold, as it offers clients increased automation, cost savings and greater control around their FX execution.
As he explains: “With this algo we’re helping our clients automate this processes, because they potentially don’t have to split up all those trades into their subcomponents in order to trade them at different times, with all the workflow constraints that entails. They can instead do them as a basket.
“The cost savings can be achieved because the algo offers genuine netting opportunities. We’re offering the ability to run dynamic hybrid algos on each leg of these trades and hence you get the benefits of internalisation and netting that come with these smart algos that you wouldn’t otherwise get if you were trading all of those legs individually.
“And then it offers more control because clients have the ability to set limits that are applied to the whole basket and you can set controls such as “no worse than” that are applied to the whole basket rather than having to toggle between the various different legs of the basket. We also give clients the ability to view the whole basket through our real-time order monitor, so they have a real understanding during the execution of the basket and what all the legs are doing.”
Also speaking to Profit & Loss, Ralf Donner, head of client FX algo execution at Goldman Sachs, says that it took the firm nearly a year to go from inception to launch of the Basket Algo and that “there’s no doubt that this has been our most complex algo product in FX to-date”.
But while he maintains that the algo is very complicated on the back-end, Donner says that there was a strong emphasis on ensuring that it remained as simple as possible for clients to use on the front-end.
“There was a stage in algo development where it became quite popular to expose almost every feature of the algo’s functionality to clients to be able to modify. I think that complexity for complexity’s sake is no longer the way that people build an algo product, it’s only justified if it solves a problem,” he comments.
Thus, while Donner says that the complexity of the Basket Algo on the back-end is entirely justified for the problems that it solves, his team is still counting the number of clicks that it takes to launch a ticket using it and trying to reduce this number in order to make it as straightforward as possible for clients. Indeed, functionality and the ability to integrate algos such as this into client workflows is vitally important to their adoption, contend both Donner and Wilkins.
Interestingly, one by-product of executing FX transactions as a basket is that it could mean that traditional metrics for transaction cost analysis (TCA) are no longer as relevant.
“If you imagine looking at a single execution and then looking at your performance versus arrival price or an estimated risk transfer on that execution, it’s actually of limited value if you’re looking at the portfolio level. So new metrics are actually needed to be able to analyse the performance of these baskets,” says Donner.
He adds that Goldman Sachs is therefore developing new metrics for TCA of this algo, with the most obvious real-time indicator being what the slippage is that a client has on the basket as a whole and what their progress through the basket is like, looking at live liquidity on the various legs. Donner says the bank is also talking to third-party TCA providers to help develop new metrics on the post-trade side.
“Where I hope this ends up is in a situation where it becomes apparent what the cost is to clients of not using a Basket Algo. That should be the other thing that naturally emerges from these new metrics,” he concludes.