Awards: Tradepoint

Algorithms have come of age in the foreign exchange space. They have penetrated ever larger swaths of the market and competition has broadened beyond the larger banks, as a wider range of providers extend their offerings with a suite of algos to stay in the game.

“We are seeing a downward shift, whereby larger Tier 2 banks are beginning to offer algorithmic services to their liquidity clients, creating more competition in this market space,” says Eric Adelman, president and chief executive of Tradepoint Systems.

Tradepoint has been voted the winner of the Independent Algorithmic Trading Technology Provider of the Year category at the 2018 FX Week e-FX Awards.

“What previously existed as a tool for large Tier 1 [banks] is increasingly becoming a service offered by everyone who provides liquidity to their customers,” says Adelman.

As a result of this shift, Tradepoint has been building a lot more client-facing algos than ever before. Very often, many of these liquidity providers now offer a suite of strategies just as a means of holding on to their client base, he says.

Interest from the buy side is also on the rise, as hedge funds and asset managers begin to recognise the potential benefits of electronic aggregation and algo trading.

What previously existed as a tool for large Tier 1 [banks] is increasingly becoming a service offered by everyone who provides liquidity to their customers

Eric Adelman, Tradepoint Systems

“Some buy-siders are coming from a place of pure voice trading, whereby we achieve better-priced execution by introducing more liquidity and advanced algorithmic capabilities,” says Adelman.

“Others are coming from the world of bank algos, whereby we provide lower-cost execution, allowing them to transition from an expensive brokerage model of algo execution to a controlled-cost licence model,” he adds.

Balancing act

But, market participants, especially on the buy side, have to continually balance the trade-offs between best execution requirements and maintaining relationships with their liquidity providers who do not want to see their counterparty moving markets.

As a result, Adelman says several clients have begun to ask their direct liquidity providers to provide both a full-amount and a sweepable stream of liquidity, and they rely on algos to know when to send orders to aggregated markets and when to execute on a full-amount basis.

“The future is data: the intersection of client-facing algorithms with transaction cost analysis in a wide aggregate market creates the need to understand and monitor the evolving cost-value proposition of each liquidity client, liquidity provider and algorithm on a per-symbol basis,” says Adelman.

For such decisions, data is crucial, but it also has to be dynamic rather than static to allow a smart-order router to sort based on additional factors than just price, and to interpret the different outcomes between equivalent quotes.

“The final analysis should take into account a weighting of all the criteria – from price to lit quantity, to likelihood, to venue responsiveness to market data age. A healthy weighting adjusts, dynamically based on its own performance, constantly getting closer to the ideal execution,” Adelman says.

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