FastMatch Expands FX Algos01.10.2017
Foreign exchange technology firm FastMatch has opened its trading platform and algorithms to the sell side and smaller banks.
The firm, founded in 2012 by Credit Suisse alum and electronic trading wunderkind Dmitri Galinov, made the decision to broaden the availability of his proprietary electronic trading solutions after noting the growth of the FX markets, as well as increased institutional client demand for efficient and transparent trading. As Galinov told Traders Magazine in an interview, FastMatch’s three algos were originally only offered in 2012 via Credit Suisse’s AES platform and to the largest banks and other asset managers. But as the FX market grew to be $5.3 trillion per day trading behemoth, according to the Bank for International Settlements, the need for his algos would only grow.
“And it has,” said Galinov. “My objective in creating FastMatch and entering the FX institutional was to provide a new fast, cheap and transparent ECN in the FX space. We just felt that at that time (2012) the existing trading platforms and technology were not adequate.”
As Galinov described, back in 2012 FX vendors and others were not providing the buy-side with information such as order type descriptions, full trade information, the latest in trade technology and were costly. Given his background at Credit Suisse in electronic trading and what customers wanted, he left the bulge firm and in just three months created FastMatch and its ECN network.
The ECN network grew to include AgencyFX, its buy-side focused product, providing a safe, reliable way to trade with institutional and retail FX clients. Its liquidity was greatly increased with the creation of three in-house developed algorithms – Passive, Neutral and Aggressive.
As their names imply, each of the three algorithms works at a given speed (Passive – very very slow, Neutral – modest, Aggressive – fast) to match trades. The algos trade speed for information leakage, so as a trader needs to execute faster he might expose more of his strategy or intentions. These were offered to the largest buy-side clients who interacted with Credit Suisse but as time went on, Galinov said that making his algos, trading engines and ECN open to smaller underserved firms via other sell-side brokers would be advantageous. So, in 2015, he opened the platform up to all via FIX, API or GUI.
“We noticed that in the FX market that outside of us via Credit Suisse, no one was offering algos to the smaller banks or sell side and we could fill it – very quickly,” Galinov said.
How quickly? Once a trader connects to FastMatch, its algorithms can be adapted to meet his specific needs (if the baseline algo isn’t sufficient) in just 25 microseconds. The trader simply interfaces with the algo platform via his GUI and enters a few keystrokes. That’s it.
Once a trade is executed electronically, traders can then track the algo’s performance via FastMatch’s own trade cost analysis system.
“As for the future, I think we have a ways to go, so moving into other asset classes is not yet in our future,” Galinov said. “ However, our technology can be altered in three months or so to offer algos in stocks or options. But for right now, we see a huge growth opportunity in FX and will stay here.”
Due diligence process has not kept pace with the proliferation of algorithmic trading.
By Greta Zhou and Andy Cheung, APAC AES, Credit Suisse
Broker's new platform generates execution strategies that leverage client-specific trading data.
Trading platform addresses the market's need for performance, transparency and control.
Forensic analysis makes ’black box’ algorithms more transparent.