KCG is looking to Catch liquidity any way it can, just ask Charles Susi.
As part of KCG’s continued push into the institutional trading side of the business, the well-regarded and historically focused market -maker has built its first brand new algorithmic trading tool – Catch. The algo, Susi, KCG’s head of product development for the firm’s client execution services group, in an interview with Traders explained is the vanguard of new products designed to unite the buyside with the firm’s deep retail liquidity, dark pool and market making abilities.
“We’re making the push into institutional market and Catch is part of our strategy,” Susi told Traders. KCG wants to grow its agency execution business, but he added, not at the expense of its market making or other operations. KCG’s electronic execution business averages354.9 million shares traded per day in U.S. equities.
Thus, the firm has developed Catch – an algorithm designed to find what Susi and KCG term “higher quality” liquidity. Higher quality liquidity, he noted, could be defined as order flow that reflects little to no market impact after and execution – no market movement, reversion or footprint. Thus, Catch is meant for buysiders who are quietly searching for that elusive block trade and/or natural fill – not the small predatory orders or high-frequency traders who look to sniff out institutions larger orders and get out in front of them.
“Higher quality could mean a natural block or retail flow,” Susi said. It could also mean another child order of a natural order, he added.
Users could simply define higher quality as simply getting a trade done with minimal impact.
Catch took a few months to build, Susi said, and is in full operation now after spending the last several weeks in the hands of select KCG clients in beta testing. And it is the buyside customer that KCG is looking for, as Susi told Traders KCG’s buyside-focused business is up 45 percent in October and the firm has added 100 new clients this year, 75 of which are buyside.
So, how does the algorithm work?
In simple terms, Catch casts a wider net for an order, leveraging a broader set of tools when chasing liquidity. Utilizing thoughtful, passive order placement logic and an advanced fair value model, Catch is empowered by KCG’s Big Data analytics and low-latency routing technology.
Catch is guided, but not governed, by a market-aware participation strategy that uses adaptive participation guidelines. This strategy influences the urgency of trading, but will not force trading at inopportune times, as can be the case with algorithms coded with hard bands.
Susi explained that the algo is designed to act aggressive early on. That is, volume participation will be greater at the beginning of the order, getting a user closer to the fill sooner. As the algo runs, it continuously recalibrates. Catch manages opportunistic passive and aggressive trading by considering urgency, inventory, and market conditions in real-time. Therefore, its participation is continually recalibrated as an order progresses to ensure proper exposure and optimal execution performance.
He added that Catch is rooted in the firm’s market making technology, market latency experience and now big data technology. The result is an algorithm which helps the buyside find alpha at all levels – especially incremental or “micro” alpha at the child order level.
While it incorporates some elements found in the firm’s Opportunistic strategy, Catch is all new. It is billed as a liquidity seeking algorithm that uses KCG proprietary analytics, venue analysis and order placement modeling technology in every execution. As Susi put it, “We’re going to try to capture spread and incremental alpha in every child order.”
Catch uses a fair value model, among other analyses, to determine where it sends an order and how it dices up a parent order. Whether Catch is set for a target of participation, crossing the spread, or sourcing liquidity in a dark pool, it places the order(s) at price KCG’s model thinks a stock is going to, Susi explained.
“Catch will manage queue priority on venues – sometimes it will try to be first or at other times it can choose a different placement to balance urgency and market impact,” Susi said.
To that end, Catch’s logic is very data driven in that it measures venue characteristics – toxicity, order fill rates, etc, gets an understanding of the venue, and then decides whether or not to send an order. As Susi explained, “it just goes by the numbers.” But it can also be customized by a user, who can tweak the settings to his likings.
The buyside users can change several other characteristics of Catch. Users can select the aggressiveness with which the algo hunts down liquidity and specify defaults to specify percentage-of-volume brackets, depending on user settings. Susi explained that users can set urgency levels on just how fast they want to get their fill. The highest urgency setting, “aggressive,” means the order will be more “front-loaded” and that participation will be higher. The lowest urgency level, “passive,” means the participation range overall will be lower and the order will not be as urgent at the outset.
Participation is continually recalibrated to ensure proper exposure and optimal performance. Catch won’t seek an average market participation rate – it flexes widely in ranges based on urgency.
“We want to intelligently become part of the market,” he said.
Also, users can select the type of liquidity they wish to interact with – principal or agency flow. Options for crossing with KCG’s dark pool, retail order flow or external venues are available.
We want to help the buyside source the right liquidity – whether via blocks, interaction with retail or intelligent participation in public markets, Susi said. Catch wont go just along for a ride in a block trade if our fair value models tell us its not a good price.
Catch is just part of KCG’s new electronic algorithmic offering as the firm continues to migrate legacy Knight and Getco tools to the KCG stable. Susi told Traders that older algos, such as the existing VWAP or Opportunistic products are being modified and tweaked with the goal of helping the buyside source liquidity more intelligently and with less market impact.
