Algorithmic trading is doing more for Lou Morgan than offering fast and efficient trading strategies. As head trader for HG Trading, a boutique investment firm in Heartland, Wisconsin, he can measure the performance of his staff and their initiatives in real time. If a trading strategy is failing, he and his team can bail out and start anew at a moment's notice.
There is no need for phone calls or faxes to his sell-side counterpart at Essex Radez, based in Chicago, which provides HG Trading with market data and an array of trading tools from Apama. "We do a lot of statistical arbitrage and you don't want human intervention because it's usually wrong. The algorithms are an enforced discipline. When it works, it's great. When it doesn't, you can slow it down or turn it off," says Morgan.
HG Trading runs multiple algorithms at once with four different strategies at work. "But we may have 20 to 30 instances of each strategy on at any one given time," he says. Morgan also uses algorithms for transactional cost analysis (TCA). "There are real-time results. If it's getting into trouble, it will bail out automatically," he says.
Morgan estimates that an algorithm can bail out of a trade multiple times per day. "We run hundreds of instances per day and we might bail out on 10 of them. Twenty would be a lot, for example," he says.
Welcome to the newest phase of the ever-evolving space known as algorithmic trading. At first, these advanced trading formulas were used to trade faster than humans could. Recently, however, trading algorithms have been touted as a way for buy-side firms to measure the performance of their sell-side counterparts via TCA. This also raises a sticky issue, because the sell side often offers trading algorithms for free to the buy side in exchange for using its trading venues. But now, investment firms like HG Trading and vendors of algorithmic tools are seeing a new use for these advanced formulas: the ability for the buy side to look into the mirror and gauge its own performance and strategies.
Paul Scott of Fix City, a software provider and consultancy, has noticed an increase in these new demands from the buy side. "We're hearing a lot from buy-side clients in terms of TCA. It's becoming a way to monitor their brokers' execution as well as their own. They are trying to judge if they are getting the best execution from splitting the trade and using direct market access for some portion of a trade and algorithmically trading other parts into the crossing networks with the darker pools of liquidity," says Scott.
In short, Scott says, buy-side firms are using TCA to eliminate that information leakage and get the best price.
Jeff Wecker, CEO of Townsend Analytics, says he agrees. "It's not just measuring the sell side; it's a way for the buy side to measure the quality of its own trading. It's also a way of measuring the execution quality for different liquidity destinations such as exchanges, ECNs or dark-pool ATSes."
While this new power of TCA has some sell-side firms reportedly rattled, no one interviewed for this article has heard of a buy-side firm canceling its contracts with its sell-side counterparts over poor trades. "It can become part of the broker's reviews. It is a way to monitor the execution and the level of execution and it has become a factor in that review process," says Wecker. "But I haven't heard that anyone has dropped a broker because of it."
With increased TCA comes greater transparency. "With the execution for a particular order the trader is working on, there are a number of other factors that come into play with regards to the broker and how well they've done. We have seen more commission-sharing agreements where the value of the execution is now clearer. Previously, you had to put research together with the cost of trading. Now, that is being separated from the actual dealing cost. It's a lot easier for the buy-side trader to determine how much that execution is costing them," says Wecker.
As algorithms become smarter, they can adapt to more volatile and faster-paced trading environments. Apama is developing what it calls a "genetic" approach to algorithmic trading, where the program will evaluate nearly 1,000 permutations of a strategy, feed it market data, calculate profit and loss, and kill off the least profitable formula scenarios.
"You kill the ones that are least profitable but grow the ones that are more so. That is the ultimate TCA: self-evolving and based on profitability," says John Bates, CTO and co-founder of Apama, an algorithmic trading platform provider. He says that this genetic trading is under development and while some buy-side firms are using it, he declines to provide their names.
HG Trading's Morgan says he is interested in this approach, but at press time, his firm has not signed up for it.
The Search for Dark Pools
The latest wave of algorithms is being designed to not only deliver TCA but also to lead clients to so-called dark liquidity. In an interview with sibling publication Dealing with Technology, Bill Harts, managing director and head of strategy for equities at Banc of America Securities (BAS), discusses algorithms and dark liquidity. Harts joined BAS in May to replace Rob Flatley, who moved to Deutsche Bank last spring.
"Our newest algorithm is called Ambush. There is a lot of liquidity out there that's not visible in the market, either because it's in a reserve order or a hidden order. The Ambush algorithm is designed to sniff out the sort of liquidity that's not ordinarily visible," says Harts. Harts says he would like to see BAS release as many as six algorithms each year, adding that market demand remains a key factor. "We don't just develop algorithms because we dream something up and say, 'If we build it, they will come.' We do it in response to specific client concerns or interest," he says.
While hedge funds have been early adopters of algorithmic trading, other sectors have been embracing the formulas in growing numbers. "The high-frequency trading hedge funds have long embraced algorithmic trading. In some ways, they were pioneers, but now we're seeing more traditional mutual funds and portfolio managers also start to embrace algo trading," says Harts.
Surprisingly, the recent wave of stock exchange mergers has not triggered a consolidation of liquidity. Just the opposite, says Harts. "Many people thought that if exchanges consolidated, then liquidity would also consolidate. But instead, the liquidity is actually fragmenting. We're seeing a proliferation of what are becoming known as dark pools of liquidity," he says.
"Even though there are fewer market centers, there are more dark pools, so investors are going to need algorithms that access those dark liquidity pools in a way that hasn't been done yet," says Harts.
The week on Risk.net, December 2–8, 2016Receive this by email