QFinity Labs Are Using Artificial Intelligence To Improve Algorithmic Performance at FVP Trade
February 2, 2021
Artificial intelligence (AI) has measurably improved the performance of execution algorithms in CFD trading and could do the same in many other asset classes according to Qfinity, the
independent algorithmic trading technology provider.
David Moche, the founder and chief executive of QFinity Labs, said that the firm decided to apply modern AI tools to its algorithms in the spring of 2018. He explained that the firm began to test the neural network in late 2019 with orders being sent to the AI algorithms on a randomized basis.
Following a number of controlled trials with clients, the AI algorithms were found to improve performance by between 33% and 50%, including the volatile conditions of last year. The AI algorithms react to signals to improve micro-trading decisions, such as whether to be aggressive or passive, routing, sizing, pricing and timing of orders.
“AI provided a material benefit which exceeded our expectations,” Moche added. “The principles are applicable to any market-driven asset class and we are beginning to see positive results in foreign exchange.”
The algorithms cover a universe of 3,000 assets, some of which are illiquid. Mooche said: “We have seen a 50% increase inflows to the AI algorithms.”
Moche continued that Qfinity Labs has a pipeline of enhancements to further improve performance.
Last year a long-awaited rule from the US Securities and Exchange Commission came into effect with the aim of helping the buy-side achieve better execution by getting more data and
information about their trades. Rule 606(b)(3) requires a broker-dealer to disclose routing and execution data for not held orders over the previous six months if a customer asks for the
information. The rule is likely to lead to the buy-side using more analytics to improve execution as electronic trading becomes more sophisticated and the choice in how orders are executed continues to increase.
“Rule 606 shows there is a growing focus on broker obligations and that trend will continue,” added Moche.
He explained that, as a result, the bar is getting higher to compete in the top tier of algorithms trading.
“Getting a material, measurable benefit in average shortfall requires a lot of ingenuity,” said Moche. “It took us a year and a half of intense research and development before we had our
first version in production.”
Algorithms also have to adapt to changes in the market structure. Last year three new exchanges launched in the US and firms have filed for regulatory approval of new order types.
Moche finished by saying “The use of AI allows us to adapt more quickly to market structure changes.”