CFM’s Philip Seager on AI, Data and Systematic Trading Edge
In an interview with Traders Magazine Philip Seager, Head of Portfolio Management at CFM, explores how machine learning systems are transforming research workflows, how expanding data and execution infrastructure are driving systematic performance, and how electronic markets continue to evolve across fragmented liquidity pools.
Please tell us about CFM’s trading desk. What are your trading volumes today, and what types of instruments does your trading desk primarily focus on?
Our core business focuses on electronic order book markets. Our “trading desk” is small in comparison to others due to the fact we trade very few markets manually. We rely predominantly on our in-house developed algorithms for the vast majority of our trading. Where we cannot trade through an electronic order book we do have people trading through electronic click-and-trade/RFQ/RFS type venues. This opens up other areas of liquidity and diversification for us.
What market conditions in the US are creating the biggest opportunities for systematic trading strategies in 2026?
Favorable conditions in markets for our types of strategies are those where volatility is driven by market participants. Volatility from geopolitical events leads to uncertainty and further volatility as market players try to navigate these events. Generally our strategies are built to take advantage of behavioral biases in the post event period. The biggest opportunities for systematic trading in 2026 are not so much due to market conditions but come rather in the form of data and technology. We are professional accumulators of data, the more we have, the better informed we and our trading decisions are. Signal research and technology (a growing component of which is AI based) then allows us to extract more and more value from these often unstructured data sets.
How is AI changing the way trading signals are identified and executed?
We have built an agentic system to perform certain research tasks. This system is capable, for example, of taking as input an academic or broker paper written on a particular strategy and performing tests, coding the strategy and outputting statistics that allow us to see if the strategy is additive to our portfolio. A human validation procedure is still in place, however, to decide if an idea makes its way through to implementation. This infrastructure also allows us to do certain research tasks at scale and has led to researchers having less of a need for coding. Ultimately this technology is a powerful tool for improving research productivity. Projecting ahead one can see a future where researchers have more time for ideation, spending less time on the implementation of those ideas.
How are quant managers adapting to increasingly fragmented and electronic markets?
We were early adopters of electronic markets and have traded them algorithmically for decades. It plays to our strengths if all markets become electronic and preferably are traded through order books. In the equity space, fragmentation has become a dominant theme. Liquidity has slowly moved away from lit markets and onto darker venues (albeit there is still a lot of liquidity on the lit markets). This has led to us adapting our trading style on a case by case basis, changing our algorithms accordingly, accessing all different types of liquidity in an attempt to obtain the best execution prices.
What role does data quality and research play in maintaining an edge in systematic trading?
We have been extracting and cleaning data for use in our strategies and execution for many years now. The quality of the data for financial instruments is simply a question of identifying bad prices. This is very different to the task of identifying biases in datasets that can lead to spurious results. These biases are mainly those arising from Point-in-Time effects where a provider, for whatever reason, prints a datapoint with a timestamp which is not the time at which the information is known but rather is backdated. This leads to a backtest that can be too good to be true due to accessing information which is not actually available until later. These effects are subtle but can make a big difference to research results. We have many ways of trying to identify such effects to limit the bias in our results, allowing us to more robustly quantify the real value of a data set.
How are systematic traders navigating recent periods of volatility and shifting liquidity conditions?
The volatility arising from the Iran war has been somewhat different to that of the so called Liberation day volatility of a year earlier. On the whole the Liberation day gyrations were bad for systematic futures players but better for systematic equity players. It seems in 2026 that the opposite has been the case. This certainly shows the benefits of a diversified play. As a firm we tend to focus research and trading on the most liquid contracts. The danger in having sizeable positions in illiquid contracts is that transaction costs also become sizeable. In times of crisis it is the most liquid instruments that actually become more liquid, meaning there is a flight-to-liquidity effect, while the less liquid markets tend to dry up. As a result we are somewhat less effected by liquidity than most.
As more firms adopt quantitative trading strategies, where do you still see untapped opportunities in the market?
The opportunity for us in our ability to craft strategies from a deep understanding of markets, data and signal processing. We have a large research team building strategies and portfolios collaboratively. When we make a breakthrough in an area of research it is efficiently propagated throughout our portfolios. When we buy a new dataset it is used across teams. The more data we have, the more we are able to understand any one given dataset. This scaling up of the research process is our main strength and the biggest opportunity in the market.
CFM has been expanding its U.S. presence, particularly in New York. What opportunities do you see in the U.S. market, both from a trading and talent perspective?
US markets offer the greatest depth in terms of liquidity and diversity so it makes sense for us to have a presence there. New York is of course also one of the world’s major financial hubs with an unrivaled depth of talent. Being a European manager it makes sense for us to diversify talent pools on the research and data side of the business.
Disclaimer: All opinions and estimates included in this document constitute judgments of CFM as at the date of this document and are subject to change without notice. Future evidence and actual results could differ materially from those set forth, contemplated by or underlying these statements. CFM does not give any representation or warranty as to the reliability or accuracy of the information contained in this document. CFM accepts no liability for any inaccurate, incomplete or omitted information of any kind or any losses caused by using this information.
