“Trading is constantly trading and evolving.”

That truth was noted in the introduction to a panel at last week’s Linedata Exchange NYC 2024. 

The theme of change and what’s new was also covered at the Security Traders Association of New York’s annual conference, which was held April 15 at New York Stock Exchange.   

What are some current front-of-mind considerations as of mid-April 2024?

Lower commissions, fragmented liquidity, and broker selection were cited as challenges by speakers at the Linedata event. 

Of course, challenges can be opportunities for providers of trading technology, who recognize the need to continuously innovate in providing reliable, scalable technology that interoperates with other platforms. 

Getting data right was cited as a critical building block for effectively deploying technology. “Automation is a hot topic, but without data you can’t automate,” one speaker said. 

Current technology systems enable buy-side traders to put their orders on multiple venues to await a match, and even have orders “scraped” off their own order management system (OMS) by venues. But the fragmentation, especially in small and mid-cap names, still vexes.

Industry initiatives aimed at solving liquidity challenges include better integration and utilization of dark and lit liquidity in combination, as well as a revival of indications of interest (IOIs), which don’t have a great reputation but can work when there’s guaranteed liquidity behind them.

Artificial intelligence, specifically generative AI, was discussed at the STANY event. 

One STANY panelist noted AI has proven itself in areas such as reinforcement learning, and improving quantitative processes and liquidity “heat maps”. What hasn’t proven itself yet is the “black box” type, unexplainable gen AI. 

“That’s where people want to see it going. I think it’s the future, but at this point we’re not there yet.” 

Another person noted gaps in the adoption of AI, due to a lack of visibility in how AI makes decisions. There is more work to be done in bridging the gap between human and machine, but “you will be left behind” if you don’t adopt AI.   

Data quality has always been important, but it’s especially important with a framework of AI systems. “Garbage in, garbage out is even more so with AI,” one person said. 

Looking ahead, STANY speakers said they don’t expect AI to force big changes on the trading desk within three years, but in five or ten year’s time, “it will be further along as we start removing guardrails and letting it do its thing.”