Blogs

The release of ChatGPT by OpenAI last year, and its viral success in responding to human prompts in natural language, has ignited interest in generative AI technology, and has pushed asset managers and trading firms to grasp the technology rather than risk falling behind. Despite concerns about accuracy, financial firms and fintech providers are experimenting with specific use cases for generative AI using natural language processing trained on large language models (LLMs).

As the buy-side trader seeks to aggregate a multitude of pre-trade liquidity sources, trading protocols, and execution venues, many are turning to the execution management system or EMS to gain a competitive edge. In this Q&A, Venky Vemparala, FlexTrade’s Global Product Manager – Fixed Income, who is speaking at FILS, shares his views on the key issues facing the buy-side around data, trading protocols, and automation.

Over the past five years, FDC3, which is hosted by FINOS on the GitHub repository, has emerged as an open-source standard for connecting disparate applications on the desktop and creating more efficient workflows for traders.

One of the major themes for 2023 is the emphasis on multi-asset trading and the focus on efficiency and scalability across regions and countries. In the past, a trader focused on a single asset class such as equities or bonds, whereas today with the migration to electronic trading, the desk can automate workflows and manage executions across all asset classes.

A key innovation is the ability to dynamically switch between algos and/or tweak algo parameters based on the current market conditions and algo performance. The concept of algo switching is not new; however, since FlexAlgoWheel focuses on order routing, we offer dynamic switching as an integral feature. Dynamic re-evaluation, an advanced feature of FlexAlgoWheel, continues to assess the real-time market conditions.

A key innovation is the ability to dynamically switch between algos and/or tweak algo parameters based on the current market conditions and algo performance. The concept of algo switching is not new; however, since FlexAlgoWheel focuses on order routing, we offer dynamic switching as an integral feature. Dynamic re-evaluation, an advanced feature of FlexAlgoWheel, continues to assess the real-time market conditions.

Panelists agreed on the need to capture and monitor tradeable streams as a precondition for calculating liquidity analytics, emphasizing this helps them understanding which LPs are performing better than others.

The discussion looked at the shifting risk trends that institutional investors are facing and how they are bringing in new alternative data feeds alongside traditional risk models to make more informed decisions.

From selecting FX algorithms, to evaluating liquidity providers, to identifying hidden costs, there is an emphasis on what the data is telling people, said multiple speakers at the virtual event.  In addition, recent changes to the FX Global Code of Conduct, could provide additional market transparency for the buy side related to algorithmic trading and TCA.

Data is shaping the fixed-income trading desk of the future. Keeping up with the exponential rise in data from inbound liquidity, new issues, and pricing services has become a challenge for asset managers in an OTC market landscape that is shifting and becoming more automated. Demand for data is exploding with the evolution of the …