About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Intelligent Trading Summit Considers Potential of Predictive Analytics and Machine Learning

Subscribe to our newsletter

Predictive analytics, machine learning and sentiment analysis are making their way into the trading environment, but how useful are they and will they provide a new model for intelligent trading? These questions and more will be discussed at next week’s A-Team Group Intelligent Trading Summit in New York.

Adrian Sharp, senior industry consultant, capital markets, Teradata, will moderate a panel session that will consider the potential of these emerging capabilities during the summit. He will be joined on the panel by Li Yang, vice president, lead of development, Citi; Philippe Burke, managing partner, Apache Capital; Antonio Hallak, CEO, Sibyl Trading; Steven Cohen, CEO, Gold Coast Advisors; and Yadu Kalia, worldwide business architect, financial services, IBM.

Moving on from high frequency algo trading, which is driven by speed but ultimately limited by system power, the panel will consider how the trading model may change over time to become less about speed and more about predictive analytics that could, perhaps, identify what might happen in the next 10 milliseconds.

Machine learning and sentiment analysis, which introduces unstructured data, also reduce speed. If these technologies are deployed in trading, a use case that includes a different view of time to that used in high frequency trading is required.

Sharp suggests there is a place in trading for machine learning, sentiment analysis and predictive analytics, but says it is difficult to find use cases for the technologies at the moment. He explains: “If machine learning, sentiment analysis and predictive analytics are applied to trading, the trading process changes and the model is different to that used for high frequency trading. The question is whether we are going to continue to exploit inefficiencies in the market or take a broader view over a longer time by bringing in more analytics.”

To find out more about:

  • Alternative trading models
  • The power of predictive analytics
  • Use cases for machine learning
  • Future trading developments

Register to attend the A-Team Intelligent Trading Summit.

Subscribe to our newsletter

Related content

WEBINAR

Upcoming Webinar: From Data to Alpha: AI Strategies for Taming Unstructured Data

Date: 16 April 2026 Time: 9:00am ET / 2:00pm London / 3:00pm CET Duration: 50 minutes Unstructured data and text now accounts for the majority of information flowing through financial markets organisations, spanning research content, corporate disclosures, communications, alternative data, and internal documents. While AI has created new opportunities to extract signals, many firms are...

BLOG

Interop.io Targets Secure AI Adoption in Finance with io.Intelligence Launch

Desktop interoperability specialist interop.io has today unveiled io.Intelligence, a new initiative designed to enable financial institutions to securely deploy and scale AI copilots within their existing technology infrastructure. The launch aims to bridge the gap between the powerful potential of AI and the practical realities of complex, highly regulated enterprise environments. The new offering provides...

EVENT

RegTech Summit New York

Now in its 9th year, the RegTech Summit in New York will bring together the RegTech ecosystem to explore how the North American capital markets financial industry can leverage technology to drive innovation, cut costs and support regulatory change.

GUIDE

Regulatory Reporting Handbook – First Edition

Welcome to the inaugural edition of A-Team Group’s Regulatory Reporting Handbook, a comprehensive guide to reporting obligations that must be fulfilled by financial institutions on a global basis. The handbook reviews not only the current state of play within the regulatory reporting space, but also looks ahead to identify how institutions should be preparing for...