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

Challenging the Status Quo: Re-imagining the Trading Desk for 2026 and Beyond

The opening session of A-Team Group’s recent TradingTech Summit Europe set a pragmatic tone for the discussions that followed. In a fireside chat between Stuart Lawrence, Head of EMEA Equity Trading at UBS Asset Management, and Monika Fernando, Product Leader, FinTech & Digital Platforms and former Head of Global FI Client Data & Analytics at...

EVENT

AI in Data Management Summit New York City

Following the success of the 15th Data Management Summit NYC, A-Team Group are excited to announce our new event: AI in Data Management Summit NYC!

GUIDE

Entity Data Management Handbook

Following on from the success of our Regulatory Data Handbook, A-Team Group is pleased to introduce its new Entity Data Management Handbook which is available for free download. This Handbook is the ultimate guide to all things entity data: Why Entity Data is important A full review of Legal Entity Identifiers (LEIs) Where they came...