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

Recorded Webinar: Unlocking value: Harnessing modern data platforms for data integration, advanced investment analytics, visualisation and reporting

Modern data platforms are bringing efficiencies, scalability and powerful new capabilities to institutions and their data pipelines. They are enabling the use of new automation and analytical technologies that are also helping firms to derive more value from their data and reduce costs. Use cases of specific importance to the finance sector, such as data...

BLOG

From Broker Bias to Independent Insight: The Case for Cloud-Native TCA

For years, the path of least resistance for buy-side transaction cost analysis (TCA) was simple: let the broker do it. Historically, asset managers have relied on their execution counterparties to provide post-trade reporting. It was a workflow of convenience. Brokers executed the trades and subsequently provided the analysis on how well they performed. However, this...

EVENT

Eagle Alpha Alternative Data Conference, London, hosted by A-Team Group

Now in its 8th year, the Eagle Alpha Alternative Data Conference managed by A-Team Group, is the premier content forum and networking event for investment firms and hedge funds.

GUIDE

Regulatory Data Handbook 2019/2020 – Seventh Edition

Welcome to A-Team Group’s best read handbook, the Regulatory Data Handbook, which is now in its seventh edition and continues to grow in terms of the number of regulations covered, the detail of each regulation and the impact that all the rules and regulations will have on data and data management at your institution. This...