Mohammad Yousuf Hussain

Chevron down

Application of Generative Adversarial Networks (GANs) in Algorithmic Trading and Aggregation of Low-Alpha Strategies

Machine learning is attracting a lot of attention recently due to the promising capabilities of adapting, learning and even self-teaching algorithms. Application of machine learning in algorithmic trading offers a variety of opportunities to extract greater alpha and improve order execution. In this session, I am going to present the application of Generative Adversarial Networks (GANs) in algorithmic trading and share insights on aggregation of strategies.I would highlight the key functions of a strategy aggregator; categorisation of strategies, classification of market behaviour and application of ensemble learning. I would then briefly discuss about the design and development of controls for the aggregator framework that allows ease in monitoring and optimisation of the solution.

Mohammad Yousuf Hussain, CFA is a Senior Technology and Innovation Specialist at HSBC. Working in the Applied Innovation and Strategic Investments team, he has designed and delivered a number of artificial intelligence based electronic trading solutions. Previously, he was a Senior Consultant at GreySpark Partners where he delivered projects for UBS, HSBC, Mizuho Securities, Nomura-Instinet, Interactive Brokers and SFC. He developed expertise in assessing trading algorithms by investigating the market abuse incidents for the regulator.

Buttonlinkedin

As Featured In

Original
Original
Original
Original
Original
Original

Partners & Attendees

Intel.001
Nvidia.001
Ibm watson health 3.001
Acc1.001
Rbc research.001
Forbes.001
Twentybn.001
Kd nuggets.001
Mit tech review.001
Facebook.001
Maluuba 2017.001
Graphcoreai.001
This website uses cookies to ensure you get the best experience. Learn more