Turning a research paper into a reliable, implementable portfolio has traditionally required significant effort in data preparation, signal implementation, validation, and replication. While innovative ideas are abundant, bridging the gap between research and execution remains one of the biggest challenges in systematic research.
In this webinar, Balakrishnan Ilango, Head of Innovation & Analytics – Asia Pacific, LSEG, will demonstrate how AI agents connected directly to institutional data feeds can streamline this process. Through a live end-to-end replication of a published strategy, attendees will see how natural language-driven AI can assist with universe construction, point-in-time data assembly, signal implementation, backtesting, and portfolio translation.
The session will also explore how AI-driven workflows help uncover alpha decay, regime dependence, transaction cost sensitivity, and the data decisions that distinguish a plausible backtest from a trustworthy one. By leveraging a reusable framework of AI agents, plugins, skills, and recipes, the approach delivers deterministic, transparent, and auditable outputs that enhance reproducibility and confidence in systematic research.
Whether you are involved in research, analytics, data science, technology, or quantitative strategies, this webinar offers practical insights into how AI can help accelerate the journey from idea to implementation while maintaining transparency throughout the process.
Webinar Details
Speaker: Balakrishnan Ilango
Designation: Head of Innovation & Analytics – Asia Pacific, LSEG
Date: 13 August 2026
Time: 05:00 PM – 06:00 PM IST