Generative AI for Asset Managers is a 2-day online workshop to demonstrate how we construct a discretionary trading strategy using an LLM.
The difference between algorithmic and discretionary traders is that the latter use qualitative, unstructured data as input to their brains, form high level understanding and intuition, and make trading decisions. With the advent of Generative AI and Large Language Models (LLMs), we can now systematize and deploy at scale discretionary trading strategies – essentially creating “George Soros on a chip”.
During the workshop, we will demonstrate how asset managers and traders can use Google’s BARD to turn unstructured data such as the audio feed of the Federal Reserve’s Chair’s speech into high frequency trading signals and backtest such strategies, all at minimal cost. We will then break into small groups to explore and experiment with variations and improvements on the basic code, as well as brainstorm other use cases of LLM for asset management.
This workshop will be hosted by Dr. Ernest Chan, Founder and CEO of Predictnow.ai, and Dr. Roger Hunter, Chief Technology Officer at QTS Capital Management, and Dr. Hamlet Medina, Chief Data Scientist at Criteo. We are honoured to be joined by Dr. Lisa Huang, Head of AI Investment Management at Fidelity Investments who will present as a keynote speaker.
While the intended audience for this event includes, asset managers, venture investors, entrepreneurs, product developers, regulators, finance and AI researchers. If you fall into another category but feel like you would be a good fit for this workshop, send us an email at email@example.com and we can help clarify any questions you have.
Large Language Models (LLMs) & Generative Pre-trained Transformers (GPT)
Risks Associated with LLMs
Using LLMs for trading Federal Reserve Chair’s speeches
Deploying LLMs in Production