Please note that this event will take place IN PERSON on Saturday, 22 November, 2025 and Sunday, 22 November, 2025 in London at 6pm London time (1pm New York time).
In collaboration with Imperial College MathSoc!
Full title: A Weekend with Ernie Chan in London: Trading with GenAI
Speaker: Ernest (Ernie) P. Chan
Abstract: In the news, GenAI is usually associated with large language models (LLMs) or with image generation tools, essentially, machines that can learn from text or images and generate text or images. But in reality, these models can learn from many different types of data. In particular, they can learn from time series of asset returns, which is perhaps the most relevant for asset managers. This is a unique opportunity to spend a weekend with Ernie in London and, over these two days, learn how to build trading strategies on the basis of GenAI.
Training Agenda:
- Discriminative AI (supervised learning): CART and neural nets.
- LLM for creating and backtesting trading strategies
- Exercise: features engineering using TA-LIB. Building a gradient-boosted tree (GBT) to predict SPX returns.
- Exercise: building RNN to predict SPX returns. Performance metrics and comparison.
- Generative AI vs Discriminative AI: theory and examples. Semi-supervised learning.
- Deep Autoregressive Models and Transformers
- Exercise: building a poor person's transformer and applying it to time series prediction.
- Exercise: build, finetune, and apply the Lag-Llama transformer.
- Deep Latent Variable Models: Variational Autoencoder (VAE) for time series
- Exercise: using Gaussian Mixture Model (GMM) for regime detection/prediction.
- Exercise: using Hidden Markov Model (HMM) for regime detection/prediction.
- Exercise: using TimeVAE to predict SPX returns.
Venue: Huxley Building, Imperial College London, 180 Queen's Gate, South Kensington, London SW7 2AZ
Biography: Dr. Chan is the founder of Predictnow.ai and QTS Capital Management. Ernie’s career since 1994 has been focusing on the development of statistical models and advanced computer algorithms to find patterns and trends in large quantities of data. He has applied his expertise in machine learning at IBM T.J. Watson Research Centre's Human Language Technologies group, at Morgan Stanley’s Data Mining and Artificial Intelligence Group, and at Credit Suisse’s Horizon Trading Group. He is also the founder and managing member of a quantitative investment management firm, QTS Capital Management, LLC.
Ernie was quoted by the Wall Street Journal , New York Times , Forbes, and the CIO magazine, and interviewed on CNBC’s Closing Bell program, Technical Analysis of Stocks and Commodities magazine, Securities Industry News, Automated Trader magazine, and the CFA Institute Magazine on topics related to quantitative trading.
He is the author of “Quantitative Trading: How to Build Your Own Algorithmic Trading Business“, “Algorithmic Trading: Winning Strategies and Their Rationale“, and “Machine Trading: Deploying Computer Algorithms to Conquer the Markets“ , all published by John Wiley & Sons. He also writes the popular Quantitative Trading blog and conducts workshops on quantitative investment strategies and machine learning in London, UK. He was an Adjunct Associate Professor of Finance at Nanyang Technological University in Singapore, and an Industry Fellow of the NTU-SGX Centre for Financial Education, which is jointly set up by NTU and the Singapore Exchange. He was an adjunct faculty at Northwestern University’s Master’s in Data Science program and supervised student theses there.
Ernie holds a Bachelor of Science degree from University of Toronto in 1988, a Master of Science (1991) and a Doctor of Philosophy (1994) degree in theoretical physics from Cornell University.
Links:
Ernie's website: https://epchan.com/about
