Overview of VAEs and their application to time-series data.

Overview of discriminative AI methods including CART decision trees and neural networks for trading data.

Hands-on exercise building a lightweight transformer for time-series prediction.

Hands-on exercise building an RNN to predict SPX returns and evaluating performance metrics.

Hands-on exercise applying TimeVAE to predict SPX returns.

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. In this talk, and in our accompanying book (Generative AI for Trading and Asset Management), we highlight both the practical applications and the fundamental principles of GenAI, with a special focus on how these technologies apply to trading and asset management.

Set up a Free Tier cloud account and understand how data is organized in Couchbase. Write queries using SQL++, Key-Value, Graph, and Time-Series data.

What are the benefits of NoSQL compared to SQL databases, and multi-model applications with Couchbase database platform: JSON, Key-Value, SQL++, Graph, and Time Series.