Name: Machine Learning for Stock Selection

From: 10 Dec 2019

To: 10 Dec 2019

Address: Fordham Gabelli School of Business, McNally Amphitheatre 140 West 62nd Street New York, NY 10023
United States

Organizer: International Association for Quantitative Finance

Key speakers: Keywan Rasekhschaffe, Manager, Gresham Investment Management

Web page: https://www.iaqf.org/event/upcoming

Pricing: - variable

Description: Machine learning is an increasingly important and controversial topic in quantitative finance. A lively debate persists as to whether machine learning techniques can be practical investment tools.

Although machine learning algorithms can uncover subtle, contextual, and nonlinear relationships, overfitting poses a major challenge when one is trying to extract signals from noisy historical data.

We describe some of the basic concepts of machine learning and provide a simple example of how investors can use machine learning techniques to forecast the cross-section of stock returns while limiting the risk of overfitting.