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
Organizer: International Association for Quantitative Finance
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.
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