iAQF hosted the Seminar—Machine Learning for Stock Selection

iAQF hosted the Seminar—Machine Learning for Stock Selection

On Dec 10th, 2019, President Fiona, represented GIFP, participated in the seminar—Machine Learning for Stock Selection hosted by iAQF.

iAQF is a not-for-profit, professional society dedicated to fostering the profession of quantitative finance by providing platforms to discuss cutting-edge and pivotal issues in the field. The goal of the series of seminars is to provide a forum for the exchange of new ideas and results related to the area of quantitative finance. This goal is accomplished by hosting workshops where leading practitioners and academics present new work and following the seminars with a reception to facilitate further interaction and discussion.

The speaker of this seminar (Machine Learning for Stock Selection) is Keywan Rasekhschaffe, who is a portfolio manager and senior quantitative strategist at Gresham Investment Management LLC, where he focuses on Gresham’s systematic absolute return strategies. He earned his Ph.D. at the University of Lugano, Swiss Finance Institute, and received his MBA from the University of Oxford. He holds a joint BSc in Politics and Economics from the University of Bristol. During this seminar, he explained how people could apply machine learning to the stock market.

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 significant challenge when one is trying to extract signals from noisy historical data.

During the seminar, Professor Keywan described some of the basic concepts of machine learning, such as what is machine learning, the different methods of machine learning, how to use machine learning correctly, and overfitting issues. Then he provided 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.

After the seminar, Fiona met with Professor Harvey, who is the board member of iAQF, to introduce GIFP. During this process, they understood each other’s associate deeper. In the near future, GIFP and iAQF will cooperate in multiple ways.