Thrifting Alpha: Using Ensemble Learning To Revitalize Tired Alpha Factors
Details
Join us for a presentation by Quantopian Data Scientist, Max Margenot, on Thrifting Alpha. Food and drinks will be provided!
Thrifting Alpha: Using Ensemble Learning To Revitalize Tired Alpha Factors
Finding alpha is a constant search in algorithmic trading. New alpha factors are always exciting, but sometimes you can come up with new trading signals simply by applying novel aggregation techniques to familiar factors. In this talk we will discuss using ensemble learning methods to combine individual weak signals into stronger factors and assessing their predictive power for long-short equity strategies.
About Max Margenot
Max works at Quantopian as a data scientist and manages the lecture series for the academic team, coordinating content development and helping to run the company's quantitative finance workshops.
Max holds a MS in Mathematical Finance from Boston University and has a strong background in statistics and computer science.
He has implemented trading systems based on machine learning in the past and has published research on theoretical mathematics.
Thrifting Alpha: Using Ensemble Learning To Revitalize Tired Alpha Factors