Long-short equity strategies are an incredibly robust family of strategies. They depend on a methodology to rank equities, and perform proportionally to how well the ranking system differentiates high and low future returns. They avoid many forms of statistical bias and noise, and are an excellent way to make money off a model that predicts future returns for any given asset.
Join us for our webinar on Thursday, September 17th at 12pm ET and get an overview on the background and implementation of a long-short equity strategy on Quantopian.
Click here to reserve your spot.
This talk is part of Quantopian’s Summer Lecture Series. All lecture materials can be found at: www.quantopian.com/lectures.
Delaney Granizo-Mackenzie is an engineer at Quantopian whose focus is on how Quantopian can be used as a teaching tool. After studying computer science at Princeton, Delaney joined Quantopian in 2014. Since then he has led successful course integrations at MIT Sloan and Stanford, and is working with over 20 courses for this fall. Delaney is using his experience and feedback from professors to build a quantitative finance curriculum focusing on best statistical practices to be offered for free. Delaney’s background includes 7 years of academic research at a bioinformatics lab, and a strong focus on statistics and machine learning.