QuantCon NYC 2018 is less than one month away! Happening April 26th - 28th, our program features three days of insightful workshops and talks, with a clear focus on algorithmic trading and portfolio optimization, and how data science, alternative data sets, and machine learning, can help you craft and improve on your trading strategies.
The full agenda and talk abstracts are now available at www.quantcon.com.
Dr. Marcos López de Prado, CEO of True Positive Technologies, returns to QuantCon to present The 7 Reasons Most Machine Learning Funds Fail. He will discuss the common reasons behind why the rate of failure in quantitative finance is high, and particularly so in financial machine learning.
Our second keynote, Dr. Laruen H. Cohen, L.E. Simmons Professor at Harvard Business School, will present IQ from IP: Simplifying Search in Portfolio Choice. In this talk, Dr. Cohen will discuss how mutual funds exert effort to reduce the dimensionality of their portfolio selection problem and how this tracking has powerful implications for their portfolio choice, and its information content.
Other talks include:
Automation of Equity Markets, the Evolution of High Frequency Trading and the Applicability of Deep Learning by Bob Litzenberger, Professor Emeritus at Wharton Business School and Alexander Litzenberger, student at Carnegie Melon
Adaptive Markets and Neuro-finance by Kathryn Kaminski, Visiting Scientist at the MIT Laboratory for Financial Engineering
Statistical Algorithm Selection: A Data Science Approach to Managing Systematic Trading Strategies Developed by "The Crowd" by Dr. Jessica Stauth, Investment Team Managing Director at Quantopian
Using Bayesian Optimization to Simultaneously Tune Multiple Metrics by Scott Clark, Co-Founder and CEO of SigOpt