Using Randomness in Machine Learning to Reduce Overfitting

In this episode, we talk with Ernie Chan. Ernie, a physicist by training, is the founder of QTS Capital Management and author of a number of books on Quantitative and Algorithmic Trading. In today’s episode, we talk about Ernie’s tail reaper strategy at QTS which seeks to profit from down moves in the S&P. We go into how Gamma Dealer Hedging and Forced Rebalancing exacerbates intraday volatility in the SPX in a way that makes the S&P one of the best places for a tail strategy to work. We also go into the Evolution of Machine Learning and how it is applied to trading strategies including tail reaper and the appropriate way to use kelly criterion for investors - a lesson Ernie learned the hard way.