How a hedge fund firm is cutting through the noise around machine learning

This article was originally published on International Business Times. Much of the current machine learning revolution originated around applications like computer vision that have nothing to do with finance. Financial data modeling is beset by a low signal to noise ratio, whereas data used to teach a computer to identify a picture of a cat, for example, is unambiguous. The financial universe is a non-stationary environment with variable patterns of correlation between stocks, bonds and other instruments. Not least, the task in hand is essentially about predicting things that haven't happened yet.