We show how to mix machine learning signals such as kernel smoothing and fuzzy memberships via the Entropy Pooling approach by Meucci (2008). We illustrate a case study, where we overlay an exponentially time-decayed prior to a pseudo-Gaussian kernel that emphasizes market scenarios where...

In the Flexible Probabilities approach, given the historical distribution (histogram) of the returns of a portfolio, we can stress-test the portfolio under different time periods and market environments, by adjusting the relative weights (Flexible Probabilities) of the historical returns in the...

We represent affine sub-manifolds of exponential family distributions as minimum relative entropy sub-manifolds. With such representation we derive analytical formulas for the inference from partial information on expectations and covariances of multivariate normal distributions; and we improve...