Data smoothing uses an algorithm to remove noise from a data set, allowing important patterns to stand out. Data smoothing can be used to predict trends, such as those found in securities prices.

Smoothing algorithms for monotonic rating level PD and rating migration probability are proposed. The approaches can be characterized as follows: These approaches are based on constrained maximum ...

In a 2022 paper, Bender, Kuszmaul and four co-authors created just such an algorithm — one that was “history independent,” non-smooth and randomized — which finally reduced the 1981 upper bound, ...

Nevertheless, in 2022, Bender and five colleagues decided to try out a randomized, non-smooth algorithm anyway, just to see whether it might offer any advantages. A Secret History.

In the process of loan pricing, stress testing, capital allocation, modeling of probability of default (PD) term structure and International Financial Reporting Standard 9 expected credit loss ...