Events

Principal component analysis (PCA) is a useful tool when trying to uncover factor models from historical asset returns. For the implied volatilities of U.S. equities there is a PCA-based model with a principal eigenportfolio whose return time series lies close to that of an overarching market factor. Specifically, this market factor is the index resulting…

Persistent homology is a key method in topological data analysis, a young but rapidly growing field at the intersection of computational geometry and algebraic topology. Persistence is used to describe the shape of data in a way that generalizes clustering: besides considering what connected components (clusters) are present in the data, it also describes their…

Many estimates in analysis  have certain “common structures” which makes it possible to obtain them with  what is now called Bellman function method. Originally the method appeared in control theory (stochastic or deterministic), however its systematic use  in harmonic analysis or probability started only recently  in works of Burkholder where he obtained the sharp constants…