3 papers
q-fin.PM2026
Post-Screening Portfolio Selection
Yoshimasa Uematsu, Shinya Tanaka
We propose post-screening portfolio selection (PS), a two-step framework for high-dimensional mean--variance investing. First, assets are screened by Lasso-type regression of a…
stat.ME2026
Testing Conditional Independence via the Spectral Generalized Covariance Measure: Beyond Euclidean Data
Ryunosuke Miyazaki, Yoshimasa Uematsu
We propose a conditional independence (CI) test based on a new measure, the \emph{spectral generalized covariance measure} (SGCM). The SGCM is constructed by expressing the squared…
math.ST2024
High-Dimensional Single-Index Models: Link Estimation and Marginal Inference
Kazuma Sawaya, Yoshimasa Uematsu, Masaaki Imaizumi
This study proposes a novel method for estimation and hypothesis testing in high-dimensional single-index models. We address a common scenario where the sample size and the dimensi…