2 citations · 4 across the 9 of their papers we have counts for
9 papers
Online detection of distributional changes for time series in metric spaces
B. Cooper Boniece, Lajos Horváth, Lorenzo Trapani
We propose an online testing framework for detecting distributional changes in serially dependent data with values in a separable metric space. Based on two-sample -statistics,…
Sequential monitoring for distributional changepoints using degenerate U-statistics
B. Cooper Boniece, Lajos Horváth, Lorenzo Trapani
We investigate the online detection of changepoints in the distribution of a sequence of observations using a class of degenerate \textit{U}-statistic-type processes. We consider a…
A general randomized test for Alpha
Daniele Massacci, Lucio Sarno, Lorenzo Trapani +1
We propose a methodology to construct tests for the null hypothesis that the pricing errors of a panel of asset returns are jointly equal to zero in a linear factor asset pricing m…
Inference in matrix-valued time series with common stochastic trends and multifactor error structure
Rong Chen, Simone Giannerini, Greta Goracci +1
We develop an estimation methodology for a factor model for high-dimensional matrix-valued time series, where common stochastic trends and common stationary factors can be present.…
Moving sum procedure for multiple change point detection in large factor models
Matteo Barigozzi, Haeran Cho, Lorenzo Trapani
This paper proposes a moving sum methodology for detecting multiple change points in high-dimensional time series under a factor model, where changes are attributed to those in loa…
Sequential monitoring for explosive volatility regimes
Lajos Horvath, Lorenzo Trapani, Shixuan Wang
In this paper, we develop two families of sequential monitoring procedure to (timely) detect changes in a GARCH(1,1) model. Whilst our methodologies can be applied for the general…
Fast Online Changepoint Detection
Fabrizio Ghezzi, Eduardo Rossi, Lorenzo Trapani
We study online changepoint detection in the context of a linear regression model. We propose a class of heavily weighted statistics based on the CUSUM process of the regression re…
Real-time monitoring with RCA models
Lajos Horváth, Lorenzo Trapani
We propose a family of weighted statistics based on the CUSUM process of the WLS residuals for the online detection of changepoints in a Random Coefficient Autoregressive model, us…
On changepoint detection in functional data using empirical energy distance
B. Cooper Boniece, Lajos Horváth, Lorenzo Trapani
We propose a novel family of test statistics to detect the presence of changepoints in a sequence of dependent, possibly multivariate, functional-valued observations. Our approach…