activity
20182021
collaborators

6 papers

econ.EM2021

Inference in heavy-tailed non-stationary multivariate time series

Matteo Barigozzi, Giuseppe Cavaliere, Lorenzo Trapani

We study inference on the common stochastic trends in a non-stationary, -variate time series , in the possible presence of heavy tails. We propose a novel methodology whi…

math.ST2021

Changepoint detection in random coefficient autoregressive models

Lajos Horvath, Lorenzo Trapani

We propose a family of CUSUM-based statistics to detect the presence of changepoints in the deterministic part of the autoregressive parameter in a Random Coefficient AutoRegressiv…

econ.EM2020

Sequential monitoring for cointegrating regressions

Lorenzo Trapani, Emily Whitehouse

We develop monitoring procedures for cointegrating regressions, testing the null of no breaks against the alternatives that there is either a change in the slope, or a change to no…

econ.EM2019

Bayesian estimation of large dimensional time varying VARs using copulas

Mike Tsionas, Marwan Izzeldin, Lorenzo Trapani

This paper provides a simple, yet reliable, alternative to the (Bayesian) estimation of large multivariate VARs with time variation in the conditional mean equations and/or in the…

math.ST2019

Testing for strict stationarity in a random coefficient autoregressive model

Lorenzo Trapani

We propose a procedure to decide between the null hypothesis of (strict) stationarity and the alternative of non-stationarity, in the context of a Random Coefficient AutoRegression…

stat.ME2018

Determining the dimension of factor structures in non-stationary large datasets

Matteo Barigozzi, Lorenzo Trapani

We propose a procedure to determine the dimension of the common factor space in a large, possibly non-stationary, dataset. Our procedure is designed to determine whether there are…