Giuseppe Cavaliere

Biographic Data

ID5731705
NAMEGiuseppe Cavaliere
GIVEN NAMESGiuseppe
FAMILY NAMECavaliere
SIGNATURECAVALIERE G
AFFILIATIONSUniversity of Bologna
ORCID0000-0002-2856-0005
VERIFIEDYes
TOTAL WORKS6
TOTAL CITATIONS0
WORKS AS AUTHOR6
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2006
LATEST PUBLICATION YEAR2025
H-INDEX0

  • Factor Network Autoregressions

    Matteo Barigozzi, Giuseppe Cavaliere et al.ARTICLEJournal of Business and Economic…2025

    We propose a factor network autoregressive (FNAR) model for time series with complex network structures. The coefficients of the model reflect many different types of connections between economic agents (“multilayer network”), which are summarized into a smaller number of network matrices (“network factors”) through a novel tensor-based principal component approach. We provide consistency and asymptotic normality results for the estimation of the…

  • Specification Tests for GARCH Processes with Nuisance Parameters on the Boundary

    Open AccessGiuseppe Cavaliere, Indeewara Perera et al.ARTICLEJournal of Business and Economic…2024

    This article develops tests for the correct specification of the conditional variance function in GARCH models when the true parameter may lie on the boundary of the parameter space. The test statistics considered are of Kolmogorov-Smirnov and Cramér-von Mises type, and are based on empirical processes marked by centered squared residuals. The limiting distributions of the test statistics depend on unknown nuisance parameters in a nontrivial way,…

  • Bootstrap inference and diagnostics in state space models

    Open AccessGiovanni Angelini, Giuseppe Cavaliere et al.ARTICLEJournal of Applied Econometrics2022

    This paper investigates the potentials of the bootstrap as a tool for inference on the parameters of macroeconometric models which admit a state space representation. We consider a bootstrap estimator of the parameters of state space models and show that the bootstrap realizations of this estimator, usually employed to approximate asymptotic confidence intervals, p ‐values, and critical values of tests, can be also constructively used to build a …

  • Adaptive Inference in Heteroscedastic Fractional Time Series Models

    Giuseppe Cavaliere, MORTEN ØRREGAARD NIELSEN et al.ARTICLEJournal of Business and Economic…2022

    We consider estimation and inference in fractionally integrated time series models driven by shocks which can display conditional and unconditional heteroscedasticity of unknown form. Although the standard conditional sum-of-squares (CSS) estimator remains consistent and asymptotically normal in such cases, unconditional heteroscedasticity inflates its variance matrix by a scalar quantity, λ>1, thereby inducing a loss in efficiency relative to th…

  • Bootstrapping Noncausal Autoregressions

    Giuseppe Cavaliere, Heino Bohn Nielsen et al.ARTICLEJournal of Business and Economic…2020

    In this article, we develop new bootstrap-based inference for noncausal autoregressions with heavy-tailed innovations. This class of models is widely used for modeling bubbles and explosive dynamics in economic and financial time series. In the noncausal, heavy-tail framework, a major drawback of asymptotic inference is that it is not feasible in practice as the relevant limiting distributions depend crucially on the (unknown) decay rate of the t…

  • Stochastic Volatility

    Open AccessGiuseppe CavaliereARTICLEThe Economic Journal2006

    Although it was recognised many decades ago that financial markets are characterised by volatility which changes over time, it has only been in the last 20 years or so that a large interest has been shown by econometricians in time series models with time‐varying volatility. Undoubtedly, this was mainly due to Robert Engle’s seminal 1982 work on ARCH processes, which model the risky part of returns as the product process where ɛt is a martingale …