5 papers
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…
MinP Score Tests with an Inequality Constrained Parameter Space
Giuseppe Cavaliere, Zeng-Hua Lu, Anders Rahbek +1
Score tests have the advantage of requiring estimation alone of the model restricted by the null hypothesis, which often is much simpler than models defined under the alternative h…
Specification tests for GARCH processes
Giuseppe Cavaliere, Indeewara Perera, Anders Rahbek
This paper 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.…
Bootstrap Inference for Hawkes and General Point Processes
Giuseppe Cavaliere, Ye Lu, Anders Rahbek +1
Inference and testing in general point process models such as the Hawkes model is predominantly based on asymptotic approximations for likelihood-based estimators and tests. As an…
Bootstrapping Non-Stationary Stochastic Volatility
H. Peter Boswijk, Giuseppe Cavaliere, Anders Rahbek +1
In this paper we investigate how the bootstrap can be applied to time series regressions when the volatility of the innovations is random and non-stationary. The volatility of many…