11 citations · 20 across the 6 of their papers we have counts for
6 papers
State-Dependent Autoregressive Models: Properties, Estimation and Forecasting
Fabio Gobbi, Sabrina Mulinacci
This paper studies some temporal dependence properties and addresses the issue of parametric estimation for a class of state-dependent autoregressive models for nonlinear time seri…
Gaussian autoregressive process with dependent innovations. Some asymptotic results
Fabio Gobbi, Sabrina Mulinacci
In this paper we introduce a modified version of a gaussian standard first-order autoregressive process where we allow for a dependence structure between the state variable $Y_{t-1…
-mixing and moments properties of a non-stationary copula-based Markov process
Fabio Gobbi, Sabrina Mulinacci
This paper provides conditions under which a non-stationary copula-based Markov process is -mixing. We introduce, as a particular case, a convolution-based gaussian Markov proce…
Granger Independent Martingale Processes
Umberto Cherubini, Fabio Gobbi, Sabrina Mulinacci +1
We introduce a new class of processes for the evaluation of multivariate equity derivatives. The proposed setting is well suited for the application of the standard copula function…
Diffusion covariation and co-jumps in bidimensional asset price processes with stochastic volatility and infinite activity Levy jumps
Fabio Gobbi, Cecilia Mancini
In this paper we consider two processes driven by diffusions and jumps. The jump components are Levy processes and they can both have finite activity and infinite activity. Given d…
Identifying the covariation between the diffusion parts and the co-jumps given discrete observations
Fabio Gobbi, Cecilia Mancini
In this paper we consider two semimartingales driven by diffusions and jumps. We allow both for finite activity and for infinite activity jump components. Given discrete observatio…