Research Output per year
Personal profile
Personal information
Paolo Gorgi is an assistant professor at the department of Econometrics/OR of the Vrije Universiteit.
Research
His main research interests are:
- Score-driven time series models
- Stochastic processes
- Forecasting economic variables
- Statistical inference in non-linear dynamic models
Ancillary activities
No ancillary activities
Ancillary activities are updated daily
Education/Academic qualification
PhD, Joint degree University of Padova & Vrije Universiteit Amsterdam
1 Jan 2014 → 31 Dec 2016
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Recurrence Equations
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Maximum Likelihood Estimator
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Survival Probability
Mathematics
Invertibility
Mathematics
Autoregressive Model
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Maximum Likelihood Estimation
Mathematics
Misspecified Model
Mathematics
Stochastic Equations
Mathematics
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 2015 2019
Forecasting economic time series using score-driven dynamic models with mixed-data sampling
Gorgi, P., Koopman, S. J. & Li, M., 1 Jan 2019, (Accepted/In press) In : International Journal of Forecasting.Research output: Contribution to Journal › Article › Academic › peer-review
Economic forecasting
Sampling
Weighting
GDP growth
Inflation
Realized wishart-garch: A score-driven multi-Asset volatility model
Gorgi, P., Hansen, P. R., Janus, P. & Koopman, S. J., Jan 2019, In : Journal of Financial Econometrics. 17, 1, p. 1-32 32 p.Research output: Contribution to Journal › Article › Academic › peer-review
Assets
Volatility models
Covariance matrix
Small sample
Sample size
DSGE Models with Observation-Driven Time-Varying parameters
Angelini, G. & Gorgi, P., 2018, Amsterdam: Tinbergen Institute, 10 p. (TI Discussion Paper Series; vol. 18, no. 030/III).Research output: Working paper › Academic
DSGE Models with observation-driven time-varying volatility
Angelini, G. & Gorgi, P., Oct 2018, In : Economics Letters. 171, p. 169-171 3 p.Research output: Contribution to Journal › Article › Academic › peer-review
DSGE models
Time-varying volatility
Structural shocks
Simulation
Time variation
Feasible invertibility conditions and maximum likelihood estimation for observation-driven models
Blasques, F., Gorgi, P., Koopman, S. J. & Wintenberger, O., Mar 2018, In : Electronic Journal of Statistics. 12, 1, p. 1019-1052 34 p.Research output: Contribution to Journal › Article › Academic › peer-review
Open Access
Invertibility
Maximum Likelihood Estimation
Maximum Likelihood Estimator
Time Series Models
Misspecified Model