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Personal profile

Personal information

Luca Rossini is a Marie-Curie Individual Fellowship at the department of Econometrics/OR of the Vrije Universiteit.


His main research interest are:

- Bayesian econometrics (in particular Bayesian nonparametrics)

- Graph Theory and Network Theory for time series models

- Forecasting Electricity Prices

- Objective Bayesian Analysis

Ancillary activities

No ancillary activities

Ancillary activities are updated daily

Education/Academic qualification

Economics, PhD, Ca' Foscari University Venice

Sep 2013Jan 2017

Statistics, Master, Università di Padova

Sep 2011Apr 2013


  • Bayesian Econometrics
  • Graph Theory for time series
  • Forecasting Methods

Fingerprint Fingerprint is based on mining the text of the person's scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

Negative Binomial Model Mathematics
Bayesian Nonparametrics Mathematics
Copula Mathematics
Transition Probability Mathematics
Random Measure Mathematics
Time Series Models Mathematics
Electricity Mathematics
Credit Scoring Mathematics

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Research Output 2017 2019

Bayesian nonparametric sparse VAR models

Billio, M., Casarin, R. & Rossini, L., 2019, (Accepted/In press) In : Journal of Econometrics.

Research output: Contribution to JournalArticleAcademicpeer-review

Vector autoregressive model
Stylized facts

Hierarchical Species Sampling Models

Bassetti, F., Casarin, R. & Rossini, L., 30 Jan 2019, In : arXiv.org.

Research output: Contribution to JournalArticleAcademic

Prior distribution
Random Measure
Random Probability Measure
Nonparametric Inference

Bayesian non-parametric conditional copula estimation of twin data

Dalla Valle, L., Leisen, F. & Rossini, L., 1 Apr 2018, In : Journal of the Royal Statistical Society. Series C: Applied Statistics. 67, 3, p. 523-548 26 p.

Research output: Contribution to JournalArticleAcademicpeer-review

Bayesian Nonparametrics

Comparing the Forecasting Performances of Linear Models for Electricity Prices with High RES Penetration

Gianfreda, A., Ravazzolo, F. & Rossini, L., 12 Dec 2018, In : arXiv.org.

Research output: Contribution to JournalArticleAcademic

Electricity price
Forecasting performance
Renewable energy sources

Loss-based approach to two-piece location-scale distributions with applications to dependent data

Leisen, F., Rossini, L. & Villa, C., 28 Nov 2018, In : arXiv.org.

Research output: Contribution to JournalArticleAcademic

Dependent Data
Exponential Power Distribution
Location-scale Model