Refereed articles

  1. Gorgi, P., and Koopman, S. J. (2021). Beta observation-driven models with exogenous regressors: a joint analysis of realized correlation and leverage effects. Journal of Econometrics, https://doi.org/10.1016/j.jeconom.2021.06.010.

  2. Gorgi, P., Koopman, S. J., and Lit, R. (2021). Estimation of final standings in football competitions with premature ending: the case of COVID-19AStA Advances in Statistical Analysis, https://doi.org/10.1007/s10182-021-00415-7.

  3. Blasques, F., Gorgi, P., and Koopman, S. J. (2021). Missing observations in observation-driven time series models. Journal of Econometrics, 221, 542-568.

  4. Gorgi, P. (2020). Beta–negative binomial auto‐regressions for modelling integer‐valued time series with extreme observationsJournal of the Royal Statistical Society: Series B, 82, 1325-1347.​

  5. Gorgi, P., Koopman, S. J., and Lit, R. (2019). The analysis and forecasting of tennis matches by using a high dimensional dynamic model. Journal of the Royal Statistical Society: Series A, 182, 1393-1409.

  6. Blasques, F., Gorgi, and P., Koopman, S. J. (2019). Accelerating score-driven time series models. Journal of Econometrics, 212, 359-376.

  7. Gorgi, P., Koopman, S. J., and Li, M. (2019). Forecasting economic time series using score-driven dynamic models with mixed data sampling. International Journal of Forecasting, 35, 1735-1747.

  8. Gorgi, P., Hansen, P. R., Janus, P., and Koopman, S. J. (2019). Realized Wishart-GARCH: A Score-driven Multi-Asset Volatility Model. Journal of Financial Econometrics, 17, 1-32. (R code available here).

  9. Angelini, G., and Gorgi, P. (2018). DSGE Models with observation-driven time-varying volatility Economics Letters, 171, 169-171.

  10. Blasques, F., Gorgi, P., Koopman, S. J., and Wintenberger, O. (2018). Feasible invertibility conditions and maximum likelihood estimation of observation-driven models. Electronic Journal of Statistics, 12, 1019-1052.

  11. Gorgi, P. (2018). Integer-valued autoregressive models with survival probability driven by a stochastic recurrence equationJournal of Time Series Analysis, 39, 150-171.

Working papers

Talks in seminars and conferences