|Time series analysis||Financial econometrics||Predictive sports modelling|
|Time series forecasting||Econometric methodology||Sports statistics|
|State space models||Time-varying parameter models|
- Gorgi, P., Koopman, S.J. and Lit, R. (2018): The analysis and forecasting of ATP tennis matches using a high-dimensional dynamic model, Tinbergen Institute Discussion Paper, TI 18-009/III.
- Koopman, S.J., Lit, R. and Nguyen, T.M. (2018): Modified Efficient Importance Sampling for partially non-Gaussian State Space Models, Accepted to Statistica Neerlandica.
- Koopman, S.J. and Lit, R. (2017): Forecasting football match results in national league competitions using score-driven time series models, Tinbergen Institute Discussion Paper, TI 17-062/III.
- Koopman, S.J., Lit, R. and Lucas, A. (2017): Intraday Stochastic Volatility in Discrete Price Changes: the Dynamic Skellam Model, Journal of the American Statistical Association, 112, 1490-1503.
- 28th (EC)^2 on Time-varying Parameter Models, VU Amsterdam, The Netherlands, December 14-15, 2017.
- 9th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2016), University of Seville, Spain, December 9-11, 2016.
- 5th Rhenish Multivariate Time Series Econometrics Meeting, University of Cologne, October 8-9, 2015.
- Society for Financial Econometrics (SoFiE) conference, Aarhus University, 24-26 June, 2015.
- International Conference on the Policy Implications of Systemic Risk Models and Measure, SYRTO conference in Amsterdam, 4-5 June, 2015.
- International Association for Applied Econometrics (IAAE), Queen Mary University of London, June 26-28, 2014.
- 8th ECB Workshop on Forecasting Techniques, Frankfurt am Main, 13-14 June, 2014.