Rutger Lit, PhD

Short Bio
Rutger Lit holds a Bachelor’s degree and Master’s degree in Econometrics and Operations Research from the Vrije Universiteit Amsterdam (VU). In April 2013, Rutger started working as a PhD candidate at the Finance department at the VU. On February 9, 2016, Rutger defended his dissertation titled Time-varying parameter models for discrete valued time series Currently, he is a research fellow at the VU, specialising in time series analysis. Rutger published in top statistical journals like the Journal of the American Statistical Association and Journal of Econometrics.

In 2017, he founded Nlitn, a company offering consultancy services. Nlitn also offers full data solution packages for its clients, for example, the Time Series Lab software series.
  • Estimation of final standings in football competitions with premature ending: the case of COVID-19 [link] with Gorgi, P.  and Koopman, S.J. AStA - Advances in Statistical Analysis (2020)
  • The analysis and forecasting of tennis matches using a high-dimensional dynamic model [link] with Gorgi, P.  and Koopman, S.J. Journal of the Royal Statistical Society, Series A (2019)
  • Long Term Forecasting of El Niño Events via Dynamic Factor Simulations [link] with Li, M., Koopman, S.J., Lit, R. and Desislava Petrova Journal of Econometrics (2020)
  • Forecasting football match results in national league competitions using score-driven time series models [link] with Koopman, S.J. International Journal of Forecasting (2019)
  • Dynamic Discrete Copula Models for High Frequency Stock Price Changes [link] with Koopman, S.J. , Lucas, A. and Opschoor, A.  Journal of Applied Econometrics (2018)
  • Modified Efficient Importance Sampling for partially non-Gaussian State Space Models [link] with Koopman, S.J.  and T.M. Nguyen Statistica Neerlandica (2019)
  • Intraday Stochastic Volatility in Discrete Price Changes: the Dynamic Skellam Model [link] with Koopman, S.J.  and Lucas, A.  Journal of the American Statistical Association (2017), 112, 1490-1503
  • Model-Based Business Cycle and Financial Cycle Decomposition for Europe and the United States [link] with Koopman, S.J.  and Lucas, A.  Systemic Risk Tomography: Signals, Measurements and Transmission Channels, ISTE-Elsevier (2016)
  • A dynamic bivariate Poisson model for analysing and forecasting match results in the English Premier League [link], with Koopman, S.J.  Journal of the Royal Statistical Society, Series A (2015), 178(1), 167-186
Extensive knowledge of programming languages Python, MATLAB, OxMetrics, the document preparation software Latex, and Microsoft Excel.
Proficient at HTML, CSS, PHP, Flask, Bootstrap and the programming languages R and C.
Chess Formula 1 Sports statistics
Bouldering Cave exploration Coding
Car restoration Mountains Numbers
8-bit computing Econometrics Border Collies