The time series methodology of the Time Series Lab - Score Edition package is well-founded in the academic world and has appeared in highly respected academic journals. For an overview of score-driven publications we refer to the www.gasmodel.com website. The score-driven methodology was developed independently at VU University Amsterdam and Cambridge University. Currently, the knowledge and experience of both universities have been combined and Professor S.J. Koopman (VU Amsterdam) and Professor A.C. Harvey (Cambridge) are part of the Time Series Lab team.

More Information


The Time Series Lab - Score Edition software is proprietary software that can be downloaded using this link and is licensed without cost, including commercial purposes. Make sure to read the license agreement before installing the program. Some users / companies require more specialized features of the software. Therefore, Time Series Lab - Score Edition can be made available in a commercial package, fully customized to suit the clients' needs. Please Contact us for more information about customized versions and pricing of the software.

More Information


Score-driven models were proposed in their full generality in Creal, Koopman, and Lucas (2013) as developed at the time at VU University Amsterdam. Simultaneously, Andrew Harvey authored the book Dynamic Models for Volatility and Heavy Tails (2013) in which the mechanism to update the parameters over time is the scaled score of the likelihood function. The score-driven model encompasses other well-known models such as the generalized autoregressive conditional heteroskedasticity (GARCH) model, autoregressive conditional duration (ACD) model, and Poisson count models with time-varying mean.

More Information


A five step approach to extract signal from time series

The Lab

Connecting Academia and the Industry

Advances in time series

The Time Series Lab team is constantly looking for ways to improve the software. We do this by continuously working on time series theory and methodology by means of conducting our own research and studying the work of others. If there is something new in the world of time series, we know it. Our Time Series Lab is a controlled environment in which we test time series methodology and new features before making it available in the Time Series Lab software.

A new feature or newly developed methodology may work well on one time series but does not offer advantages for another time series. We make sure that the methodology in Time Series Lab is thoroughly tested and has proven itself before being made available to you.

On the right, you find research output that currently has our attention in the Time Series Laboratory. The listed journal articles are all related to the score-driven methodology that we apply in the Time Series Lab software package.

Current research


Close connection with academia

R. Lit, PhD

Rutger Lit is a research fellow of Vrije Universiteit Amsterdam and has a PhD in econometrics specializing in time series analysis. In 2017, he founded Nlitn which is a company that offers consultancy services. Nlitn also offers full data solution packages to suit the data analysis needs of clients. An example is the Time Series Lab software package.

Personal website
Professor S.J. Koopman

Siem Jan Koopman is Professor of Econometrics at the Department of Econometrics, Vrije Universiteit Amsterdam. He is also a research fellow at Tinbergen Institute and a long-term Visiting Professor at CREATES, University of Aarhus.

He held positions at London School of Economics and CentER (Tilburg University), and had long-term visits at US Bureau of the Census, European University Institute, and European Central Bank, Financial Research.

Personal website
Professor A.C. Harvey

Andrew Harvey is Emeritus Professor of Econometrics in the Faculty of Economics and Politics, University of Cambridge. He was Professor of Econometrics at the London School of Economics before coming to Cambridge in 1996. His most recent book is a 2013 monograph entitled Dynamic Models for Volatility and Heavy Tails.

Personal website

Get in touch

Sign up

Receive updates from Time Series Lab