Features

Academic
foundation

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.

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Customizable
software

The Time Series Lab - Score Edition software is proprietary software that can be downloaded using this link and is licensed without cost, even for 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 meet the clients' needs. Please Contact us for more information about customized versions and pricing of the software.

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Score-driven
methodology

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.

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Software

A five step approach to extract signal from time series

Research

Connecting Academia and the Industry

Time Series Lab - Article Series

The Time Series Lab - Article Series are dedicated to research performed with Time Series Lab software. The scope of the series includes the analysis and forecasting of a wide range of time series in fields like economics, finance, sports, climatology, biology, and health science.

The Time Series Lab team is constantly looking for ways to improve the software. We do this by continuously working on time series theory, methodology, and applications by means of conducting our own research and studying the work of others. The Time Series Lab team would also like to hear suggestions from you on how to advance the software further. This was one of the reasons to start the Time Series Lab - Article Series

Time Series Lab - Article Series

Other score-driven research

Team

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, a company offering consultancy services. It also offers full data solution packages to meet the data analysis needs of clients. For example, 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

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