nlitn

Turning data into actionable insights


At Nlitn we are passionate about forecasting and econometric analysis of time series. The company was founded by successful academics who developed some of the cutting edge data analysis methods. Our dynamic team still has outstanding contacts in the academic world and we are best positioned to create value for our clients based on the latest developments at the frontiers of knowledge. The two branches of the company are consultancy and software development.

Consultancy services

Through deep knowledge of econometric time series methodology, Nlitn consultancy works with clients to extract as much information as possible from their time series data sets. We refer to this as signal extraction and we use it to make time series evaluation and forecasts as accurate as possible. Nlitn has expertise in many areas. Among them are finance, sports, and climatology.

Software development

With the publication in top statistical journals comes a wealth of coding experience. We know how to efficiently implement financial and econometric algorithms in languages like Python, Matlab, R, OxMetrics and C. Especially regarding OxMetrics we can call ourselves experts and we work closely with its developers to extend and improve this family of software packages further.

Solutions

Nlitn your data

We live in an era of big data. Many companies have a wealth of data at their disposal but do not utilize their data to the full extent. Does your company have a wealth of data? We know how to extract information from your data that is valuable for your company!

Nlitn your products

We offer full data solution packages to suit your data analyzing needs. An example is the Structural Time series Analyser, Modeller and Predictor program or STAMP in short. STAMP is a statistical / econometric software system for time series models with unobserved components such as trend, seasonal, cycle and irregular.

Team

Rutger Lit

Rutger Lit is a time series expert who has a PhD in econometrics from the Vrije Universiteit Amsterdam. He has publications in top statistical journals and he co-authored several papers with professor S.J. Koopman, a leading scientist in the field of time series econometrics. Rutger is currently developing version 9 of the Structural Time series Analyser, Modeller and Predictor program (STAMP) which will offer some very useful new data analysing techniques. In his free time, Rutger likes to play poker and is trying to become better in climbing and bouldering.

Projects

Research

Get in touch