Multi-step Estimators and Shrinkage Effect in Time Series Models

Authors: Ivan Svetunkov, Nikos Kourentzes, Rebecca Killick Journal: Computational Statistics Abstract: Many modern statistical models are used for both insight and prediction when applied to data. When models are used for prediction one should optimise parameters through a prediction error loss function. Estimation methods based on multiple steps ahead forecast errors have been shown to […]

Forecasting method vs forecasting model: what’s difference?

If you work in the field of statistics, analytics, data science or forecasting, then you probably have already noticed that some of the instruments that are used in your field are called “methods”, while the others are called “models”. The issue here is that the people, using these terms, usually know the distinction between them, […]

Lecture in HSE, Saint Petersburg

Yesterday I gave a lecture to the master students of Higher School Economics, Saint Petersburg (“Marketing Analytics” programme). This was a very general lecture on “Modern Forecasting”, covering forecasting problems in practice, the solutions to these problems and modern scientific directions in the field. It seems that the lecture was well received and brought up […]

19th IIF Workshop presentation

An IIF workshop “Supply Chain Forecasting for Operations” took place at Lancaster University on 28th and 29th of June. I have given a presentation on a topic that John Boylan and I are currently working on. We suggest a universal statistical model, that allows uniting standard methods of forecasting (for example, for fast moving products) […]