ISF2022: How to make ETS work with ARIMA

This time ISF took place in Oxford. I acted as a programme chair of the event and was quite busy with schedule and some other minor organisational things, but I still found time to present something new. Specifically, I talked about one specific part of ADAM, the part implementing ETS+ARIMA. The idea is that the … Read more

A New Taxonomy for Vector Exponential Smoothing and Its Application to Seasonal Time Series

Authors: Ivan Svetunkov, Huijing Chen, John E. Boylan. Journal: European Journal of Operational Research Abstract: In short-term demand forecasting, it is often difficult to estimate seasonality accurately, owing to short data histories. However, companies usually have multiple products with similar seasonal demand patterns. A possible solution, in this case, is to use the components of … Read more

Vector Exponential Smoothing with PIC restrictions

About the paper. Introduction When you follow academics on social media, you typically see many success stories. This person published a paper in Management Science; another one published in EJOR; your colleague from a different university created a great package; and there is also an academic who is ten years younger than you and has … Read more

The first draft of “Forecasting and Analytics with ADAM”

After working on this for more than a year, I have finally prepared the first draft of my online monograph “Forecasting and Analytics with ADAM“. This is a monograph on the model that unites ETS, ARIMA and regression and introduces advanced features in univariate modelling, including: ETS in a new State Space form; ARIMA in … Read more

Stochastic coherency in forecast reconciliation

My student (co-supervised with Nikos Kourentzes), Kandrika F. Pritularga has written a paper on “Stochastic coherency in forecast reconciliation”, which has been recently published in International Journal of Production Economics (here it is). This paper contributes to the field of hierarchical forecasting, the main issue of which is that the forecasts produced on different levels … Read more

ISF2021: How to Make Multiplicative ETS Work for You

This year International Symposium on Forecasting was held online, although Centre for Marketing Analytics and Forecasting of Lancaster University had their own hub, where we would come and watch presentations together and even present to the others. I presented on the topic of Multiplicative ETS, based on this chapter of the ADAM textbook and on … Read more

Multi-step Estimators and Shrinkage Effect in Time Series Models – presentation for CEBA

Today I have made a presentation on the topic of “Multi-step Estimators and Shrinkage Effect in Time Series Models” for Center for Econometrics and Business Analytics (CEBA) of St.Petersburg State University. This presentation was based on the paper with the similar name written by Ivan Svetunkov, Nikolaos Kourentzes and Rebecca Killick. In the presentation, I … Read more

After the creation of ADAM: smooth v3.1.0

Since the previous post on “The Creation of ADAM“, I had difficulties finding time to code anything, but I still managed to fix some bugs, implement a couple of features and make changes, important enough to call the next version of package smooth “3.1.0”. Here is what’s new: A new algorithm for ARIMA order selection … Read more

The creation of ADAM – next step in statistical forecasting

Good news everyone! The future of statistical forecasting is finally here :). Have you ever struggled with ETS and needed explanatory variables? Have you ever needed to unite ARIMA and ETS? Have you ever needed to deal with all those zeroes in the data? What about the data with multiple seasonalities? All of this and … Read more

How confident are you? Assessing the uncertainty in forecasting

Introduction Some people think that the main idea of forecasting is in predicting the future as accurately as possible. I have bad news for them. The main idea of forecasting is in decreasing the uncertainty. Think about it: any event that we want to predict has some systematic components \(\mu_t\), which could potentially be captured … Read more