Ivan Svetunkov 
If you have taken a course on forecasting or time series analysis, you’ve probably heard of ARIMA and the Box–Jenkins methodology. In my opinion, this methodology has a fundamental flaw and should not be used in practice. Here’s why. When Box and Jenkins wrote their book back in the 1960s, it was a very different … Read more
It was a pleasure to attend the 5th IMA and OR Society Conference at Aston University, Birmingham, and to present my research with Anna Sroginis on model-based demand classification. A great crowd of people from universities across the UK, along with several esteemed international colleagues. The event was very well organised – thanks to Aris … Read more
Everything is random! Your data, your model, its parameter estimates, the forecasts it produces, and even the minimum of the loss function you used. There is no such thing as a “deterministic” forecast – everything is stochastic! Whenever you work with data, you are working with a sample from a population. In some cases, this … Read more
For the last year, Anna Sroginis and I have been working on a paper, trying to modernise demand classification schemes and make them useful in the brave new era of machine learning. We have finally wrapped it up and submitted it to a peer-reviewed journal. But the temptation to share was too strong, so we … Read more
There are many different issues with capturing seasonality in time series. In this short post, I’d like to discuss one of the most annoying ones. I’m talking about the seasonal pattern that shifts over time. What I mean is that, for example, instead of having the standard number of observations in the cycle (e.g., 24 … Read more
In forecasting, the term seasonality doesn’t always mean what you think it does. It encompasses more than just patterns repeating from one season to the next. In fact, seasonality covers a wide range of periodic behaviors, and can have some issues associated with the naming conventions. Should we discuss? First things first: when we say … Read more
I presented our current work with Anna Sroginis during my visit of IÉSEG School of Management, Lille, France last week. It was great to see my colleague and friend Sarah Van der Auweraer, and I enjoyed the discussion we had with people in her group related to forecasting and intermittent demand. You can see details … Read more
If someone tells you that method X solves all problems and is the best one ever, they are either lying intentionally or do not fully understand what they are talking about. There is no such thing as “the best approach for everything”. Let me explain. Consider two products sold by retailers: ice cream and bread. … Read more
If you follow certain influencers on LinkedIn, you might have come across the term “forecasting academia” (or “applied forecasting academia”). If you’re not familiar with the field, you might not know who this refers to, so I decided to write a short post about it. “Forecasting academia” refers to researchers working in the field of … Read more
Image above depicts a fashion model making a presentation about a forecasting method. I like the forecast for the final period in that image… Over the last few years, I’ve seen phrases like “LightGBM model” or “Neural Network model” on LinkedIn many times, and the statistician in me shivers every time. So, I figured it’s … Read more