Hello, Team! Thank you for letting us use your great tools. High level question: for a case where we have lots of series (in our case it's monthly ARR for different customers) do you recommend that we try multiple series handling and or use hierarchical methods in some of your packages? To be more clear are there any pages that document the theory and more detailed use of forecasting multiple series? Thank you all in advance!

Hi @David Wheeler Without looking at your data, it’s hard to say what will work best. I recommend trying both. In my experience working with large retailers, if you have a clear hierarchical structure, it usually helps using information from different levels of the hierarchy (for example, client-store and store-region). Here’s a tutorial for the hierarchical forecast Since you seem to have a large number of time series, I strongly recommend using the multi-series handling of TimeGPT since it will allow you to do the forecasts for all the series in one call. For the time being, the tutorial that you mentioned is what we have.

Awesome. Thank you, @Mariana Menchero! I really appreciate this and will give it a try!

sure, we're happy to help