We have been dealing for a while with the underperformance of Time-Series Machine Learning models (mostly due to regime changes), and haven't found the right library to complete Adaptive Backtesting before the heat-death of the universe.

We ended up writing a library from scratch, that comes with an order of magnitude speed-up, called Fold.

--- As this is the launch of the core engine of our Forecasting Suite we would love to get some feedback on Fold (https://github.com/dream-faster/fold)!

We’ll be here and happy to answer any questions.