Hi everyone,
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.
--- This is the launch of our core engine so 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.
