WaveLSFromer is a research codebase for long-sequence financial time-series
forecasting. It extends the Informer/Stockformer style transformer stack with
stock-specific training objectives, PyTorch Lightning experiment loops,
config-driven model runs, and learnable wavelet front-end components for
low/high frequency feature extraction.
Thanks to
polygon.io for being our financial data provider.