From 8831d7e765823a4044a86c8fa8fba77b5ea72b5a Mon Sep 17 00:00:00 2001 From: Accursed Galaxy | Robin <56959183+AccursedGalaxy@users.noreply.github.com> Date: Sat, 30 May 2026 15:43:23 +0200 Subject: [PATCH] Add wasserstein-btc to Time Series Analysis (#394) Distributional crypto-return forecasting via geodesic extrapolation on the 2-Wasserstein manifold, with walk-forward CRPS evaluation against both classical and named-econometric baseline panels. Co-authored-by: Claude Opus 4.7 (1M context) --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index 1ae389c..695a5f4 100644 --- a/README.md +++ b/README.md @@ -351,6 +351,7 @@ A curated list of insanely awesome libraries, packages and resources for Quants - [gluon-ts](https://github.com/awslabs/gluon-ts) - `Python` - vProbabilistic time series modeling in Python. - [OmniOracle](https://github.com/cesabici-bit/omni-oracle) - `Python` - Automatic discovery of non-trivial statistical relationships across 500+ time series from FRED, World Bank, EIA, and NOAA using mutual information screening, lagged MI directional testing, and FDR correction. - [functime](https://github.com/functime-org/functime) - `Python` - Time-series machine learning at scale. Built with Polars for embarrassingly parallel feature extraction and forecasts on panel data. +- [wasserstein-btc](https://github.com/AccursedGalaxy/wasserstein-btc) - `Python` - Distributional forecasting of crypto log-returns by tangent-space geodesic extrapolation on the 2-Wasserstein manifold (quantile-function coordinates). Walk-forward CRPS evaluation over 6.75 years across 4 assets × 3 horizons; benchmarked against classical baselines (Static / RW-Drift / HS-Bootstrap / GARCH-N / GARCH-t / GJR-GARCH-t) and a named-econometric panel (HAR-RV, CAViaR-SAV, Markov-switching Normal, FIGARCH, AR(1) Stochastic Volatility, bivariate VAR+GARCH). [Live dashboard](https://accursedgalaxy.github.io/wasserstein-btc/). - [tseries](https://cran.r-project.org/web/packages/tseries/index.html) - `R` - Time Series Analysis and Computational Finance. - [fGarch](https://cran.r-project.org/web/packages/fGarch/index.html) - `R` - Rmetrics - Autoregressive Conditional Heteroskedastic Modelling. - [timeSeries](https://cran.r-project.org/web/packages/timeSeries/index.html) - `R` - Rmetrics - Financial Time Series Objects.