Lab
Open implementations
Reference Python, Rust, and R code for Daru Finance’s public M-models and supporting analyses. These are the implementations behind articles published on this site — intentionally minimal, intentionally readable, intentionally reproducible.
Eigenspectrum of the strategy correlation matrix
Marchenko–Pastur and parallel-analysis eigenspectrum of strategy correlation matrices. Reference implementation of the firm's M/01 model.
Sparse signal detection with FDR control
Higher Criticism plus Model-X knockoffs for FDR-controlled strategy selection. Reference implementation of the firm's M/02 model.
Persistence barcodes on strategy structure
H0 persistence barcode under correlation-distance Vietoris–Rips on strategy populations. Reference implementation of the firm's M/03 model.
Peaks-over-threshold and pairwise tail-coupling
Peaks-over-threshold GPD fits and pairwise tail-coupling χ on cross-asset returns. Reference implementation of the firm's M/04 model.
Decomposing the IS-OOS Sharpe gap
Variance decomposition of the in-sample / out-of-sample Sharpe gap into selection bias, parameter-choice noise, and residual skill across 10 deep-WFO crypto assets.
Does in-sample smoothness predict out-of-sample skill?
Pre-registered empirical test of whether in-sample Sharpe-surface smoothness under a fixed five-perturbation suite predicts out-of-sample skill across SOL / DOGE / BTC walk-forward partitions.
PCA + UMAP geometry of the strategy population
PCA + UMAP embedding of large strategy populations from a 90-feature metric vector, with connectivity-based separation of robust vs fragile strategies.
Hidden-Markov regime segmentation
Gaussian HMM regime segmentation on (logret, volatility, trend) features with K selected by BIC; cross-asset 4-state preference across crypto majors.
Universe-saturation of minimum-variance portfolios
Universe-saturation analysis for minimum-variance portfolios drawn from large strategy pools, comparing Ledoit–Wolf shrinkage, Huber-style robust, and sample covariance estimators.
Sharpe density and (μ, σ, t) population scatter
Population-level Sharpe density and (mean, std, t) scatter over a strategy universe. Supporting library for empirical analyses.
Cross-asset rolling correlation cube
Cross-asset sample correlation cube over a 9-asset universe. Supporting library for population-level analyses.
The signal is collective
Reproducible synthetic demos behind the article 'The signal is collective'.
Frameworks (full backtester implementations) and the Monte-Carlo paper reproducibility package are intentionally excluded from this list — they live in their own dedicated places. See github.com/DaruFinance for the full repository index.