Conventions for writing and maintaining stochastic-rs documentation pages under website/content/docs/. Nine section templates (process / distribution / pricer / calibrator / estimator / copula / AI surrogate / concept / tutorial), frontmatter schema, KaTeX…
Enforces scalability, integration, and compatibility requirements when creating any new module in stochastic-rs — covers stochastic, quant, stats, distributions, copulas, and ai
How to implement a model calibrator in stochastic-rs (BSM, Heston, SABR, SVI, …). Invoke when adding a new calibration routine that fits a model to market option prices or implied vols.
How to expose first- and second-order Greeks in stochastic-rs — an inherent greeks(s, k, r, q, tau, option_type) aggregator on a pricer, or the no-argument GreeksExt trait for the two Monte Carlo Malliavin estimators. Invoke when adding a pricer that needs…
Maintenance and extension rules for stochastic-rs Python (PyO3) bindings — invoke when adding/updating distributions, processes, pricers, calibrators, or estimators that need Python exposure
How to add a bivariate copula to stochastic-rs-copulas. Invoke when implementing Clayton, Frank, Gumbel, Joe, Plackett, FGM-style families, or any 2-d Archimedean / extreme-value copula.
How to add a univariate distribution to stochastic-rs-distributions. Covers SimdXxx struct, sampling pattern (transformation / ziggurat / rejection / inversion), DistributionExt closed-form moments/pdf/cdf/cf, KS-test, and the py_distribution! macro.
Conventions for adding / propagating Cargo features across the stochastic-rs workspace. Invoke when adding a new optional dependency, gating a sub-module, or debugging "feature X enabled in crate A but not B" build errors.