API Reference

This section is generated from the Python docstrings.

nn_option_pricing.black_scholes	Analytical Black-Scholes pricing utilities.
nn_option_pricing.config	Configuration objects for reproducible experiments.
nn_option_pricing.dataset	Synthetic dataset generation for the supervised pricing task.
nn_option_pricing.evaluation	Evaluation metrics and persistence utilities.
nn_option_pricing.model	PyTorch model definitions for option pricing.
nn_option_pricing.monte_carlo	Monte Carlo estimators for European option pricing.
nn_option_pricing.noise	Controlled target-noise utilities for robustness experiments.
nn_option_pricing.noisy_experiment	Noisy Black-Scholes target robustness experiment.
nn_option_pricing.noisy_svr_experiment	Support Vector Regression benchmark with noisy Black-Scholes targets.
nn_option_pricing.pipeline	End-to-end experiment orchestration.
nn_option_pricing.plots	Plotting utilities for experiment diagnostics.
nn_option_pricing.svr	Support Vector Regression benchmark utilities.
nn_option_pricing.training	Training and inference utilities for the pricing neural network.