Module com.quantfinlib

module com.quantfinlib

Quant-Finance-Library, stable tier: pricing, rates, credit, market risk, alpha research, backtesting and execution analytics.

Every exported package carries the stable-tier promise of docs/STABILITY.md: no binary-incompatible change within a major version, checked by japicmp. Since 4.0 the module requires nothing but java.base (and JSpecify at compile time only, requires static): file and HTTP I/O is in com.quantfinlib.io, the strategy DSL in com.quantfinlib.research, and the reference-tier trading lane in com.quantfinlib.lowlatency. Each of those requires this module transitively; see docs/MIGRATION_4.0.md.

com.quantfinlib.internal holds shared implementation helpers and is exported only to the low-latency module; it is not API.

Packages

Exports

Package	Description
com.quantfinlib.alpha	Cross-sectional alpha research: signal generation, evaluation, validation, execution-aware backtesting, portfolio construction and reporting, each a separate step.
com.quantfinlib.backtest	Bar-based backtesting engines, execution models and performance analytics.
com.quantfinlib.backtest.portfolio	Multi-asset portfolio backtesting with point-in-time universes and financing.
com.quantfinlib.backtest.validation	Validation tools that test a backtest for overfitting.
com.quantfinlib.commodities	Commodity futures curves: roll yield, implied carry and curve shape.
com.quantfinlib.core	Core bar and bar-series types used by every analytics package.
com.quantfinlib.crb	The central risk book: one netted view of the firm's risk across desks and products, with internalization, routing and hedging.
com.quantfinlib.credit	Credit curves, CDS pricing and credit spreads.
com.quantfinlib.data	Loading, recording, replaying and aligning market data.
com.quantfinlib.execution	Order routing, execution algorithms and the venue models they learn from.
com.quantfinlib.fx	FX market conventions and instruments, from spot dates to NDFs.
com.quantfinlib.hedging	Hedging algorithms across asset classes.
com.quantfinlib.indicators	Technical indicators in batch and streaming form.
com.quantfinlib.markets	Index construction and private-market performance analytics.
com.quantfinlib.microstructure	Market microstructure analytics: impact, liquidity, order-flow signals and intraday curves.
com.quantfinlib.ml	Statistical learning models for market data, in plain Java.
com.quantfinlib.optimization	Portfolio optimisers and the solvers behind them.
com.quantfinlib.persist	Persistence of learned intraday state across trading days.
com.quantfinlib.pricing	Option and derivatives pricing models, implied volatility and volatility surfaces.
com.quantfinlib.rates	Fixed income: curves, bonds, swaps, day counts and calendars, with market conventions.
com.quantfinlib.regulatory	Benchmark-fix and regulatory execution metrics.
com.quantfinlib.risk	Risk measurement, decomposition, limits and model validation.
com.quantfinlib.screener	Stock screening by technical and fundamental filters, with ranking and CSV export.
com.quantfinlib.simulation	Monte Carlo simulation of portfolio and multi-asset price paths.
com.quantfinlib.stats	Canonical descriptive statistics: mean, sample and population variance, quantiles with a named Hyndman-Fan definition, median, covariance, Pearson correlation, skewness, kurtosis and midranks (Stats); and, since 2.4.0, the numerical routines that used to live in util.MathUtils (removed in 3.0): SpecialFunctions (normal, log-gamma, incomplete beta, Student-t), LinearAlgebra (dot products, Cholesky, solve, inverse) and Numerics (clamp, NaN arrays, decay factor, pair sort).
com.quantfinlib.volatility	Volatility models: EWMA, GARCH-family, HAR-RV, a model-free volatility index and a systematic/idiosyncratic decomposition.