All Packages
Package Summary
Package
Description
Cross-sectional alpha research: signal generation, evaluation,
validation, execution-aware backtesting, portfolio construction and
reporting, each a separate step.
Bar-based backtesting engines, execution models and performance analytics.
Multi-asset portfolio backtesting with point-in-time universes and
financing.
Validation tools that test a backtest for overfitting.
Commodity futures curves: roll yield, implied carry and curve shape.
Core bar and bar-series types used by every analytics package.
The central risk book: one netted view of the firm's risk across desks
and products, with internalization, routing and hedging.
Credit curves, CDS pricing and credit spreads.
Loading, recording, replaying and aligning market data.
Order routing, execution algorithms and the venue models they learn
from.
FX market conventions and instruments, from spot dates to NDFs.
Hedging algorithms across asset classes.
Technical indicators in batch and streaming form.
Implementation helpers shared across packages:
ValueArrays
(defensive copies for result types) and the Immutable marker that
SpotBugs reads.Index construction and private-market performance analytics.
Market microstructure analytics: impact, liquidity, order-flow signals
and intraday curves.
Statistical learning models for market data, in plain Java.
Portfolio optimisers and the solvers behind them.
Persistence of learned intraday state across trading days.
Option and derivatives pricing models, implied volatility and volatility
surfaces.
Fixed income: curves, bonds, swaps, day counts and calendars, with
market conventions.
Benchmark-fix and regulatory execution metrics.
Risk measurement, decomposition, limits and model validation.
Stock screening by technical and fundamental filters, with ranking and
CSV export.
Monte Carlo simulation of portfolio and multi-asset price paths.
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).Volatility models: EWMA, GARCH-family, HAR-RV, a model-free volatility
index and a systematic/idiosyncratic decomposition.