NAME

overview - Project overview The QuantLib project is at this time in beta status.

The following list is a (possibly outdated) overview of the existing code base.

The QuantLib-users and QuantLib-dev mailing lists are the preferred forum for proposals, suggestions and contributions regarding the future development of the library.

Date, calendars, and day count conventions

*
Date class.
*
Weekday, month, frequency, time unit enumerations.
*
Period class (eg. 1y, 30d, 2m, etc.)
*
IMM calculation.
*
More than 30 business calendars.
*
NullCalendar (no holidays) for theoretical calculations.
*
Joint calendars made up as holiday union or intersection of base calendars.
*
Rolling conventions: Preceding, ModifiedPreceding, Following, ModifiedFollowing, MonthEndReference.
*
Schedule class for date stream generation.
*
Day count conventions: Actual360, Actual365Fixed, ActualActual (Bond, ISDA, AFB), 30/360 (US, European, Italian), 1/1.

Math

*
Linear, log-linear, and cubic spline interpolation.
*
Primitive, first and second derivative functions of cubic and linear interpolators.
*
Cubic spline end conditions: first derivative value, second derivative value, not-a-knot.
*
Monotone cubic spline with Hyman non-restrictive filter.
*
Bicubic spline and bilinear interpolations.
*
N-dimensional cubic spline interpolation.
*
Normal and cumulative normal distributions.
*
Inverse cumulative normal distribution: Moro and Acklam approximations.
*
Bivariate cumulative normal distribution.
*
Binomial coefficients, binomial distribution, cumulative binomial distribution, and Peizer-Pratt inversion (method 2.)
*
Chi square and non-central chi square distributions.
*
Beta functions.
*
Poisson and cumulative Poisson distributions.
*
Incomplete gamma functions.
*
Gamma distribution.
*
Factorials.
*
Integration algorithms: segment, trapezoid, mid-point trapezoid, Simpson, Gauss-Kronrod.
*
Error function.
*
General 1-D statistics: mean, variance, standard deviation, skewness, kurtosis, error estimation, min, max.
*
Multi-dimensional (sequence) statistics: all the 1-D methods plus covariance, correlation, L2-discrepancy calculation, etc.
*
Risk measures for Gaussian and empirical distributions: semi-variance, regret, percentile, top percentile, value-at-risk, upside potential, shorfall, average shorfall, expected shortfall.
*
Array and matrix classes for algebra.
*
Singular value decomposition.
*
Eigenvalues, eigenvectors for symmetric matrices.
*
Cholesky decomposition.
*
Schur decomposition.
*
Spectral rank-reduced square root, spectral pseudo-square root.

1-dimensional solvers

*
Bisection, false position, Newton, bounded Newton, Ridder, secant, Brent.

Optimization

*
Conjugate gradient, simplex, steepest descent, line search, Armijo line search, least squares.
*
Constrained (positive, boundary, etc.) and unconstrained optimization

Random-number generation

*
Uniform pseudo-random sequences: Knuth, L'Ecuyer, Mersenne twister.
*
Uniform quasi-random (low-discrepancy) sequences: Halton, Faure, Sobol up to dimension 21,200 (8,129,334 if you really want) with unit, J├Ąckel, Bradley-Fox, and Lemieux-Cieslak-Luttmer initialization numbers.
*
Randomized quasi-random sequences (in progress)
*
Randomized (shifted) low-discrepancy sequences.
*
Primitive polynomials modulo 2 up to dimension 18 (available up to dimension 27)
*
Gaussian random numbers from uniform random numbers using different algorithms: central limit theorem, Box-Muller, inverse cumulative (Moro and Acklam algorithms)

Patterns

*
Bridge, composite, lazy object, observer/observable, singleton, strategy, visitor.

Finite differences

*
Mixed theta, implicit, explicit, and Crank-Nicolson 1-dimensional schemes.
*
Differential operators: $ D_{0} $, $ D_{+} $, $ D_{-} $, $ D_{+}D_{-} $.
*
Shout, Bermudan and American exercises.

Lattices

*
Binomial trees: Cox-Ross-Rubinstein, Jarrow-Rudd, additive equiprobabilities, Trigeorgis, Tian, Leisen-Reimer.
*
Trinomial (interest-rate) tree.
*
Discretized asset.
*
Richardson extrapolation

Monte Carlo

*
One-factor and multi-factor path classes.
*
Path-generator classes: incremental and Brownian-bridge one-factor path generation, incremental multi-factor path generation.
*
General-purpose Monte Carlo model based on traits for path samples.
*
Antithetic variance-reduction technique.
*
Control variate technique.

Pricing engines

*
Analytic Black formula (plus greeks) for different payoffs.
*
Analytic formula for American-style digital options with payoff at expiry.
*
Analytic formula for American-style digital options with payoff at hit.
*
Monte Carlo simulation base engine.
*
Lattice short rate model base engine.
*
Engines for options described by 'vanilla' set of parameters: analytic digital American, analytic discrete-dividend European, analytic European, Barone-Adesi and Whaley approximation for American, Ju approximation for American, binomial (Cox-Ross-Rubinstein, Jarrow-Rudd, additive equiprobabilities, Trigeorgis, Tian, Leisen-Reimer), Bjerksund and Stensland approximation for American, integral European, Merton 76 jump-diffusion, Monte Carlo digital, Monte Carlo European, Bates and Heston models, finite-difference European, Bermudan and American.
*
Engines for options described by 'barrier' set of parameters: analytic down/up in/out, Monte Carlo down/up in/out
*
Engines for Asian options: analytic discrete geometric average-price, analytic continuous geometric average-price, Monte Carlo discrete arithmetic average-price, Monte Carlo discrete geometric average-price.
*
Engines for options described by 'cliquet' set of parameters: analytic, analytic performance.
*
Forward and forward-performance compound engines.
*
Quanto compound engine.
*
Quanto-forward and Quanto-forward-performance compound engines.
*
Basket engine: analytic Stulz engine for max/min on two assets, Monte Carlo engine (in progress).
*
Black model base class for vanilla interest rate derivatives
*
Cap/floor pricing engines: analytic Black model, analytic affine models, tree based engine.
*
Swaption pricing engines: analytic Black model, analytic affine models (Jamshidian), tree based engine.

Pricers

*
Cliquet option
*
Analytic discrete geometric average-price option (European exercise).
*
Analytic discrete geometric average-strike option (European exercise).
*
Monte Carlo cliquet option.
*
Monte Carlo discrete arithmetic average-price option.
*
Monte Carlo discrete arithmetic average-strike option.
*
Monte Carlo Everest option.
*
Monte Carlo Himalaya option.
*
Monte Carlo max basket option.
*
Monte Carlo pagoda option.
*
Monte Carlo forward performance option.

Financial Instruments

*
Instrument base class: npv(), isExpired(), etc.
*
Interest-rate swap.
*
Swaption.
*
Cap/floor.
*
Zero-coupon, fixed-rate coupon, and floating-rate coupon bond.
*
Convertible bond.
*
Stock.
*
One-asset option base class.
*
Asian option.
*
Barrier option.
*
Cliquet option.
*
Forward vanilla option.
*
Quanto vanilla option.
*
Quanto-forward vanilla option.
*
Vanilla option.
*
Multi-asset option base class.
*
Basket option.
*
More...

Yield term structures

*
Term structure common interface.
*
Term structure classes based on discount, zero, or forward underlying description.
*
Term structure based on linear interpolation of zero yields.
*
Term structure based on log-linear interpolation of discounts.
*
Term structure based on constant flat forward.
*
Term structure based on piecewise-constant flat forwards with libor-futures-swap bootstrapping algorithm.
*
Spreaded term structures.
*
Forward-date implied term structure.

Volatility

*
Interface for cap/floor Black volatility term structures (unstable).
*
Interface for swaption Black volatility term structures (unstable).
*
Interface for equity Black volatility term structures based on volatility or variance underlying description: constant, time-dependant curve, time-strike surface, forward date implied term structure.
*
Interface for equity local volatility term structures: constant, time-dependant curve, time-asset level surface (Gatheral's formula).

Short rate models

*
Single factor models: Hull-White, Black-Karasinski, Vasichek (untested), CIR (untested), Extended CIR (untested).
*
Two factor models: G2 (untested).

Test suite

Implemented by means of the Boost unit-test framework. More than 300 automated tests.

Miscellanea

*
Index classes for handling of fixed-income libor indexes (fixings, forecasting, etc.)
*
Cash-flow class.
*
Currency class and enumeration.
*
Money class with automatic exchange-rate capabilities.
*
Output data formatters: long integers, Ordinal numerals, power of two, exponential, fixed digit, sequences, dates, etc.
*
Input data parsers.
*
Error classes and error handling.
*
Exercise classes: European, Bermudan, American
*
Payoff classes: plain, gap, asset-or-nothing, cash-or-nothing
*
Grid classes for handling of equally and unequally spaced grids.
*
History class for handling of historical data.
*
Quote class for mutable data.
*
Null types.
*
User-configurable flag to disable usage of deprecated classes.

Documentation

*
Documentation automatically generated with Doxygen