ql-overview (3) - Linux Manuals
ql-overview: Project overview
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The following list is a (possibly outdated) overview of the existing code base.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
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- Date class.
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- Weekday, month, frequency, time unit enumerations.
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- Period class (eg. 1y, 30d, 2m, etc.)
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- IMM calculation.
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- More than 30 business calendars.
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- NullCalendar (no holidays) for theoretical calculations.
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- Joint calendars made up as holiday union or intersection of base calendars.
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- Rolling conventions: Preceding, ModifiedPreceding, Following, ModifiedFollowing, MonthEndReference.
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- Schedule class for date stream generation.
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- Day count conventions: Actual360, Actual365Fixed, ActualActual (Bond, ISDA, AFB), 30/360 (US, European, Italian), 1/1.
Math
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- Linear, log-linear, and cubic spline interpolation.
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- Primitive, first and second derivative functions of cubic and linear interpolators.
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- Cubic spline end conditions: first derivative value, second derivative value, not-a-knot.
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- Monotone cubic spline with Hyman non-restrictive filter.
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- Bicubic spline and bilinear interpolations.
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- N-dimensional cubic spline interpolation.
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- Normal and cumulative normal distributions.
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- Inverse cumulative normal distribution: Moro and Acklam approximations.
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- Bivariate cumulative normal distribution.
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- Binomial coefficients, binomial distribution, cumulative binomial distribution, and Peizer-Pratt inversion (method 2.)
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- Chi square and non-central chi square distributions.
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- Beta functions.
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- Poisson and cumulative Poisson distributions.
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- Incomplete gamma functions.
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- Gamma distribution.
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- Factorials.
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- Integration algorithms: segment, trapezoid, mid-point trapezoid, Simpson, Gauss-Kronrod.
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- Error function.
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- General 1-D statistics: mean, variance, standard deviation, skewness, kurtosis, error estimation, min, max.
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- Multi-dimensional (sequence) statistics: all the 1-D methods plus covariance, correlation, L2-discrepancy calculation, etc.
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- Risk measures for Gaussian and empirical distributions: semi-variance, regret, percentile, top percentile, value-at-risk, upside potential, shorfall, average shorfall, expected shortfall.
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- Array and matrix classes for algebra.
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- Singular value decomposition.
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- Eigenvalues, eigenvectors for symmetric matrices.
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- Cholesky decomposition.
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- Schur decomposition.
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- Spectral rank-reduced square root, spectral pseudo-square root.
1-dimensional solvers
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- Bisection, false position, Newton, bounded Newton, Ridder, secant, Brent.
Optimization
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- Conjugate gradient, simplex, steepest descent, line search, Armijo line search, least squares.
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- Constrained (positive, boundary, etc.) and unconstrained optimization
Random-number generation
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- Uniform pseudo-random sequences: Knuth, L'Ecuyer, Mersenne twister.
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- Uniform quasi-random (low-discrepancy) sequences: Halton, Faure, Sobol up to dimension 21,200 (8,129,334 if you really want) with unit, Jäckel, Bradley-Fox, and Lemieux-Cieslak-Luttmer initialization numbers.
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- Randomized quasi-random sequences (in progress)
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- Randomized (shifted) low-discrepancy sequences.
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- Primitive polynomials modulo 2 up to dimension 18 (available up to dimension 27)
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- Gaussian random numbers from uniform random numbers using different algorithms: central limit theorem, Box-Muller, inverse cumulative (Moro and Acklam algorithms)
Patterns
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- Bridge, composite, lazy object, observer/observable, singleton, strategy, visitor.
Finite differences
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- Mixed theta, implicit, explicit, and Crank-Nicolson 1-dimensional schemes.
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- Differential operators: $ D_{0} $, $ D_{+} $, $ D_{-} $, $ D_{+}D_{-} $.
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- Shout, Bermudan and American exercises.
Lattices
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- Binomial trees: Cox-Ross-Rubinstein, Jarrow-Rudd, additive equiprobabilities, Trigeorgis, Tian, Leisen-Reimer.
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- Trinomial (interest-rate) tree.
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- Discretized asset.
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- Richardson extrapolation
Monte Carlo
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- One-factor and multi-factor path classes.
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- Path-generator classes: incremental and Brownian-bridge one-factor path generation, incremental multi-factor path generation.
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- General-purpose Monte Carlo model based on traits for path samples.
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- Antithetic variance-reduction technique.
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- Control variate technique.
Pricing engines
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- Analytic Black formula (plus greeks) for different payoffs.
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- Analytic formula for American-style digital options with payoff at expiry.
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- Analytic formula for American-style digital options with payoff at hit.
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- Monte Carlo simulation base engine.
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- Lattice short rate model base engine.
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- 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.
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- Engines for options described by 'barrier' set of parameters: analytic down/up in/out, Monte Carlo down/up in/out
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- 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.
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- Engines for options described by 'cliquet' set of parameters: analytic, analytic performance.
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- Forward and forward-performance compound engines.
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- Quanto compound engine.
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- Quanto-forward and Quanto-forward-performance compound engines.
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- Basket engine: analytic Stulz engine for max/min on two assets, Monte Carlo engine (in progress).
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- Black model base class for vanilla interest rate derivatives
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- Cap/floor pricing engines: analytic Black model, analytic affine models, tree based engine.
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- Swaption pricing engines: analytic Black model, analytic affine models (Jamshidian), tree based engine.
Pricers
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- Cliquet option
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- Analytic discrete geometric average-price option (European exercise).
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- Analytic discrete geometric average-strike option (European exercise).
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- Monte Carlo cliquet option.
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- Monte Carlo discrete arithmetic average-price option.
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- Monte Carlo discrete arithmetic average-strike option.
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- Monte Carlo Everest option.
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- Monte Carlo Himalaya option.
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- Monte Carlo max basket option.
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- Monte Carlo pagoda option.
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- Monte Carlo forward performance option.
Financial Instruments
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- Instrument base class: npv(), isExpired(), etc.
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- Interest-rate swap.
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- Swaption.
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- Cap/floor.
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- Zero-coupon, fixed-rate coupon, and floating-rate coupon bond.
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- Convertible bond.
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- Stock.
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- One-asset option base class.
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- Asian option.
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- Barrier option.
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- Cliquet option.
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- Forward vanilla option.
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- Quanto vanilla option.
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- Quanto-forward vanilla option.
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- Vanilla option.
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- Multi-asset option base class.
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- Basket option.
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- More...
Yield term structures
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- Term structure common interface.
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- Term structure classes based on discount, zero, or forward underlying description.
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- Term structure based on linear interpolation of zero yields.
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- Term structure based on log-linear interpolation of discounts.
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- Term structure based on constant flat forward.
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- Term structure based on piecewise-constant flat forwards with libor-futures-swap bootstrapping algorithm.
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- Spreaded term structures.
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- Forward-date implied term structure.
Volatility
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- Interface for cap/floor Black volatility term structures (unstable).
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- Interface for swaption Black volatility term structures (unstable).
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- 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.
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- Interface for equity local volatility term structures: constant, time-dependant curve, time-asset level surface (Gatheral's formula).
Short rate models
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- Single factor models: Hull-White, Black-Karasinski, Vasichek (untested), CIR (untested), Extended CIR (untested).
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- Two factor models: G2 (untested).
Test suite
Implemented by means of the Boost unit-test framework. More than 300 automated tests.
Miscellanea
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- Index classes for handling of fixed-income libor indexes (fixings, forecasting, etc.)
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- Cash-flow class.
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- Currency class and enumeration.
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- Money class with automatic exchange-rate capabilities.
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- Output data formatters: long integers, Ordinal numerals, power of two, exponential, fixed digit, sequences, dates, etc.
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- Input data parsers.
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- Error classes and error handling.
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- Exercise classes: European, Bermudan, American
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- Payoff classes: plain, gap, asset-or-nothing, cash-or-nothing
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- Grid classes for handling of equally and unequally spaced grids.
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- History class for handling of historical data.
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- Quote class for mutable data.
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- Null types.
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- User-configurable flag to disable usage of deprecated classes.
Documentation
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- Documentation automatically generated with Doxygen