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finmath-lib | Mathematical Finance Library

 by   finmath Java Version: finmath-lib-4.1.2 License: Apache-2.0

 by   finmath Java Version: finmath-lib-4.1.2 License: Apache-2.0

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kandi X-RAY | finmath-lib Summary

finmath-lib is a Java library. finmath-lib has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub, Maven.
Mathematical Finance Library: Algorithms and methodologies related to mathematical finance.
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kandi-support Support

  • finmath-lib has a low active ecosystem.
  • It has 345 star(s) with 132 fork(s). There are 43 watchers for this library.
  • It had no major release in the last 12 months.
  • There are 10 open issues and 21 have been closed. On average issues are closed in 206 days. There are 1 open pull requests and 0 closed requests.
  • It has a neutral sentiment in the developer community.
  • The latest version of finmath-lib is finmath-lib-4.1.2
finmath-lib Support
Best in #Java
Average in #Java
finmath-lib Support
Best in #Java
Average in #Java

quality kandi Quality

  • finmath-lib has 0 bugs and 0 code smells.
finmath-lib Quality
Best in #Java
Average in #Java
finmath-lib Quality
Best in #Java
Average in #Java

securitySecurity

  • finmath-lib has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
  • finmath-lib code analysis shows 0 unresolved vulnerabilities.
  • There are 0 security hotspots that need review.
finmath-lib Security
Best in #Java
Average in #Java
finmath-lib Security
Best in #Java
Average in #Java

license License

  • finmath-lib is licensed under the Apache-2.0 License. This license is Permissive.
  • Permissive licenses have the least restrictions, and you can use them in most projects.
finmath-lib License
Best in #Java
Average in #Java
finmath-lib License
Best in #Java
Average in #Java

buildReuse

  • finmath-lib releases are available to install and integrate.
  • Deployable package is available in Maven.
  • Build file is available. You can build the component from source.
  • Installation instructions are not available. Examples and code snippets are available.
finmath-lib Reuse
Best in #Java
Average in #Java
finmath-lib Reuse
Best in #Java
Average in #Java
Top functions reviewed by kandi - BETA

kandi has reviewed finmath-lib and discovered the below as its top functions. This is intended to give you an instant insight into finmath-lib implemented functionality, and help decide if they suit your requirements.

  • Returns a random variable with respect to the given variable index .
    • Performs the forward and returns the product derivatives .
      • Calculates the impliedVolatility value for an option .
        • Calculate the Black - Scholes barrier option value .
          • Returns the caplet volatility matrix .
            • Run the algorithm .
              • Returns a clone of the LIBORCovanceModel .
                • Create a clone of this model .
                  • Runs the Optimizer .
                    • Create index curve with the given fixing dates .

                      Get all kandi verified functions for this library.

                      Get all kandi verified functions for this library.

                      finmath-lib Key Features

                      Analytic Formulas

                      Distributions: Normal, Gamma, Non-Central Chi-Squared (some functions are delegated to Apache commons-math).

                      Models: Black Scholes, Bachelier, SABR, ZABR, CEV, etc.

                      General numerical algorithms like

                      Generation of random numbers

                      Optimization (a Levenberg–Marquardt algorithm is provided)

                      Valuation using Fourier transforms / characteristic functions (contributed by Alessandro Gnoatto, Lorenzo Torricelli and others)

                      Black-Scholes model

                      Heston model

                      Bates model

                      Two factor Bates model

                      Merton model

                      Variance Gamma model (contributed and maintained by Alessandro Gnoatto)

                      Finite difference methods (contributed by Ralph Rudd and Jörg Kienitz)

                      Numerical schemes using finite differences

                      Theta-scheme

                      Models

                      Black-Scholes model

                      Constant Elasticity of Variance model

                      Products

                      European option

                      Monte-Carlo simulation of multi-dimensional, multi-factor stochastic differential equations (SDEs)

                      Hull-White Short Rate Model (with time dependent parameters)

                      LIBOR Market Model (Forward Rate Model) (in various forms)

                      Time Homogeneous Forward Rate Model

                      Cross-Currency LIBOR Market Model

                      Black-Scholes type multi-asset model (multi-factor, multi-dimensional geometric Brownian motion)

                      Equity Hybrid LIBOR Market Model

                      Merton Model (as Monte-Carlo Simulation)

                      Heston Model (as Monte-Carlo Simulation)

                      Variance Gamma model (as Monte-Carlo Simulation, contributed and maintained by Alessandro Gnoatto)

                      American Monte-Carlo: Estimation of conditional expectations in a Monte-Carlo framework

                      Stochastic Automatic Differentiation (AAD) (part of the package net.finmath.montecarlo.automaticdifferentiation)

                      Monte-Carlo Simulation on GPGPUs (via Cuda) (requires finmath-lib-cuda-extensions https://github.com/finmath/finmath-lib-cuda-extensions )

                      Dependency injection on numerical algorithms (Monte-Carlo simulations) with custom return type priorities (see http://ssrn.com/abstract=3246127 ).

                      Dividend model for equity option valuation (European and American) (contributed by Andreas Grotz)

                      Analytic valuation via curves and surfaces

                      Multi-Curve valuation of interest rate products (collateralization and funding) (Swaps, FRA).

                      Bonds valuation using bond curves.

                      CDS valuation.

                      Calibration of market data objects like curves (discount and forward curve) or volatility surfaces

                      Rate Curves:

                      Multi-curve interest rate curve calibration (OIS discounting, basis-swaps, cross-currency-swaps).

                      Bond curve calibration using local linear regression (see https://ssrn.com/abstract=3073942 ).

                      Various interpolation methods (linear, cubic spline, harmonic spline, Akima).

                      Various interpolation entities (value, log-value, rate, etc.).

                      Parametric curves like Nelson-Siegel and Nelson-Siegel-Svensson.

                      Volatility Curves and Cubes:

                      SABR smile parameterization.

                      Swaption volatility cubes with SABR parameterization.

                      CMS replication with various annuity mappings.

                      Simulation of interest rate term structure models (LIBOR market model with local and stochastic volatility)

                      LIBOR market model with local and stochastic volatility

                      Time-Homogeneous Forward Rate Model (LIBOR market model)

                      Calibration of the LIBOR market model

                      Cross-Currency LIBOR Market Model

                      Equity Hybrid LIBOR Market Model

                      Local and stochastic volatility models (SABR, ZABR)

                      Valuation of complex derivatives

                      Bermudan options / multi-callables lower bound via regression estimation of the conditional expectation

                      Bermudan options / multi-callables upper bound via dual method

                      Hedge Simulation

                      Margin Valuation Adjustments (MVA) though forward ISDA SIMM simulation (this is currently a separate project at https://github.com/finmath ).

                      Community Discussions

                      No Community Discussions are available at this moment for finmath-lib.Refer to stack overflow page for discussions.

                      No Community Discussions are available at this moment for finmath-lib.Refer to stack overflow page for discussions.

                      Community Discussions, Code Snippets contain sources that include Stack Exchange Network

                      Vulnerabilities

                      No vulnerabilities reported

                      Install finmath-lib

                      You can download it from GitHub, Maven.
                      You can use finmath-lib like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the finmath-lib component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

                      Support

                      For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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