awesome-repositories.com
Blog
awesome-repositories.com

Descubre los mejores repositorios open-source con nuestra búsqueda potenciada por IA.

ExplorarBúsquedas curadasAlternativas open-sourceSoftware autohospedableBlogMapa del sitio
ProyectoAcerca deCómo clasificamosPrensaServidor MCP
Aviso legalPrivacidadTérminos
© 2026 Bringes Technology SRL·VAT RO45896025·hello@awesome-repositories.com
·
google avatar

google/tf-quant-finance

0
View on GitHub↗
5,404 estrellas·688 forks·Python·Apache-2.0·11 vistas

Tf Quant Finance

Esta es una librería de finanzas cuantitativas construida sobre TensorFlow para ingeniería financiera, valoración de activos y gestión de riesgos. Sirve como un motor de valoración de derivados financieros, una herramienta de calibración de modelos y una librería matemática acelerada por hardware para tareas numéricas.

La librería proporciona capacidades especializadas para valorar activos financieros utilizando modelos estándar y lógica de opciones americanas, así como para calibrar modelos de valoración con datos de mercado a través de volatilidad local. Incluye herramientas para construir curvas de rendimiento mediante algoritmos de bootstrapping e interpolación convexa monótona.

El framework cubre una amplia gama de tareas de modelado cuantitativo, incluyendo la simulación de procesos estocásticos, el muestreo de cópulas para modelar estructuras de dependencia y la resolución de ecuaciones diferenciales ordinarias y parciales. También proporciona herramientas de análisis numérico para la búsqueda de raíces y la optimización matemática.

Features

  • Quantitative Finance & Trading - A comprehensive high-performance library for financial engineering, asset pricing, and risk management built on TensorFlow.
  • Automatic Differentiation Engines - Provides a computational graph engine for calculating precise gradients used in model calibration and optimization.
  • TensorFlow Graph Execution - Executes mathematical operations via TensorFlow computational graphs to leverage hardware acceleration.
  • Diffusion Path Generators - Generates sample paths for financial variables using diffusion generators to model market uncertainty.
  • Derivative Pricing Models - Implements quantitative models for computing option values and managing financial derivatives.
  • Model Calibration Frameworks - Fits model parameters to real-world market data using local volatility and optimization algorithms.
  • Asset Price Path Simulators - Generates sample paths for financial assets using diffusion-based stochastic process simulators.
  • Volatility Calibration - Fits pricing model parameters to market data using local volatility and calibration algorithms.
  • Model Calibration Algorithms - Implements algorithms to fit pricing model parameters to market data using local volatility and bootstrapping.
  • Vectorized Stochastic Simulations - Simulates multiple stochastic process trajectories simultaneously using vectorized tensor operations on GPUs and CPUs.
  • Copula Models - Uses copula-based sampling to generate correlated random variables for dependency modeling.
  • Differential Equation Solvers - Implements numerical solvers for ordinary and partial differential equations using multi-dimensional methods.
  • General PDE Solvers - Provides a framework for solving ordinary and partial differential equations using multi-dimensional numerical methods.
  • Hardware-Accelerated Numerical Libraries - Offers hardware-accelerated numerical tools for root finding and optimization using GPUs and automatic differentiation.
  • Mathematical Optimization Solving - Provides numerical solvers for mathematical optimization, root finding, and interpolation tasks.
  • Numerical Integration Tools - Computes multi-dimensional definite integrals and numerical approximations to solve differential equations.
  • Financial Analysis Tools - Provides tools for complex financial modeling, including solving differential equations and root finding.
  • Hardware-Accelerated Implementations - Offloads iterative numerical searches for function zeros to parallel processing hardware to accelerate pricing.
  • Yield Curve Construction - Implements bootstrapping algorithms and monotone convex interpolation to construct financial yield curves.
  • AI and Machine Learning - High-performance TensorFlow library for quantitative finance.
  • Financial Analysis - High-performance quantitative finance using TensorFlow.
  • Financial Analytics - Quantitative finance tools built on TensorFlow.
  • Financial Analytics Tools - High-performance library for quantitative finance.
  • Financial Instruments and Pricing - High-performance library for quantitative finance using machine learning frameworks.

Historial de estrellas

Gráfico del historial de estrellas de google/tf-quant-financeGráfico del historial de estrellas de google/tf-quant-finance

Búsqueda con IA

Explora más repositorios increíbles

Describe lo que necesitas en lenguaje sencillo: la IA clasifica miles de proyectos open-source curados por relevancia.

Start searching with AI

Alternativas open-source a Tf Quant Finance

Proyectos open-source similares, clasificados según cuántas características comparten con Tf Quant Finance.
  • fincept-corporation/finceptterminalAvatar de Fincept-Corporation

    Fincept-Corporation/FinceptTerminal

    26,900Ver en GitHub↗

    FinceptTerminal is a quantitative finance platform and financial engineering library designed for asset valuation, risk management, and fixed-income analytics. It provides a comprehensive suite for algorithmic trading and investment strategy automation, integrating specialized language model agents and node-based workflows to automate market research and alpha generation. The project distinguishes itself with a dedicated game theory analysis engine for calculating Nash equilibria and simulating strategic interactions in competitive markets. It also features a specialized credit risk modeling

    C++bloomberg-terminalcontributions-welcomefinance
    Ver en GitHub↗26,900
  • cantaro86/financial-models-numerical-methodsAvatar de cantaro86

    cantaro86/Financial-Models-Numerical-Methods

    6,831Ver en GitHub↗

    This project is a quantitative finance library providing implementations of numerical methods for financial engineering. It focuses on derivative pricing, portfolio optimization, stochastic simulation, and volatility calibration. The library includes tools for calculating option values using Monte Carlo simulations, binomial trees, and Fourier inversion. It provides a framework for fitting volatility smiles to market data and a simulation engine for generating asset price paths via geometric Brownian motion and jump-diffusion models. The codebase covers broader numerical analysis capabilitie

    Jupyter Notebookamerican-optionsbrownian-motioneconometrics
    Ver en GitHub↗6,831
  • domokane/financepyAvatar de domokane

    domokane/FinancePy

    3,004Ver en GitHub↗

    A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives.

    Jupyter Notebook
    Ver en GitHub↗3,004
  • pmorissette/ffnAvatar de pmorissette

    pmorissette/ffn

    2,607Ver en GitHub↗

    ffn - a financial function library for Python

    Python
    Ver en GitHub↗2,607
Ver las 30 alternativas a Tf Quant Finance→

Preguntas frecuentes

¿Qué hace google/tf-quant-finance?

Esta es una librería de finanzas cuantitativas construida sobre TensorFlow para ingeniería financiera, valoración de activos y gestión de riesgos. Sirve como un motor de valoración de derivados financieros, una herramienta de calibración de modelos y una librería matemática acelerada por hardware para tareas numéricas.

¿Cuáles son las características principales de google/tf-quant-finance?

Las características principales de google/tf-quant-finance son: Quantitative Finance & Trading, Automatic Differentiation Engines, TensorFlow Graph Execution, Diffusion Path Generators, Derivative Pricing Models, Model Calibration Frameworks, Asset Price Path Simulators, Volatility Calibration.

¿Qué alternativas de código abierto existen para google/tf-quant-finance?

Las alternativas de código abierto para google/tf-quant-finance incluyen: fincept-corporation/finceptterminal — FinceptTerminal is a quantitative finance platform and financial engineering library designed for asset valuation,… cantaro86/financial-models-numerical-methods — This project is a quantitative finance library providing implementations of numerical methods for financial… pmorissette/ffn — ffn - a financial function library for Python. domokane/financepy — A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including… wilsonfreitas/awesome-quant — Awesome-quant is a curated directory of open-source software libraries and tools designed for quantitative finance,… jerbouma/fundamentalanalysis — FundamentalAnalysis is a comprehensive financial analysis library, quantitative finance framework, and macroeconomic…