google/tf-quant-finance

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.

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