This library provides high-performance components leveraging the hardware acceleration support and automatic differentiation of TensorFlow. The library will provide TensorFlow support for foundational mathematical methods, mid-level methods, and specific pricing models. The coverage is being expanded over the next few months.
The library is structured along three tiers:
- Foundational methods. Core mathematical methods – optimisation, interpolation, root finders, linear algebra, random and quasi-random number generation, etc.
- Mid-level methods. ODE & PDE solvers, Ito process framework, Diffusion Path Generators, Copula samplers etc.
- Pricing methods and other quant finance specific utilities. Specific Pricing models (e.g Local Vol (LV), Stochastic Vol (SV), Stochastic Local Vol (SLV), Hull-White (HW)) and their calibration. Rate curve building, payoff descriptions and schedule generation.
We aim for the library components to be easily accessible at each level. Each layer will be accompanied by many examples which can be run independently of higher level components.