Collection of notebooks about quantitative finance, with interactive python code.
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Updated
Feb 26, 2024 - Jupyter Notebook
Collection of notebooks about quantitative finance, with interactive python code.
Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.
NMA Computational Neuroscience course
Gaussian processes in TensorFlow
Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
Rust library for quantitative finance.
Generate realizations of stochastic processes in python.
Python framework for short-term ensemble prediction systems.
Solvers for stochastic differential equations which connect with the scientific machine learning (SciML) ecosystem
Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
EasyTPP: Towards Open Benchmarking Temporal Point Processes
Language modeling via stochastic processes. Oral @ ICLR 2022.
Economic scenario generator for python: simulate stocks, interest rates, and other stochastic processes.
Multifractal Detrended Fluctuation Analysis in Python
📦 Python library for Stochastic Processes Simulation and Visualisation
R package for statistical inference using partially observed Markov processes
Implement pricing analytics and Monte Carlo simulations for stochastic volatility models including log-normal SV model, Heston
Matlab Toolbox for the Numerical Solution of Stochastic Differential Equations
A library of noise processes for stochastic systems like stochastic differential equations (SDEs) and other systems that are present in scientific machine learning (SciML)
JumpDiff: Non-parametric estimator for Jump-diffusion processes for Python
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