87 Open Source Monte Carlo Simulation Software Projects
Free and open source monte carlo simulation code projects including engines, APIs, generators, and tools.
Companion code for "Modern Computational Finance: AAD and Parallel Simulations" (Antoine Savine, Wiley, 2018)
UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical systems.
A continuous-time hybridization-expansion Monte Carlo code for calculating n-particle Green's functions of the Anderson impurity model and within dynamical mean-field theory.
Python-based portfolio / stock widget which sources data from Yahoo Finance and calculates different types of Value-at-Risk (VaR) metrics and many other (ex-post) risk/return characteristics both on an individual stock and portfolio-basis, stand-alone and vs. a benchmark of choice (constructed with wxPython)
Tutorials about Quantitative Finance in Python and QuantLib: Pricing, xVAs, Hedging, Portfolio Optimisation, Machine Learning and Deep Learning
Applying Data Science Using Sas14 ⭐
Companion and Download Site for the SAS Press Book "Applying Data Science - Business Case Studies Using SAS"
Code for "DeepDRR: A Catalyst for Machine Learning in Fluoroscopy-guided Procedures". https://arxiv.org/abs/1803.08606
A Power BI template that provides easy to understand, actionable flow metrics and predictive analytics for your agile teams using Azure DevOps, Azure DevOps Server and/or TFS.
Spring 2018 Monte Carlo project at ENSAE: simulation of self-avoiding random walks
CRPropa is a public astrophysical simulation framework for propagating extraterrestrial ultra-high energy particles. https://crpropa.github.io/CRPropa3/
Rust library for setting up and running distributed Monte-Carlo statistical simulations. Designed primarily for lattice QCD.
Option Pricing16 ⭐
Implementation of Monte Carlo simulations and Black-Scholes method to calculate prices for American and European options respectively.
Julia and Python programs that implement some of the tools described in my book "Stochastic Methods in Asset Pricing" (SMAP), MIT Press 2017 (e.g., the method for computing the price of American call options and the construction of the early exercise premium in the Black-Scholes-Merton framework from section 18.4 in SMAP).
An R package for symbolic and numerical computations on scalar and multivariate systems of stochastic differential equations (SDEs). It provides users with a wide range of tools to simulate, estimate, analyze, and visualize the dynamics of these systems in both forms Itô and Stratonovich <doi:10.18637/jss.v096.i02>.
An example project that predicts risk of credit card default using a Logistic Regression classifier and a 30,000 sample dataset.
Taa Pg23 ⭐
Usage of policy gradient reinforcement learning to solve portfolio optimization problems (Tactical Asset Allocation).
Tools for uncertainty propagation and measurement unit conversion — Outils pour la propagation des incertitudes et la conversion d'unités de mesure
Option Pricing Via Levy Models In R16 ⭐
using the Inverse-Transform method to speed up options pricing simulations in R
Propagation of distributions by Monte-Carlo sampling: Real number types with uncertainty represented by samples.
A python based, MPI enabled, Monte-Carlo calculation of 2D system using Metropolis algorithm.
Pythonic particle-based (super-droplet) warm-rain/aqueous-chemistry cloud microphysics package with box, parcel & 1D/2D prescribed-flow examples in Python, Julia and Matlab
Wqu Projects13 ⭐
Projects are developed for implementing the knowledge gained in the courses studied at World Quant University and meeting the requirement of clearing the courses.
Implement Option Pricing Model Using Python10 ⭐
Simulated GBM using MC simulation, estimated option' Greeks using numerical methods such as finite difference, pathwise derivative estimate and likelihood ratio methods. Lastly, implemented binomial tree option pricing to price American option.
Algorithmic Trading43 ⭐
I have been deeply interested in algorithmic trading and systematic trading algorithms. This Repository contains the code of what I have learnt on the way. It starts form some basic simple statistics and will lead up to complex machine learning algorithms.
Towardsai Tutorials595 ⭐
AI-related tutorials. Access any of them for free → https://towardsai.net/editorial
Option Pricing Models16 ⭐
Simple python/streamlit web app for European option pricing using Black-Scholes model, Monte Carlo simulation and Binomial model. Spot prices for the underlying are fetched from Yahoo Finance API.
Markowitzify will implement a variety of portfolio and stock/cryptocurrency analysis methods to optimize portfolios or trading strategies. The two primary classes are "portfolio" and "stonks."
Mathematics Statistics For Data Science30 ⭐
Mathematical & Statistical topics to perform statistical analysis and tests; Linear Regression, Probability Theory, Monte Carlo Simulation, Statistical Sampling, Bootstrapping, Dimensionality reduction techniques (PCA, FA, CCA), Imputation techniques, Statistical Tests (Kolmogorov Smirnov), Robust Estimators (FastMCD) and more in Python and R.
A Monte Carlo molecular simulation software especially suited for materials simulations with polarizable models
GOMC - GPU Optimized Monte Carlo is a parallel molecular simulation code designed for high-performance simulation of large systems
A program with an implemented Monte Carlo Ray Tracer algorithm for global illumination of a virtual 3D scene.
Slot machine base game evolutionary RTP optimization as parallel implementation with MPI.
Ithaka board game is played on a four by four square grid with three pieces in each of four colors.
GridCal, a cross-platform power systems solver written in Python with user interface and embedded python console
Supplychainpy is a Python library for supply chain analysis, modelling and simulation. The library assists a workflow that is reliant on Excel and VBA.
EGSnrc toolkit for Monte Carlo simulation of ionizing radiation — Trousse d'outils logiciels pour la simulation Monte Carlo du rayonnement ionisant
Monte Carlo simulation routines for high-performance parallelization of differential equation solvers and scientific machine learning
AdaptivePELE is a Python package aimed at enhancing the sampling of molecular simulations
Finmath Lib353 ⭐
Mathematical Finance Library: Algorithms and methodologies related to mathematical finance.
Predict stock market pricing over 180 minutes using Black-Scholes stocastic modelling and parallel Monte-Carlo simulations.
GemPy is an open-source, Python-based 3-D structural geological modeling software, which allows the implicit (i.e. automatic) creation of complex geological models from interface and orientation data. It also offers support for stochastic modeling to adress parameter and model uncertainties.