Financial-Models-Numerical-Methods
SDE
| Financial-Models-Numerical-Methods | SDE | |
|---|---|---|
| 3 | 1 | |
| 5,267 | 153 | |
| - | 0.0% | |
| 6.2 | 0.0 | |
| 2 months ago | almost 3 years ago | |
| Jupyter Notebook | MATLAB | |
| GNU Affero General Public License v3.0 | MIT License |
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Financial-Models-Numerical-Methods
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Pricing models - which do MMs use these days
If you have experience with Python, here is a great repo: https://github.com/cantaro86/Financial-Models-Numerical-Methods If you don't know Python, I suggest you learn. It's one of the easier languages to learn. The course below will teach you everything you need to get started. https://www.youtube.com/watch?v=rfscVS0vtbw
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Ask HN: Best Resources on (Computational) Finance
I found this collection of Jupyter notebooks really well done. Some basic knowledge in stochastic calculus, financial mathematics and statistics is needed.
https://github.com/cantaro86/Financial-Models-Numerical-Meth...
- Classical portfolio optimization in a Python notebook
SDE
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Ask HN: Good Book on Stochastic Differential Equations?
I am not an expert in SDEs (my background is machine learning) but if I wanted to dig more into the subject, this is where I personally would start. Code [1] and pdf [2] for the book are available.
Simo Särkkä and Arno Solin (2019). Applied Stochastic Differential Equations. Cambridge University Press. Cambridge, UK.
[1] https://github.com/AaltoML/SDE
[2] https://users.aalto.fi/~asolin/sde-book/sde-book.pdf
What are some alternatives?
machine_learning_basics - Plain python implementations of basic machine learning algorithms
score_sde - Official code for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
rmi - A learned index structure
DifferentialEquations.jl - 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.
Quantsbin - Quantitative Finance tools
gramm - Gramm is a complete data visualization toolbox for Matlab. It provides an easy to use and high-level interface to produce publication-quality plots of complex data with varied statistical visualizations. Gramm is inspired by R's ggplot2 library.
torchsde - Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
fastpages - An easy to use blogging platform, with enhanced support for Jupyter Notebooks.
ModelingToolkit.jl - An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
hca-resources - zipline-broker Examples. Full notebooks plus python code for long term investment strategies using zipline based tools.
dynamax - State Space Models library in JAX