I have been working on a project involving large systems of stochastic differential equations. I considered using Ito.jl (to my knowledge the only package with features for SDEs), but it was not quite to my tastes and did not seem to offer much. In response, I wrote my own solver based on the tutorial "An Algorithmic Introduction to Numerical Simulation of Equations" by Desmond Higham (Euler-Maruyama) and have spent some time optimizing it. Would this be something that people would be interested in using?
There are some small changes that I would have to make for theoretical correctness, but otherwise it looks fairly nice to me. If I do turn this into its own package I will fix any of these latent issues and also work on adding support for features such as different algorithms and distributions. Then we would have Ito.jl for quantitative finance and SDE.jl (or whatever I call it) for controls, dynamical systems, etc. Currently this code is on github with the code for a personal project I am working on at https://github.com/mcorah/MultiQuadLift
