Optimization-Python
cocp
Optimization-Python | cocp | |
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1 | 1 | |
221 | 75 | |
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0.0 | 10.0 | |
over 2 years ago | over 1 year ago | |
Jupyter Notebook | Jupyter Notebook | |
MIT License | Apache License 2.0 |
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Optimization-Python
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What is the best DCA Strategy - Part IV (Dynamic DCA)
One approach to this problem is based on the Nobel prize winning Modern Portfolio Theory (MPT). In fact, there we can use pretty simple code available online: https://github.com/tirthajyoti/Optimization-Python/blob/master/Portfolio_optimization.ipynb. There is a one BIG difference between DCA and MPT though. Here, we do not want to do a one-time purchase and try to gain maximum profit. We are looking at a dual problem, where we want to purchase regularly, while aiming maximum accumulation.
cocp
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GPT can tune your PID/LQR controllers
I agree and I think I may be able to do what you propose (using COCP). Will share results once I get some. In general I think GPT can be really powerful in translating human feedback in cost functions and constraints for optimization problems.
What are some alternatives?
market-making-backtest - algo trading backtesting on BitMEX
lmpc-py
portfolio_allocation_js - A JavaScript library to allocate and optimize financial portfolios.
Algorithms-for-Automated-Driving - Each chapter of this (mini-)book guides you in programming one important software component for automated driving.
JuMP.jl - Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)
analisis-numerico-computo-cientifico - Análisis numérico y cómputo científico
Optimus * 96 - Optimus is a mathematical programming library for Scala.
NextFace - A high-fidelity 3D face reconstruction library from monocular RGB image(s)
psi4numpy - Combining Psi4 and Numpy for education and development.
swift - Swift for TensorFlow
minizinc-python - Access to all MiniZinc functionality directly from Python