Optimization-Python
portfolio_allocation_js
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| Optimization-Python | portfolio_allocation_js | |
|---|---|---|
| 1 | 1 | |
| 221 | 169 | |
| - | - | |
| 0.0 | 0.0 | |
| over 2 years ago | about 1 year ago | |
| Jupyter Notebook | JavaScript | |
| MIT License | MIT License |
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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.
portfolio_allocation_js
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TMF down -18% in 52 weeks - have people been plowing money into it?
I also found this, which seems to work with Google sheets: https://github.com/lequant40/portfolio_allocation_js. Haven't checked it out yet though, since I primarily use Excel and have the python working.
What are some alternatives?
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