In this video we did a quick comparison of the portfolio optimization methods. In addition to classic methods such as Mean Variance, HRP and CLA, we also tested two exotic methods: the first is based on the idea of using LSTM model directly to optimize Sharpe value, and the second is a pretrained model that predicts future allocations. Also we created a simple strategy for dynamic rebalancing of the portfolio based on a given model and compared the results.
00:24 Theory and Methods
03:00 Comparison of Allocations
04:30 Testing
06:00 Results
If you want to support this channel:
https://commerce.coinbase.com/checkou...
Code: https://github.com/CloseToAlgoTrading...
LSTM optimization methods: https://paperswithcode.com/paper/deep...
pyportfolioopt: https://pypi.org/project/pyportfolioopt/
コメント