Battle Of The Portfolio Optimization Methods

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

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Code: github.com/CloseToAlgoTrading/CodeFromVideo/tree/m…

LSTM optimization methods: paperswithcode.com/paper/deep-learning-for-portfol…

pyportfolioopt: pypi.org/project/pyportfolioopt/