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 If you want to support this channel: https://commerce.coinbase.com/checkout/e47393db-561b-41bb-a5f7-c5f913af87f9 Code: https://github.com/CloseToAlgoTrading/CodeFromVideo/tree/master/Episode_20_Battle_Of_Optimization_Methods LSTM optimization methods: https://paperswithcode.com/paper/deep-learning-for-portfolio-optimisation pyportfolioopt: https://pypi.org/project/pyportfolioopt/