Simple Portfolio Optimization that Works!
164 Pages Posted: 5 Nov 2021 Last revised: 8 Nov 2021
Date Written: October 14, 2021
We first show that the common "mean-variance" portfolio method fails because variance is a horrible risk-measure for investing, and also because estimation errors may cause that method to concentrate the portfolio in losing assets that are highly correlated. We then present a new so-called "filter-diversify" method for portfolio optimization. The filtering process is trivial as it only allows assets into the portfolio if they have sufficiently high estimated returns. The diversification process is based on a new algorithm with several benefits: The algorithm is fairly simple. It allows both positive and negative portfolio weights. It is extremely fast and only takes a few milli-seconds to compute for a portfolio of 1000 assets. It is guaranteed to converge to the optimal solution. It is very robust to estimation errors, because it will only decrease the portfolio weights, so the worst that can happen is that it moves too much of the portfolio into cash (or another low-risk asset of your choice). We perform numerous tests of the new portfolio method on real-world stock-data from USA, and find that the new method performs extremely well on all performance metrics, and is very robust to estimation errors.
Keywords: portfolio optimization
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