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A Novel Way to Diversify Portfolio Weights

25.00 mins
Jean-Paul Jaegers
Thu 2 Nov 2023

There is broad agreement among academics and practitioners that, in general, a diversified portfolio delivers more robust out-of-sample performance than a concentrated one. This session covers a new method to diversify portfolio weights, which does not rely on expected returns or volatilities and is therefore robust to measurement error in these variables. It uses pair-wise regressions to estimate how much variation each asset explains in terms of another asset. The optimisation function finds the portfolio weights that maximise the unexplained variation of the portfolio. We benchmark our method to established methods from the literature, such as the minimum volatility and the equal risk contribution portfolios. We demonstrate that our method adheres to established diversification properties.