Mean-Maximum Drawdown Optimization of Buy-and-Hold Portfolios Using a Multi-objective Evolutionary Algorithm

We develop a novel Mean-Max Drawdown portfolio optimization approach using buy-and-hold portfolios. The is performed utilizing multi-objective evolutionary algorithm on sample of S&P 100 constituents. Our procedure provides portfolios with better trade-offs compared to relevant benchmarks, regardless the selected subsamples and market conditions. superior performance our particularly pronounced in periods reversing trends (i.e. rally fall same subsample).