Median-adaptive portfolios: a minimum criteria approach to asset allocation
提出一类基于等权组合和中位数资产的新投资组合，通过单一参数调整实现任意维度的静态或优化配置，避免维度诅咒，在标准指标上优于等权基准。
Abstract We propose a new class of adaptive portfolios for asset allocation, based on a one-parameter variation of the equally weighted portfolio and the use of the median-ranked asset. Our methodological contribution offers a simple way of performing, static or optimized, allocation of assets in portfolios of any dimension, thus easily circumventing the “curse of dimensionality”. Our results show that, even for a static selection of the parameter that defines our allocation, we obtain improved performance compared to the equally weighted benchmark in all the standard metrics. For the case of an optimized selection of the parameter we offer results from minimum variance optimization, that do require the estimation of the covariance matrix, but our approach can easily be adapted to other kinds of portfolio objective functions. This new class of portfolios can easily be added to, as a complement or substitute, to any existing portfolio allocation method.