This study propose a new robust method to rank the performances of multi-assets （portfolios）, based purely on their return time series. This method makes no assumption on the distributions. Topsoe distance is symmet...This study propose a new robust method to rank the performances of multi-assets （portfolios）, based purely on their return time series. This method makes no assumption on the distributions. Topsoe distance is symmetrized Kullback-Leibler divergence by average of the probabilities. The square root of Topsoe distance is a metric. We extend this metric from probability density functions to real number series on （0, 1 ]. We call it ST-metric. We show the consistency of ST-metric with mean-variance theory and stochastic dominance method of order one and two. We demonstrate the advantages of ST-metric over mean-variance rule and stochastic dominance method of order one and two.展开更多
文摘This study propose a new robust method to rank the performances of multi-assets （portfolios）, based purely on their return time series. This method makes no assumption on the distributions. Topsoe distance is symmetrized Kullback-Leibler divergence by average of the probabilities. The square root of Topsoe distance is a metric. We extend this metric from probability density functions to real number series on （0, 1 ]. We call it ST-metric. We show the consistency of ST-metric with mean-variance theory and stochastic dominance method of order one and two. We demonstrate the advantages of ST-metric over mean-variance rule and stochastic dominance method of order one and two.
