The M6 Competition assessed the performance of competitors using a ranked probability score and an information ratio (IR). While these metrics do well at picking the winners in the competition, crucial questions remain for investors with longer-term incentives. To address these questions, we compare the competitors' performance to a number of conventional (long-only) and alternative indices using standard industry metrics. We apply factor models to measure the competitors' value-adds above industry-standard benchmarks and find that competitors with more extreme performance are less dependent on the benchmarks. We also uncover that most competitors could not generate significant out-performance compared to randomly selected long-only and long-short portfolios but did generate out-performance compared to short-only portfolios. We further introduce two new strategies by picking the competitors with the best (Superstars) and worst (Superlosers) recent performance and show that it is challenging to identify skill amongst investment managers. We also discuss the incentives of winning the competition compared to professional investors, where investors wish to maximize fees over an extended period of time.

翻译：M6竞赛采用排序概率得分和信息比率（IR）评估参赛者表现。尽管这些指标在竞赛优胜者遴选中表现良好，但对于具有长期激励的投资者而言，关键问题依然存在。为解答这些问题，我们使用行业标准指标将参赛者表现与多个传统（纯多头）及另类指数进行对比。通过因子模型衡量参赛者相对于行业标准基准的超额价值，发现表现越极端的参赛者对基准的依赖性越低。研究还揭示：多数参赛者相较于随机选择的纯多头和多空组合未能产生显著超额收益，但相较于纯空头组合确实产生了超额收益。我们进一步提出两种新策略——选取近期表现最佳（超级明星）与最差（超级输家）的参赛者构建组合，结果表明在投资经理中识别技能具有挑战性。此外，我们探讨了竞赛获胜激励与专业投资者激励的差异，后者更倾向于在长期时间内实现费用最大化。