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 the competitors' returns and show the difficulty for any competitor to demonstrate a statistically significant value-add above industry-standard benchmarks within the short timeframe of the competition. We also uncover that most competitors generated lower risk-adjusted returns and lower maximum drawdowns than randomly selected portfolios, and that most competitors could not generate significant out-performance in raw returns. 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. Overall, our findings highlight the difference in incentives for competitors over professional investors, where the upside of winning the competition dwarfs the potential downside of not winning to maximize fees over an extended period of time.

翻译：M6竞赛采用排名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。为探究这些问题，我们使用行业标准指标将参赛者表现与多种传统（纯多头）及另类指数进行比较。通过对参赛者收益应用因子模型，我们证明在竞赛的短期框架内，任何参赛者都难以展现出超越行业标准基准的统计显著性增值。研究还发现：多数参赛者的风险调整后收益低于随机组合，最大回撤更小，且大部分参赛者无法产生显著的原始收益超额回报。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（超级失败者）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。总体而言，我们的研究揭示了竞赛参与者与专业投资者在激励机制的差异：对参赛者而言，赢得竞赛的收益远超过未能获胜的潜在损失，而专业投资者则需在长期时间内通过最大化管理费实现收益。