摘要翻译：
投资经理的表现是根据财务指数等基准进行评估的。由于大多数专业数据库不跟踪基准组合构成变化的操作限制，性能的标准测试在测试期结束时而不是在测试期开始时使用构成参考基准的资产时，会受到“前瞻性基准偏差”的影响。在这里，我们报告，“前瞻基准偏差”在普通股投资组合中可以表现出惊人的大振幅（以标准普尔500为基准的年利率高达8%）--而大多数研究强调了共同基金和对冲基金业绩中的相关生存偏差，这种偏差预计会更大。我们使用1926年至2006年的CRSP数据库，并分析了美国500强的持续资本化，以证明这种偏差可以解释对夏普比率等绩效指标的总体高估以及对风险的低估，如通过峰谷降额来衡量。我们证明了在文献中研究的存活率和前瞻性偏差的估计中存在显著的偏差。针对具有相似投资约束的随机策略，提出了一种检验投资策略性质的一般方法。
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英文标题：
《Look-Ahead Benchmark Bias in Portfolio Performance Evaluation》
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作者：
Gilles Daniel, Didier Sornette and Peter Wohrmann
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最新提交年份：
2008
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Portfolio Management        项目组合管理
分类描述：Security selection and optimization, capital allocation, investment strategies and performance measurement
证券选择与优化、资本配置、投资策略与绩效评价
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一级分类：Physics        物理学
二级分类：Physics and Society        物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
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英文摘要：
  Performance of investment managers are evaluated in comparison with benchmarks, such as financial indices. Due to the operational constraint that most professional databases do not track the change of constitution of benchmark portfolios, standard tests of performance suffer from the "look-ahead benchmark bias," when they use the assets constituting the benchmarks of reference at the end of the testing period, rather than at the beginning of the period. Here, we report that the "look-ahead benchmark bias" can exhibit a surprisingly large amplitude for portfolios of common stocks (up to 8% annum for the S&P500 taken as the benchmark) -- while most studies have emphasized related survival biases in performance of mutual and hedge funds for which the biases can be expected to be even larger. We use the CRSP database from 1926 to 2006 and analyze the running top 500 US capitalizations to demonstrate that this bias can account for a gross overestimation of performance metrics such as the Sharpe ratio as well as an underestimation of risk, as measured for instance by peak-to-valley drawdowns. We demonstrate the presence of a significant bias in the estimation of the survival and look-ahead biases studied in the literature. A general methodology to test the properties of investment strategies is advanced in terms of random strategies with similar investment constraints.
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PDF链接：
https://arxiv.org/pdf/0810.1922