“Smart Beta”etf有多聪明?相对性能与因素暴露分析

Denys Glushkov
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引用次数: 10

摘要

利用2003-2014年164只国内股票型Smart Beta (SB) etf的综合样本,我分析了这些基金是否通过将投资组合偏向于众所周知的因素(如规模、价值、动量、质量、Beta和波动性)来跑赢基准。然后,我测试Smart Beta基金是否通过定期逆价交易,比传统的上限加权基准基金更有效地获得因子溢价。虽然60%的创业板基金类别超过了原始被动基准,但我发现没有确凿的实证证据支持创业板etf在研究期间优于其风险调整基准的假设。与风险调整后的混合基准相比,SB基金的表现也不显著,后者利用现有的上限加权基金提供低成本的市场、规模和价值因素的被动敞口。SB etf表现出潜在的意想不到的因素倾斜,这可能会抵消预期因素倾斜带来的回报优势。在将SB基金的总配置成分分解为静态和动态效应后,我发现动态因子配置的收益最多是中性的。这与假设是一致的,即静态因素敞口而不是系统的基于规则的再平衡是SB etf业绩的主要驱动力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
How Smart are 'Smart Beta' ETFs? Analysis of Relative Performance and Factor Exposure
Using a comprehensive sample of 164 domestic equity Smart Beta (SB) ETFs during 2003-2014 period, I analyze whether these funds beat their benchmarks by tilting their portfolios to well-known factors such as size, value, momentum, quality, beta and volatility. I then test if Smart Beta funds harvest factor premiums more efficiently than their traditional cap-weighted benchmarks by periodic trading against price movements. While 60% of SB fund categories have beaten their raw passive benchmarks, I find no conclusive empirical evidence to support the hypothesis that SB ETFs outperform their risk-adjusted benchmarks over the studied period. Performance of SB funds is also insignificant when compared with the risk-adjusted blended benchmark that uses existing cap-weighted funds to provide low-cost passive exposure to market, size and value factors. SB ETFs exhibit potentially unintended factor tilts which may work to offset the return advantage from intended factor tilts. After decomposing total allocation component of SB funds into static and dynamic effects, I find that the benefit from dynamic factor allocation is neutral at best. This is consistent with the hypothesis that static factor exposure rather systematic rule-based rebalancing is the main driver of SB ETFs performance.
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