跳至正文
返回文库全部文档

跨市场动量择时与超额收益

文章 arXiv papers · 作者: Marc Rohloff et al.
阅读原文

总结

该文介绍一种相对基准的策略，利用时间序列动量，在相关且可投资的指数间择时获取超额收益。策略只需基准和相关指数的收益序列，无需通过回归估计参数。该方法应用于股票和债券基准，再合并成一个以Eonia总收益指数为基准的绝对收益投资组合。

据报告，仅做多回测的年收益接近MSCI World和Bloomberg Barclays Euro Aggregate Corporate Bond基准的两倍，同时满足所述事前风险要求。组合策略报告的夏普比率为1.8，检验还发现其优于固定权重投资组合，包括具有被动股票因子敞口的组合。文中称该策略扣除交易成本后仍盈利。这些发现来自回测；摘录未提供样本日期、详细实施规则或关于样本外表现和稳健性的更多证据。

核心观点

  • 该方法利用相关可投资指数间的时间序列动量择时获取超额收益。
  • 该方法需要基准和相关指数序列，无需通过回归估计参数。
  • 文中报告称，仅做多回测的表现优于股票和公司债券基准。
  • 据报告，该方法优于静态等权和被动因子敞口组合，且扣除交易成本后仍有优势。
  • 摘录未说明样本期间，也未提供评估样本外稳健性所需的细节。

标签

动量多资产股票固定收益回测
全文
# Timing Excess Returns A cross-universe approach to alpha


# Timing Excess Returns A cross-universe approach to alpha









We present a simple model that uses time series momentum in order to construct strategies that systematically outperform their benchmark. The simplicity of our model is elegant: We only require a benchmark time series and several related investable indizes, not requiring regression or other models to estimate our parameters. We find that our one size fits all approach delivers significant outperformance in both equity and bond markets while meeting the ex-ante risk requirements, nearly doubling yearly returns vs. the MSCI World and Bloomberg Barclays Euro Aggregate Corporate Bond benchmarks in a long-only backtest. We then combine both approaches into an absolute return strategy by benchmarking vs. the Eonia Total Return Index and find significant outperformance at a sharpe ratio of 1.8. Furthermore, we demonstrate that our model delivers a benefit versus a static portfolio with fixed mean weights, showing that timing of excess return momentum has a sizeable benefit vs. static allocations. This also applies to the passively investable equity factors, where we outperform a static factor exposure portfolio with statistical significance. Also, we show that our model delivers an alpha after deducting transaction costs.

在遵守原作品许可的前提下，附作者信息全文展示。 许可协议: abstract CC0

此摘要由 Stratmill 研究智能体根据原文撰写，并非原文副本。