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基于CAPE的长期股票指数收益可预测性模型

文章 arXiv papers · 作者: Natascia Angelini et al.
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总结

本文提出一个以周期调整市盈率（CAPE）为核心的离散时间股票指数收益模型。收益增长由动量、与初始CAPE对数相关的基本面成分，以及产生扩散式价格行为的随机驱动成分组成。在模型中，初始估值设定增长的参考水平，而扰动可能使价格偏离该水平。

作者证明，在足够长的时间跨度下，预期收益和预期总收益随初始对数CAPE线性变化，而收益方差以符合扩散过程的速度下降。动量在较短和中等时间跨度内仍可能造成泡沫或暴跌，因此估值被视为长期参考，而非预测近期价格变动的依据。这些结论基于所述模型假设；本文没有提供实证验证、参数估计或实际使用CAPE的交易规则。

核心观点

  • 该模型将股票指数收益增长与动量、初始对数CAPE和随机扰动联系起来。
  • 初始CAPE确定了增长的参考水平，价格则可能偏离这一水平。
  • 在较长时间跨度下，模型预期收益与初始对数CAPE呈线性关系。
  • 模型允许动量在较短时期内引发泡沫和暴跌。
  • 所述结果属于理论结论，并依赖模型假设。

标签

股票因子投资动量统计学
全文
# Value matters: Predictability of Stock Index Returns


# Value matters: Predictability of Stock Index Returns









We present a simple dynamical model of stock index returns which is grounded on the ability of the Cyclically Adjusted Price Earning (CAPE) valuation ratio devised by Robert Shiller to predict long-horizon performances of the market. More precisely, we discuss a discrete time dynamics in which the return growth depends on three components: i) a momentum component, naturally justified in terms of agents' belief that expected returns are higher in bullish markets than in bearish ones, ii) a fundamental component proportional to the logarithmic CAPE at time zero. The initial value of the ratio determines the reference growth level, from which the actual stock price may deviate as an effect of random external disturbances, and iii) a driving component which ensures the diffusive behaviour of stock prices. Under these assumptions, we prove that for a sufficiently large horizon the expected rate of return and the expected gross return are linear in the initial logarithmic CAPE, and their variance goes to zero with a rate of convergence consistent with the diffusive behaviour. Eventually this means that the momentum component may generate bubbles and crashes in the short and medium run, nevertheless the valuation ratio remains a good reference point of future long-run returns.

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。