用收益率曲线斜率实时判断经济状态，提升股市收益预测精度。
The Aligned Economic Index & The State Switching Model
- 基于收益率曲线斜率构建动态经济状态模型，实现时变预期收益捕捉。
- 新指标'对齐经济指数'在样本内外均显著提升预测效果，优于主流基准。
- 适合关注宏观预测与资产配置的量化研究者或投资者参考。
大量实证研究显示，股权溢价的可预测性具有状态依赖特征，预测能力主要集中在衰退期（Henkel等，2011；Dangl和Halling，2012；Devpura等，2018）。本文研究美国股票回报在不同经济状态下的可预测性，发现扩张与收缩状态下预期收益均显著变化。本文贡献有二：第一，提出一种基于实际经济状态的切换预测回归模型，以收益率曲线斜率实时定义市场状态。相较于标准单状态回归，该模型在样本内与样本外均显著提升Welch和Goyal（2008）所列主流预测因子的表现，多数因子实现经济上有意义的性能改进。第二，提出新综合预测指标——对齐经济指数（Aligned Economic Index），通过偏最小二乘法（PLS）构建。在状态切换模型下，该指标在样本内与样本外均表现出统计与经济上显著的预测能力，优于广泛使用的基准预测因子及其它组合方法。
原文摘要 · Abstract (English)
A growing empirical literature suggests that equity-premium predictability is state dependent, with much of the forecasting power concentrated around recessionary periods (Henkel et al., 2011; Dangl and Halling, 2012; Devpura et al., 2018). I study U.S. stock return predictability across economic regimes and document strong evidence of time-varying expected returns across both expansionary and contractionary states. I contribute in two ways. First, I introduce a state-switching predictive regression in which the market state is defined in real time using the slope of the yield curve. Relative to the standard one-state predictive regression, the state-switching specification increases both in-sample and out-of-sample performance for the set of popular predictors considered by Welch and Goyal (2008), improving the out-of-sample performance of most predictors in economically meaningful ways. Second, I propose a new aggregate predictor, the Aligned Economic Index, constructed via partial least squares (PLS). Under the state-switching model, the Aligned Economic Index exhibits statistically and economically significant predictive power in sample and out of sample, and it outperforms widely used benchmark predictors and alternative predictor-combination methods.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。