The Aligned Economic Index & The State Switching Model

ArXiv ID: 2512.20460 “View on arXiv”

Authors: Ilias Aarab

Abstract

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.

Keywords: Predictive Regression, Partial Least Squares (PLS), Economic Regimes, Yield Curve, Out-of-Sample Forecasting, Equity

Complexity vs Empirical Score

• Math Complexity: 7.0/10
• Empirical Rigor: 7.5/10
• Quadrant: Holy Grail
• Why: The paper employs advanced econometric techniques like a state-switching predictive regression with an ex-ante yield curve indicator and uses Partial Least Squares (PLS) for dimensionality reduction, indicating substantial mathematical complexity. It is grounded in robust empirical design with a long-term dataset, real-time state definition, in-sample and out-of-sample testing, and comparison to established benchmarks, demonstrating high backtest-ready rigor.

  flowchart TD
    A["Research Goal<br>Identify state-dependent equity-premium predictability<br>and improve forecasting accuracy"] --> B["Methodology<br>State-Switching Predictive Regression"]
    B --> C["Input Data<br>U.S. Stock Returns<br>Yield Curve Slope<br>Welch & Goyal Predictors"]
    C --> D["Process 1: State Definition<br>Real-time economic regimes<br>defined by yield curve slope"]
    C --> E["Process 2: Predictor Construction<br>Aligned Economic Index via<br>Partial Least Squares (PLS)"]
    D --> F["Computational Analysis<br>In-sample & Out-of-sample testing<br>State-switching vs. Standard models"]
    E --> F
    F --> G["Key Findings/Outcomes<br>1. State-switching improves forecasting performance<br>2. Aligned Economic Index shows significant predictive power<br>3. Outperforms standard benchmarks"]