Paper: arXiv 2509.10483

Authors: Kuok Sin Un, Marcel Ausloos

Abstract

Through a novel approach, this paper shows that substantial change in stock market behavior has a statistically and economically significant impact on equity risk premium predictability both on in-sample and out-of-sample cases. In line with Auer’s ‘‘Bullish ratio’’, a ‘‘Bullish index’’ is introduced to measure the changes in stock market behavior, which we describe through a ‘‘fluctuation detrending moving average analysis’’ (FDMAA) for returns. We consider 28 indicators. We find that a ‘‘positive shock’’ of the Bullish Index is closely related to strong equity risk premium predictability for forecasts based on macroeconomic variables for up to six months. In contrast, a ‘’negative shock’’ is associated with strong equity risk premium predictability with adequate forecasts for up to nine months when based on technical indicators.

Complexity vs Empirical Score

  • Math Complexity: 6.0/10
  • Empirical Rigor: 5.5/10
  • Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper uses advanced mathematical methods like FDMAA and Hurst exponent estimation, but also includes detailed empirical backtesting with multiple indicators and robustness checks, fitting both criteria for the Holy Grail quadrant.

Research Flowchart

  flowchart TD
  A["Research Goal:<br>Predict Equity Risk Premium<br>accounting for Market Regime Changes"] --> B["Key Methodology:<br>Fluctuation Detrending Moving Average Analysis<br>FDMAA to define 'Bullish Index'"]
  
  B --> C["Data/Inputs:<br>28 Predictors<br>Macro Variables & Technical Indicators"]
  
  C --> D["Computational Process:<br>1. Identify 'Positive' & 'Negative' Shocks<br>2. In-Sample & Out-of-Sample Analysis"]
  
  D --> E{"Key Findings/Outcomes"}
  E --> F["Positive Shock<br>Macro Variables predict ERP up to 6 months"]
  E --> G["Negative Shock<br>Technical Indicators predict ERP up to 9 months"]