Event-Driven Market Co-Movement Dynamics in Critical Mineral Equities: An Empirical Framework Using Change Point Detection and Cross-Sectional Analysis

Paper: arXiv 2601.10851

Authors: Haibo Wang

Abstract

This study examines market behavior in critical mineral investments using a novel analytical framework that combines change-point detection (PELT algorithm) with cross-sectional analysis. This research analyzes ESG-ranked critical mineral ETFs from March 31, 2014, to April 19, 2024, using the S&P 500 as a benchmark to evaluate market co-movements. The findings demonstrate that different critical mineral investments experienced change points at distinct times, but three major dates, July 23, 2015; March 17, 2020; and December 1, 2020, were common and aligned with global events such as the oil market shock, the COVID-19 pandemic, and later market adjustments. Herding behavior among investors increased after these shocks, following the 2015 and 2020 crises, but shifted to anti-herding after positive vaccine news in late 2020 and after the Russian invasion of Ukraine in 2022. The sensitivity analysis shows that investor coordination is strongest during market downturns but exhibits greater variation during stable periods or after major developments, with these dynamics sensitive to the length of the observation period. Additionally, anti-herding became more apparent during crises, suggesting investors reacted to specific risks rather than moving in lockstep, especially in response to geopolitical shocks.

Complexity vs Empirical Score

• Math Complexity: 5.5/10
• Empirical Rigor: 7.5/10
• Quadrant: Holy Grail — high math complexity, high empirical rigor

Why this score: The paper presents a solid empirical investigation of ESG-ranked critical mineral ETFs by integrating the PELT change-point detection algorithm with cross-sectional herding metrics (CSSD/CSAD). It offers actionable market microstructure insights regarding investor behavior during major geopolitical and macroeconomic shocks.

Research Flowchart

  flowchart TD
    A[Research Goal: Analyze Market Co-Movement & Herding in Critical Mineral Equities] --> B[Data Inputs: ESG Critical Mineral ETFs & S&P 500 Benchmark 2014–2024]
    B --> C[Methodology Step 1: Structural Break Detection via PELT Algorithm]
    C --> D[Methodology Step 2: Cross-Sectional Analysis of Investor Herding Behavior]
    D --> E[Key Finding 1: Structural Breaks Identified at Major Events<br>2015 Oil Shock, 2020 COVID-19, Late 2020 Market Adjustments]
    D --> F[Key Finding 2: Crisis-Driven Behavior Shifts<br>Herding Post-Shocks vs. Anti-Herding Post-Vaccine & Geopolitical Shocks]