Core Viewpoint - Supply chain risk has become an increasing concern for investors, and the article analyzes a unique factor called "centrality measure" to determine its ability to predict stock performance during market disruptions [2][4]. Group 1: Supply Chain Risk and Centrality Measure - The COVID-19 pandemic caused significant disruptions in global supply chains, leading to widespread product shortages and severe impacts on businesses. Even after the initial crisis, geopolitical events and tariff disruptions continued to challenge supply chain resilience [4]. - The article highlights a rising trend in the search volume for "supply chain risk" on Google Trends since 2020, indicating growing market concern [4]. - Traditional fundamental factors like earnings quality and stability can measure a company's ability to withstand supply chain disruptions, but the article focuses on a unique factor derived from supply chain network topology: centrality measure [7]. Group 2: HITS Algorithm and Its Application - Centrality measure assesses the importance of nodes/edges in the supply chain network, helping to identify critical suppliers or customers and their interactions [8]. - The HITS (Hyperlink-Induced Topic Search) algorithm is applied to the supply chain network to identify "hubs" and "authorities," where important customers source from key suppliers and vice versa [8]. Group 3: Investment Portfolio Analysis - The article created five equally weighted investment portfolios based on centrality measures from the FactSet supply chain database and backtested their performance over the past decade [9]. - Cumulative returns of the portfolios based on "important customer centrality" showed significant performance differences, with the highest centrality group (H5) outperforming the lowest (H1) [9]. - Similar results were observed for portfolios based on "important supplier centrality," indicating consistent performance trends across different groups [12]. Group 4: Performance During Market Disruptions - Since the COVID-19 pandemic, the spread of cumulative return differentials has continued to widen, with significant events impacting global supply chains noted in the analysis [15]. - High centrality companies often experience initial sell-offs during market turmoil but are bought back as the market stabilizes, while low centrality companies struggle to recover even after stability returns [15]. Group 5: Comparison with Traditional Factors - The centrality measure was compared with traditional alpha/risk factors, revealing a positive correlation with market capitalization, as larger companies play more significant roles in supply chain networks [19]. - The correlation of centrality measures with spread returns was stronger than with market capitalization, suggesting that centrality captures stock price signals not reflected by size alone [23]. - Backtesting results indicated significant differences in performance between centrality measures and size factors, with annualized spread returns of 6.08% for important customer centrality and 4.67% for important supplier centrality, compared to only 1.44% for market capitalization [26]. Group 6: Conclusion and Future Research Directions - The study suggests that centrality measure, derived from supply chain relationships, may have predictive capabilities for stock performance, especially during supply chain disruptions [30]. - The analysis indicates that centrality measures outperform size factors, with potential applications in predicting volatility during market turmoil and serving as a key risk factor [30].