Assessing Dynamic Connectedness in Global Supply Chain Infrastructure Portfolios: The Impact of Risk Factors and Extreme Events

ArXiv ID: 2508.04858 “View on arXiv”

Authors: Haibo Wang

Abstract

This paper analyses the risk factors around investing in global supply chain infrastructure: the energy market, investor sentiment, and global shipping costs. It presents portfolio strategies associated with dynamic risks. A time-varying parameter vector autoregression (TVP-VAR) model is used to study the spillover and interconnectedness of the risk factors for global supply chain infrastructure portfolios from January 5th, 2010, to June 29th, 2023, which are associated with a set of environmental, social, and governance (ESG) indexes. The effects of extreme events on risk spillovers and investment strategy are calculated and compared before and after the COVID-19 outbreak. The results of this study demonstrate that risk shocks influence the dynamic connectedness between global supply chain infrastructure portfolios and three risk factors and show the effects of extreme events on risk spillovers and investment outcomes. Portfolios with higher ESG scores exhibit stronger dynamic connectedness with other portfolios and factors. Net total directional connectedness indicates that West Texas Intermediate (WTI), Baltic Exchange Dry Index (BDI), and investor sentiment volatility index (VIX) consistently are net receivers of spillover shocks. A portfolio with a ticker GLFOX appears to be a time-varying net receiver and giver. The pairwise connectedness shows that WTI and VIX are mostly net receivers. Portfolios with tickers CSUAX, GII, and FGIAX are mostly net givers of spillover shocks. The COVID-19 outbreak changed the structure of dynamic connectedness on portfolios. The mean value of HR and HE indicates that the weights of long/short positions in investment strategy after the COVID-19 outbreak have undergone structural changes compared to the period before. The hedging ability of global supply chain infrastructure investment portfolios with higher ESG scores is superior.

Keywords: TVP-VAR Model, Risk Spillover, Global Supply Chain, ESG Indexes, Connectedness Analysis, Infrastructure

Complexity vs Empirical Score

• Math Complexity: 7.0/10
• Empirical Rigor: 8.0/10
• Quadrant: Holy Grail
• Why: The paper employs an advanced econometric model (TVP-VAR) with dense methodological detail, placing it in the high math complexity range. It is highly data-driven, analyzing specific financial time series over a 13-year period with real-world tickers and quantitative metrics like hedge ratios, making it very backtest-ready and empirically rigorous.

  flowchart TD
    A["<b>Research Goal</b><br>Assess dynamic connectedness in<br>global supply chain infrastructure portfolios<br>impact of risk factors & extreme events"] --> B

    subgraph B ["<b>Methodology & Data</b>"]
        direction LR
        B1["TVP-VAR Model"] --> B2["Data: Jan 2010 - Jun 2023"]
        B2 --> B3["Variables:<br>ESG Indexes, WTI, BDI, VIX"]
    end

    B --> C["<b>Computational Process</b><br>Estimate Time-Varying Parameter<br>Spillover & Connectedness Analysis<br>Pre/Post-COVID Event Comparison"]

    C --> D["<b>Key Findings</b>"]
    
    D --> D1["Risk shocks drive<br>dynamic connectedness"]
    D --> D2["Higher ESG scores<br>show stronger connectedness<br>superior hedging ability"]
    D --> D3["WTI, BDI, VIX<br>net receivers of spillover"]
    D --> D4["COVID-19 changed<br>connectedness structure<br>investment weight shifts"]