Dynamic Spillovers and Portfolio Construction: A TVP-VAR Analysis of the S&P 500, SSE, ESG ETFs, and Commodities

[Purpose] This study explores the dynamic return spillovers and portfolio implications of key global financial assets, including U.S. and Chinese equities, crude oil, and ESG-focused investments, with the aim of analyzing whether investors in the S&P 500 and Shanghai Stock Exchange can mitigate portfolio risk through strategic allocation to ESG and commodity assets. This research provides a quantitative framework for investors, portfolio managers, and policymakers to make evidence-based decisions on risk diversification, hedging strategies, and performance enhancement in both equity and multi-asset portfolios under conditions of financial and economic uncertainty. [Design/methodology/approach] A Time-Varying Parameter Vector Autoregressive (TVP-VAR) model is applied to examine evolving interdependencies among the S&P 500 Index, Shanghai Stock Exchange Composite Index, West Texas Intermediate (WTI) crude oil, and the SPDR S&P 500 ESG ETF (EFIV). Four dynamic portfolio optimization strategies—Minimum Variance, Minimum Correlation, Minimum Connectedness, and Risk Parity—are implemented and evaluated under varying market conditions. [Findings] Results indicate that the S&P 500 and EFIV consistently act as net transmitters of volatility, while WTI and SSE function predominantly as receivers. Portfolios optimized using Minimum Connectedness and Correlation strategies demonstrate superior cumulative returns, whereas those using Minimum Variance and Risk Parity approaches achieve better risk-adjusted performance. Bivariate hedging analyses highlight the effectiveness of ESG assets, especially in equity pairings. [Practical implications] Findings provide valuable insights for institutional investors and portfolio managers seeking to optimize diversification, manage risk, and incorporate ESG principles in asset allocation strategies, particularly under conditions of global financial uncertainty. [Originality/value] This study contributes to the literature by integrating ESG-focused instruments within a dynamic connectedness framework and demonstrating their role in portfolio risk mitigation and performance enhancement. Specifically, it introduces a novel combination of TVP-VAR modeling with multiple dynamic portfolio optimization strategies, demonstrating how ESG assets can systematically mitigate portfolio risk and enhance performance, offering new guidance for evidence-based decision-making in financial markets.