Modelling Volatility of Green Investment: Evidence From Hydrogen Financing

Abstract

ABSTRACT: The global clean energy demand has increased in recent years to address sustainability. At present, hydrogen is considered a cornerstone of sustainable energy solutions. Due to the increased demand for global sustainability, hydrogen has experienced significant growth in demand, production, and research. To ensure its viability and widespread adoption, understanding and managing the inherent risks associated with hydrogen investments is crucial for fostering a stable and attractive environment for continued growth and innovation in this vital sector. Moreover, the hydrogen investment can be influenced by the financial market condition represented by the Volatility Index (VIX). Surprisingly, the volatility dynamics and risk profiles of this growing sector, particularly the influence of broader financial market conditions as reflected by the VIX, remain largely unexplored. This gap in understanding presents a challenge to investors and policymakers seeking to foster stable and sustainable growth in hydrogen financing. To rectify this situation, this research addresses the gap in understanding and predicting hydrogen return volatility by applying various GARCH-type models to the S&P hydrogen economy index and CBOE Volatility Index (VIX) from May 2019 to May 2025. By applying a set of GARCH (generalized autoregressive conditional heteroskedasticity) approaches, the study reveals strong proof of volatility clustering and unequal effects of shocks on hydrogen returns. The TGARCH model highlights the prominence of negative shocks, while the EGARCH model indicates a larger impact from positive shocks. Furthermore, the study shows that the content of information in the Volatility Index (VIX) is an essential determinant to explain the variation in the hydrogen return. The incorporation of the Volatility Index (VIX) into the GARCH variance equation also improves the volatility forecasts of the hydrogen return.

The outcomes of the analysis could be helpful for investors, decision-makers, and stakeholders in developing effective risk management strategies for green energy projects within the emerging hydrogen financing sector. In the future, to contribute to the existing literature, the researchers can explore this area by expanding datasets, adding more macroeconomic factors, investigating specific event impacts, analysing interdependencies with other renewable energy sectors, employing advanced econometric techniques, and considering behavioural influences to further refine our understanding and forecasting capabilities.