Dependencies and volatility spillovers among carbon, energy, and stock markets in the EU

Información del proyecto

ECS

Identificador del acuerdo de subvención: 101064650

DOI

10.3030/101064650

Proyecto cerrado

Fecha de la firma de la CE 19 Julio 2022

Fecha de inicio 15 Diciembre 2022

Fecha de finalización 14 Marzo 2025

Financiado con arreglo a

• Marie Skłodowska-Curie Actions (MSCA)

Coste total

Sin datos

Aportación de la UE

€ 172 750,08

Coordinado por

FONDAZIONE ENI ENRICO MATTEI
Italy

Periodic Reporting for period 1 - ECS (Dependencies and volatility spillovers among carbon, energy, and stock markets in the EU)

Período documentado: 2022-12-15 hasta 2025-03-14

Resumen del contexto y de los objetivos generales del proyecto

The research focuses on understanding the interconnections and spillover effects between carbon, energy, metal, and financial markets within the European Union Emissions Trading System (EU-ETS). Given the growing importance of carbon pricing in mitigating climate change, this study aims to provide a comprehensive analysis of market dynamics influencing the EU-ETS. The primary objectives are:

- To analyze the causality direction and dependency structure between carbon allowances (EUA) and key market assets such as oil, gas, coal, metals (gold, silver, copper), and financial indices (EuroStoxx600).
- To explore how these relationships evolve over different trading phases of the EU-ETS (from 2005 to 2022).
- To quantify time-varying spillovers and volatility transmission mechanisms affecting carbon markets.
- To offer policy-relevant insights that can help in designing more resilient carbon pricing strategies.

To achieve these goals, the study employs advanced econometric techniques, including Directed Acyclic Graph (DAG) analysis, Canonical Vine Copula (C-Vine) models, and Time-Varying Parameter Vector Auto Regressive models with Stochastic Volatility (TVP-VAR-SV). By integrating these methodologies, the research aims to provide a novel perspective on the interconnectedness of the EU carbon market with broader economic and financial variables​

Trabajo realizado desde el comienzo del proyecto hasta el final del período abarcado por el informe y los principales resultados hasta la fecha

The study was conducted using a large dataset covering daily trading data from April 25, 2005, to December 30, 2022, encompassing all phases of the EU-ETS. The key methodological steps and findings include:

- Causality and Dependency Analysis: Using DAG models, the study identified that energy, metal, and financial markets exert a significant influence on the EU carbon market. Specifically, oil and copper prices show the highest dependency on EUA prices.
- Spillover Effects: TVP-VAR-SV models revealed that carbon markets are net receivers of shocks from energy, metal, and financial markets, with spillover effects lasting between 2 to 15 days.
- Time-Variation in Market Relationships: The strength of these relationships varies across different market phases, with higher volatility observed during economic crises (e.g. the Global Financial Crisis, COVID-19, and the Russia-Ukraine war).
- Robustness Checks: Alternative econometric techniques, including FCI and FGES algorithms, were used to validate the findings. The results consistently demonstrated that carbon price dynamics are heavily influenced by external market factors​.

Avances que van más allá del estado de la técnica e impacto potencial esperado (incluida la repercusión socioeconómica y las implicaciones sociales más amplias del proyecto hasta la fecha)

This research advances previous studies by adopting a multidimensional approach that integrates econometric models capable of capturing dynamic, non-linear, and high-frequency interactions among markets. The key contributions include:

- Multi-Market Perspective: Unlike traditional studies that focus on bilateral relationships (e.g. carbon-energy or carbon-financial linkages), this study provides a comprehensive, simultaneous analysis of all relevant markets.
- Time-Varying Dependency Analysis: By using DAG and C-Vine Copula models, the study moves beyond static correlation analyses, allowing for a deeper understanding of evolving market dependencies.
- Spillover Effect Characterization: The study identifies not only the magnitude but also the direction and duration of spillover effects, which is crucial for risk assessment and investment strategies.
- Policy-Relevant Insights: The findings suggest that policy interventions should consider the cross-market dynamics that impact carbon price volatility, particularly in times of economic uncertainty​