Using Markov Chains and Entropy to Explain Value at Risk in European Electricity Markets

The increasing complexity of energy systems amid the global push for decarbonization raises important questions about how transitions in the energy matrix affect financial risk in electricity markets. This study investigates the relationship between structural changes in national energy matrices and the systemic risk associated with electricity prices in Europe from 2015 to 2022. Using daily electricity price data, we calculate log returns and estimate the Value at Risk (VaR) at the 1% level as a measure of extreme financial loss. We incorporate energy market variables, including the volatility of Brent oil and coal prices, and an entropy-based indicator derived from the Shannon index, which captures the degree of technological dispersion in the energy mix over time. A fixed-effects panel regression model is applied across 21 European countries to identify the drivers of energy-related financial risk. Results show that higher volatility in Brent and coal prices significantly increases the VaR, and that greater entropy reflecting a more complex and dynamic energy transition also correlates with higher systemic risk. These findings suggest that while energy diversification is a goal of sustainability, it may entail short-term instability. The study contributes to the understanding of how structural transformations in energy systems interact with financial vulnerabilities in liberalized electricity markets.