Abstract
Using a fresh empirical approach to time-frequency domain frameworks, this study analyzes the return and volatility spillovers from fossil fuel markets (coal, natural gas, and crude oil) to electricity spot and futures markets in Europe. In the time domain, by an approach developed by Diebold and Yilmaz (2012) which can analyze the directional spillover effect across different markets, we find natural gas has the highest return spillover effect on electricity markets followed by coal and oil. We also find that return spillovers increase with the length of the delivery period of electricity futures. In the frequency domain, using the methodology proposed by Barunik and Krehlik (2018) that can decompose the spillover effect into different frequency bands, we find most of the return spillovers from fossil fuels to electricity are produced in the short term while most of the volatility spillovers are generated in the long term. Additionally, dynamic return spillovers have patterns corresponding to the use of natural gas for electricity generation, while volatility spillovers are sensitive to extreme financial events.
Highlights
Electricity is traded in both spot and futures markets
Diebold and Yilmaz [17] proposed an approach for measuring spillover in the generalized vector autoregression framework using the concept of connectedness, which built on the generalized forecast error variance decomposition (GFEVD) of a Vector Autoregressive (VAR) model with p lags
The last column of the table labelled ‘Directional Spillover (From)’ shows the total spillover effect from all fossil fuel commodities combined on the electricity spot market
Summary
Electricity is traded in both spot and futures markets. Extensive research has been undertaken over the past two decades concerning the spot market for electricity (e.g., [1,2,3,4]). 40.5% of electricity was produced by oil, gas, and coal sources in Europe, which necessarily implies the possibility of the spillover effects across the fossil fuel markets and electricity market. Mjelde and Bessler [12] used a vector error correction model to analyze the relationship between electricity spot prices and electricity-generating fuel sources (natural gas, crude oil, coal, and uranium) in the US. We analyze the return and volatility spillovers from the fossil fuel market commodities of natural gas, coal, and crude oil, to electricity spot and futures markets in Europe, by using two new empirical methods in the time-frequency domain: (1) the Diebold–Yilmaz approach; and (2). Used the Diebold–Yilmaz approach and the Barunik and Krehlik methodology to analyze the volatility connectedness between Henry Hub natural gas and West Texas Intermediate (WTI) crude oil in the time and frequency domains.
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