TY - JOUR

T1 - Modeling risk contagion in the Italian zonal electricity market

AU - Fianu, Emmanuel Senyo

AU - Ahelegbey, Daniel Felix

AU - Grossi, Luigi

N1 - Funding Information: The authors wish to thank the Associate Editor and four anonymous reviewers for carefully reading the submitted manuscript and for their extremely helpful comments. The authors believe that the suggestions made by the Associate Editor and the reviewers have contributed to the improvement of the paper. However, possible mistakes contained in the current version of the paper must be exclusively attributed to the authors. Emmanuel S. Fianu is grateful (i) for the financial support under grant 01LA1104A from (i) the German Federal Ministry of Education and Research, (ii) to the committee in charge of the Young investigator Training Program (YITP) Research Prizes for Energy Finance Italia 3, and (iii) to the ACRI - Associazione di Fondazioni e Casse di Risparmio Spa, for providing the funding. In addition, many thanks also go to the conference participants of the Energy Finance conference III in 2018 and the The Center for Quantitative Risk Analysis (CEQURA) conference held in 2020 for stimulating discussions and comments. In addition, Luigi Grossi acknowledges the financial support from the Italian Ministry of Education and University (MIUR: Ministero dell’Istruzione, dell’Universitá e della Ricerca), award code FFABR 2017. Publisher Copyright: © 2021 Elsevier B.V.

PY - 2022/4/16

Y1 - 2022/4/16

N2 - Ensuring the security of stable, efficient and reliable energy supplies has intensified the interconnections between energy markets. Imbalances between supply and demand due to operational failures, congestion and other sources of risk faced by market connections can lead to a system that is vulnerable to the spread of risk and its spill-over. The main contribution of this paper is the development and estimation of a Bayesian Graphical Vector-AutoRegression and a Bayesian Graphical Structural Equation Modelling with external regressors - BG-VARX and BG-SEMX, respectively - enhancing the proper analysis of market connections. The Italian electricity market has been chosen because it is a clear example of a zonal market where risk can spread over connected zones. We estimate, for the first time, within-day and across-day zonal market interconnections with a multivariate time series of hourly prices, actual and forecast power demand and forecast wind generation over the period 2014–2019 and evaluate the dynamics and persistence of zonal market connections, examining the spread of risk in the zones of the Italian electricity market. Our findings provide an improved, accurate explanation of risk contagion, identifying the zones that are most influential in terms of hub centrality (major transmitters) and authority centrality (major recipients), respectively, for intra-day and inter-day risk propagation in the Italian electricity market. In addition, the policy implications in terms of market-monitoring are discussed.

AB - Ensuring the security of stable, efficient and reliable energy supplies has intensified the interconnections between energy markets. Imbalances between supply and demand due to operational failures, congestion and other sources of risk faced by market connections can lead to a system that is vulnerable to the spread of risk and its spill-over. The main contribution of this paper is the development and estimation of a Bayesian Graphical Vector-AutoRegression and a Bayesian Graphical Structural Equation Modelling with external regressors - BG-VARX and BG-SEMX, respectively - enhancing the proper analysis of market connections. The Italian electricity market has been chosen because it is a clear example of a zonal market where risk can spread over connected zones. We estimate, for the first time, within-day and across-day zonal market interconnections with a multivariate time series of hourly prices, actual and forecast power demand and forecast wind generation over the period 2014–2019 and evaluate the dynamics and persistence of zonal market connections, examining the spread of risk in the zones of the Italian electricity market. Our findings provide an improved, accurate explanation of risk contagion, identifying the zones that are most influential in terms of hub centrality (major transmitters) and authority centrality (major recipients), respectively, for intra-day and inter-day risk propagation in the Italian electricity market. In addition, the policy implications in terms of market-monitoring are discussed.

KW - Complex networks

KW - Electricity price volatility

KW - OR in energy

KW - Systemic risk

KW - Zonal electricity market

KW - Management studies

KW - Economics

UR - http://www.scopus.com/inward/record.url?scp=85111499367&partnerID=8YFLogxK

U2 - 10.1016/j.ejor.2021.06.052

DO - 10.1016/j.ejor.2021.06.052

M3 - Journal articles

AN - SCOPUS:85111499367

VL - 298

SP - 656

EP - 679

JO - European Journal of Operational Research

JF - European Journal of Operational Research

SN - 0377-2217

IS - 2

ER -