Modeling Turning Points In Global Equity Market

Research output: Working paperWorking papers

Standard

Modeling Turning Points In Global Equity Market. / Fianu, Emmanuel Senyo; Ahelegbey, Daniel Felix; Grossi, Luigi.
Pavia Universty - Department of Economics and Management, 2020. (DEM - Working Paper Series; Vol. 195 (11-20)).

Research output: Working paperWorking papers

Harvard

Fianu, ES, Ahelegbey, DF & Grossi, L 2020 'Modeling Turning Points In Global Equity Market' DEM - Working Paper Series, vol. 195 (11-20), Pavia Universty - Department of Economics and Management. <https://economiaemanagement.dip.unipv.it/sites/dip10/files/2022-04/DEMWP0195.pdf>

APA

Fianu, E. S., Ahelegbey, D. F., & Grossi, L. (2020). Modeling Turning Points In Global Equity Market. (DEM - Working Paper Series; Vol. 195 (11-20)). Pavia Universty - Department of Economics and Management. https://economiaemanagement.dip.unipv.it/sites/dip10/files/2022-04/DEMWP0195.pdf

Vancouver

Fianu ES, Ahelegbey DF, Grossi L. Modeling Turning Points In Global Equity Market. Pavia Universty - Department of Economics and Management. 2020 Nov 20. (DEM - Working Paper Series).

Bibtex

@techreport{22a4a99288a640c5aee6a7989435a2e3,
title = "Modeling Turning Points In Global Equity Market",
abstract = "Ensuring the security of stable, efficient, and reliable energy supplies has intensified the interconnections among energy markets. Imbalances between supply and demand due to operational failures, congestions and other sources of risk faced by these connections can lead to a system that is vulnerable to the spread of risk and its spill-over. The main contribution of this paper lies in the adoption of recently proposed network models in an innovative way, which enhances the proper analysis of these market connections. The case of the Italian energy market is studied because it is a clear example of a zonal market where risk can spread across connected zones. We estimate within-day and across-day zonal market interconnections with a multivariate time series of hourly prices, forecast demand and wind generation over the period 2010 – 2016 and evaluate the dynamics and persistence of zonal market connections examining the central market and the spread of risk in the zones of the Italian electricity market. Our findings show that models based purely on prices give a better and more accurate explanation of risk contagion than models with exogenous regressors, revealing that the Central North and Central South zones are the most influential in terms of hub centrality for intraday and inter-day risk transmission, respectively, in the Italian energy market.",
keywords = "Economics, Bayesian inferenc, Dynamic Programming, Turning points, Networks VAR",
author = "Fianu, {Emmanuel Senyo} and Ahelegbey, {Daniel Felix} and Luigi Grossi",
note = "Publisher Copyright: {\textcopyright} 2021 Elsevier B.V.",
year = "2020",
month = nov,
day = "20",
language = "English",
series = "DEM - Working Paper Series",
publisher = "Pavia Universty - Department of Economics and Management",
address = "Italy",
type = "WorkingPaper",
institution = "Pavia Universty - Department of Economics and Management",

}

RIS

TY - UNPB

T1 - Modeling Turning Points In Global Equity Market

AU - Fianu, Emmanuel Senyo

AU - Ahelegbey, Daniel Felix

AU - Grossi, Luigi

N1 - Publisher Copyright: © 2021 Elsevier B.V.

PY - 2020/11/20

Y1 - 2020/11/20

N2 - Ensuring the security of stable, efficient, and reliable energy supplies has intensified the interconnections among energy markets. Imbalances between supply and demand due to operational failures, congestions and other sources of risk faced by these connections can lead to a system that is vulnerable to the spread of risk and its spill-over. The main contribution of this paper lies in the adoption of recently proposed network models in an innovative way, which enhances the proper analysis of these market connections. The case of the Italian energy market is studied because it is a clear example of a zonal market where risk can spread across connected zones. We estimate within-day and across-day zonal market interconnections with a multivariate time series of hourly prices, forecast demand and wind generation over the period 2010 – 2016 and evaluate the dynamics and persistence of zonal market connections examining the central market and the spread of risk in the zones of the Italian electricity market. Our findings show that models based purely on prices give a better and more accurate explanation of risk contagion than models with exogenous regressors, revealing that the Central North and Central South zones are the most influential in terms of hub centrality for intraday and inter-day risk transmission, respectively, in the Italian energy market.

AB - Ensuring the security of stable, efficient, and reliable energy supplies has intensified the interconnections among energy markets. Imbalances between supply and demand due to operational failures, congestions and other sources of risk faced by these connections can lead to a system that is vulnerable to the spread of risk and its spill-over. The main contribution of this paper lies in the adoption of recently proposed network models in an innovative way, which enhances the proper analysis of these market connections. The case of the Italian energy market is studied because it is a clear example of a zonal market where risk can spread across connected zones. We estimate within-day and across-day zonal market interconnections with a multivariate time series of hourly prices, forecast demand and wind generation over the period 2010 – 2016 and evaluate the dynamics and persistence of zonal market connections examining the central market and the spread of risk in the zones of the Italian electricity market. Our findings show that models based purely on prices give a better and more accurate explanation of risk contagion than models with exogenous regressors, revealing that the Central North and Central South zones are the most influential in terms of hub centrality for intraday and inter-day risk transmission, respectively, in the Italian energy market.

KW - Economics

KW - Bayesian inferenc

KW - Dynamic Programming

KW - Turning points

KW - Networks VAR

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

M3 - Working papers

T3 - DEM - Working Paper Series

BT - Modeling Turning Points In Global Equity Market

PB - Pavia Universty - Department of Economics and Management

ER -

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