Estimation of risk measures on electricity markets with fat-tailed distributions

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

Standard

Estimation of risk measures on electricity markets with fat-tailed distributions. / Fianu, Emmanuel Senyo; Grossi, Luigi.

in: Journal of Energy Markets, Jahrgang 8, Nr. 3, 09.2015, S. 29-54.

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

Harvard

APA

Vancouver

Bibtex

@article{86ce9d0f203b4319873de8d5535bb3d7,
title = "Estimation of risk measures on electricity markets with fat-tailed distributions",
abstract = "This paper proposes an autoregressive-generalized autoregressive conditional heteroscedasticity (AR-GARCH)-type extreme value theory (EVT) model with various innovations based on value-at-risk (VaR) and conditional value-at-risk (CVaR) for energy price risk quantification in different emerging energy markets.We assess the best-fitting AR-exponential GARCH-EVT and AR-threshold GARCH-EVT models for Powernext and the European Energy Exchange, respectively. EVT is adopted explicitly to model the tails of the return distribution in order to capture extremal events. One of the main contributions of this paper is the estimation ofVaR and CVaR via EVT on the lower and upper tails of the return distribution in order to capture the extreme events of the distribution. This paper also contributes to the literature by analyzing both the upper and lower tails, in order to satisfy the different perspectives of regulators and investors in the energy market.",
keywords = "Sustainability Science, AR-GARCH model, Conditional value-at-risk, Electricity price, Extreme value theory, Risk management, Risk measure",
author = "Fianu, {Emmanuel Senyo} and Luigi Grossi",
year = "2015",
month = sep,
doi = "10.21314/JEM.2015.121",
language = "English",
volume = "8",
pages = "29--54",
journal = "Journal of Energy Markets",
issn = "1756-3607",
publisher = "Infopro digital",
number = "3",

}

RIS

TY - JOUR

T1 - Estimation of risk measures on electricity markets with fat-tailed distributions

AU - Fianu, Emmanuel Senyo

AU - Grossi, Luigi

PY - 2015/9

Y1 - 2015/9

N2 - This paper proposes an autoregressive-generalized autoregressive conditional heteroscedasticity (AR-GARCH)-type extreme value theory (EVT) model with various innovations based on value-at-risk (VaR) and conditional value-at-risk (CVaR) for energy price risk quantification in different emerging energy markets.We assess the best-fitting AR-exponential GARCH-EVT and AR-threshold GARCH-EVT models for Powernext and the European Energy Exchange, respectively. EVT is adopted explicitly to model the tails of the return distribution in order to capture extremal events. One of the main contributions of this paper is the estimation ofVaR and CVaR via EVT on the lower and upper tails of the return distribution in order to capture the extreme events of the distribution. This paper also contributes to the literature by analyzing both the upper and lower tails, in order to satisfy the different perspectives of regulators and investors in the energy market.

AB - This paper proposes an autoregressive-generalized autoregressive conditional heteroscedasticity (AR-GARCH)-type extreme value theory (EVT) model with various innovations based on value-at-risk (VaR) and conditional value-at-risk (CVaR) for energy price risk quantification in different emerging energy markets.We assess the best-fitting AR-exponential GARCH-EVT and AR-threshold GARCH-EVT models for Powernext and the European Energy Exchange, respectively. EVT is adopted explicitly to model the tails of the return distribution in order to capture extremal events. One of the main contributions of this paper is the estimation ofVaR and CVaR via EVT on the lower and upper tails of the return distribution in order to capture the extreme events of the distribution. This paper also contributes to the literature by analyzing both the upper and lower tails, in order to satisfy the different perspectives of regulators and investors in the energy market.

KW - Sustainability Science

KW - AR-GARCH model

KW - Conditional value-at-risk

KW - Electricity price

KW - Extreme value theory

KW - Risk management

KW - Risk measure

UR - http://www.scopus.com/inward/record.url?scp=85045015797&partnerID=8YFLogxK

U2 - 10.21314/JEM.2015.121

DO - 10.21314/JEM.2015.121

M3 - Journal articles

VL - 8

SP - 29

EP - 54

JO - Journal of Energy Markets

JF - Journal of Energy Markets

SN - 1756-3607

IS - 3

ER -

DOI