Dependence structure in the Australian electricity markets: New evidence from regular vine copulae

Apergis, Nicholas; Gözgör, Giray; Lau, Chi Keung Marco; Wang, Shixuan

doi:10.1016/j.eneco.2020.104834

Cited by 27 publications

(17 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is an important task for existing COVID-19 related researches. In terms of research method, conditional correlation methods ( Balcilar and Ozdemir, 2013 ; Chen et al, 2020 ; Dua and Tuteja, 2016 ; El Ghini and Saidi, 2016 ; Lei et al, 2019 ; Liang et al, 2020a ; Liang et al, 2020b ; Öztek and Öcal, 2017 ; Tsuji, 2020 ; Wei et al, 2017 , 2020a , 2020b , 2021 ; Wright and Hirano, 2002 ; Zhang et al, 2019 , 2020 ; Zhang et al, 2019a,b ), Granger-causality ( Balboa et al, 2015 ; Massa and Rosellón, 2020 ; Papana et al, 2017 ; Woźniak, 2016 ; Yang et al, 2021 ), copula models ( Apergis et al, 2020 ; Boako et al, 2019 ; Kotkatvuori-Örnberg, 2016 ; Mensah and Premaratne, 2017 ; Rodriguez, 2007 ; Wen et al, 2012 ), and conditional value-at-risk ( Ji et al, 2018a , 2019 ; Li and Wei, 2018 ; Mensi et al, 2017 ; Reboredo and Ugolini, 2015 , 2016 ) are widely used to explore the characteristics of the information transmission between two variables/assets. Since Diebold and Yılmaz (2009 , 2012 , 2014) 's study which explore the connectedness across an asset system, a large body of literature realizes the importance of uncovering system spillovers in a large system ( Ji et al, 2018b ; Lundgren et al, 2018 ; Tiwari et al, 2020 ; Wang et al, 2020 ; Wei et al, 2019 ; Yoon et al, 2019 ; Zeng et al, 2019 ; Zhang, 2017 ).…”

Section: Introductionmentioning

confidence: 99%

Return connectedness among commodity and financial assets during the COVID-19 pandemic: Evidence from China and the US

Wei

et al. 2021

Resources Policy

View full text Add to dashboard Cite

In this paper, we explore the dynamics of the return connectedness among major commodity assets (crude oil, gold and corn) and financial assets (stock, bond and currency) in China and the US during recent COVID-19 pandemic by using the time-varying connectedness measurement introduced by Antonakakis et al. (2020). Firstly, we find that the total return connectedness of the US commodity and financial assets is stronger than that of the Chinese commodity and financial assets in most cases, and both of them increase rapidly after the outbreak of COVID-19. Secondly, gold is a net transmitter of return shocks in both the Chinese and the US markets before the burst of COVID-19 pandemic, while stock and currency become net transmitters of shocks in both markets after that. Thirdly, corn usually receives the shocks from other commodity and financial assets in both China and the US markets during the COVID-19 epidemic, and the shocks it receives peak during this period, making it the strongest net receiver of shocks. Fourthly, crude oil shifts from a net transmitter to a net receiver of shocks in China after the outbreak of COVID-19, but it remains to be a net transmitter of shocks in the US. Finally, bond changes from a net receiver to a net transmitter of shocks in China after the outbreak of the epidemic, but converts from a net transmitter to a net receiver of shock in the US. The interchangeable roles of the commodity and financial assets suggest flexible regulatory and portfolio allocation strategies should be applied by policy makers and investors.

show abstract

Section: Introductionmentioning

confidence: 99%

Return connectedness among commodity and financial assets during the COVID-19 pandemic: Evidence from China and the US

Wei

et al. 2021

Resources Policy

View full text Add to dashboard Cite

show abstract

“…Most power supply transactions (generation, purchasing and selling) in Australia occur in the free market, implying that market participants must match the supply and demand for power simultaneously. Second, spot prices in the Australian power market are incredibly volatile (Apergis et al, 2020), compared with other comparable power markets (Higgs and Worthington, 2008;Mayer and Tr€ uck, 2018). Apergis et al (2020) showed that power prices could fluctuate immensely to levels much higher than the long-term price, implying that Australian power market participants must possess sound risk management when transacting in the market.…”

Section: Introductionmentioning

confidence: 99%

“…Second, spot prices in the Australian power market are incredibly volatile (Apergis et al, 2020), compared with other comparable power markets (Higgs and Worthington, 2008;Mayer and Tr€ uck, 2018). Apergis et al (2020) showed that power prices could fluctuate immensely to levels much higher than the long-term price, implying that Australian power market participants must possess sound risk management when transacting in the market. Third, according to Simshauser (2021), the world's longest transmission network is the Australian power market.…”

Section: Introductionmentioning

confidence: 99%

“…However, none has examined contagions in the Australian interconnected power markets. Recent papers (Ignatieva and Tr€ uck, 2016;Smith and Shively, 2018;Apergis et al, 2020;Yan and Tr€ uck, 2020) have investigated spot price dependence in the Australian interconnected power markets. This paper is different from those for a number of reasons.…”

Section: Introductionmentioning

confidence: 99%

“…This paper is different from those for a number of reasons. First, their papers (Ignatieva and Tr€ uck, 2016;Smith and Shively, 2018;Apergis et al, 2020) examined contagions by measuring the spot price dependence, while this paper examines the contagion of spot price change (i.e. "return").…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Contagions in interconnected power markets

Handika

2021

JRF

View full text Add to dashboard Cite

PurposeThis paper offers an alternative approach to assessing contagions in price and load in the Australian interconnected power markets. This approach enabled us to identify a high-risk region and assess the direction of contagions from both buyers' and sellers' perspectives.Design/methodology/approachThe author used a multinomial logit method to measure contagions. Having identified the exceedance and coexceedances, the author estimated the multinomial logit coefficients of the covariates explaining the probability of a certain number of coexceedances.FindingsMarket participants should recognize the presence of contagion risk and scrutinize price and load dynamics in the NSW and VIC regions to anticipate any simultaneous extreme changes. Regulators need to stabilize the demand and supply sides in those regions to minimize any possible contagions.Originality/valueThis paper presents a pioneering study investigating contagion in the Australian interconnected power markets.

show abstract

Vines climbing higher: Risk management for commodity futures markets using a regular vine copula approach

Liu

Wang

2020

Int. J Fin Econ

Self Cite

View full text Add to dashboard Cite

The volume of trading activity relating to China's commodity futures has grown rapidly over the course of the last decade. To improve risk management in China's commodity futures markets, this paper employs a regular vine (R-vine) copula model to study the dependence structure of commodity futures and to enhance Value-at-Risk (VaR) forecast. In doing so, we find that China's commodity futures market is not centred on one category of commodity futures and the tail dependence between different categories of commodity futures varies significantly. Based on the dependence structure analysed using the R-vine copula model, we forecast the VaR of individual indices, which are formed of several commodity futures, as well as forecasting the VaR of an equally-weighted portfolio. Our method can outperform the standard GARCH-VaR method in terms of VaR backtesting. The tool developed within this study will enable those involved in commodity futures markets to improve their risk management.

show abstract

Dependence structure in the Australian electricity markets: New evidence from regular vine copulae

Cited by 27 publications

References 41 publications

Return connectedness among commodity and financial assets during the COVID-19 pandemic: Evidence from China and the US

Return connectedness among commodity and financial assets during the COVID-19 pandemic: Evidence from China and the US

Contagions in interconnected power markets

Vines climbing higher: Risk management for commodity futures markets using a regular vine copula approach

Contact Info

Product

Resources

About