Decoding the Australian electricity market: New evidence from three-regime hidden semi-Markov model

Abstract

The hidden semi-Markov model (HSMM) is more flexible than the hidden Markov model (HMM). As an extension of the HMM, the sojourn time distribution in the HSMM can be explicitly specified by any distribution, either nonparametric or parametric, facilitating the modelling for the stylised features of electricity prices, such as the short-lived spike and the time-varying mean. By using a three-regime HSMM, this paper investigates the hidden regimes in five Australian States

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

“…In 2011, the Gillard Labor Government introduced the carbon pricing scheme 11 in Australia, commonly known as the carbon tax, with a legislation named Clean Energy 2011, which took effect on July 1, 2012. Although there was a decline in carbon emissions after the imposition of the carbon tax, the net result was a deadweight cost to the economy because it indirectly increased electricity costs for households and industries (Apergis et al, 2019). The Abbott Government repealed the carbon tax on July 1, 2014, and replaced it with the Emission Reduction Fund.…”

“…The Abbott Government repealed the carbon tax on July 1, 2014, and replaced it with the Emission Reduction Fund. Apergis et al (2019) showed that carbon tax is associated with common market characteristics across different states because of "a greater degree of interconnectedness via greater transfer capacity on interstate interconnectors, linking QLD, NSW, and VIC relative to the interconnectors linking TAS and SA to VIC." We suspected that the dependence structure might also have structural breaks due to this policy change.…”

Interconnectedness in the Australian National Electricity Market: A Higher‐Moment Analysis*

“…As Apergis et al . (2019, p. 140) describe the fallout from the failed negotiation: ‘The upshot was that the period 2013–16 left the energy industry with huge uncertainty about what is in store, at a time when it [craved] reassurance more than ever.’…”

“…Tasmania has only a 500 MW interconnector (Basslink) arrangement in place, which links the TAS regional markets with VIC directly, and the rest of the NEM indirectly. Tasmania is also heavily hydro reliant, making it vulnerable to rainfall conditions (Apergis et al ., 2019). The vulnerability in energy supply security was exposed through a power crisis, which occurred in TAS in 2015 when the Basslink interconnector required maintenance, together with TAS having low water storage.…”

Bear, Bull, Sidewalk, and Crash: The Evolution of the US Stock Market Using Over a Century of Daily Data

“…1 Given this, Bulla and Bulla (2006) show that HSMM outperforms the HMM in the reproduction of the stylized facts of daily financial returns. Since then, the HSMM has been a prevailing tool to quantitively identify the market conditions based on the distributional properties of the hidden states (see, Yue (2010), Lau et al, (2017), Wang (2017a, 2017b), Apergis et al, (2019) for detailed literature reviews, and alternative applications in this regard). In light of this, we also employ the HSMM model, for the first time in the literature, to analyse and identify hidden states of the DJIA returns, since its inception spanning 136 years of daily data.…”