Modeling anomalous diffusion and volatility in the Australian national electricity market using a space-fractional Black-Scholes framework

Extreme volatility, price spikes, and complex nonlinear dynamics are characteristics often shown in the electricity market, particularly the Australian national electricity market (NEM). These attributes are usually driven by supply-demand imbalances, renewable energy integration, and regulatory interventions, which make traditional pricing models, such as the Black-Scholes framework, inadequate for capturing key market behaviors like long-memory effects, heavy tails, and volatility clustering. This study developed and applied a fractional Black-Scholes model that integrated space-fractional derivatives to account for memory effects, anomalous diffusion, and extreme price movements. The proposed model was calibrated using historical NEM data, demonstrating significant improvements in the pricing of electricity options. The results suggested that it effectively captured key market behaviors. Overall, the findings offered valuable insights and provided a more accurate representation of the Australian electricity market's distinct dynamics.

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Publication Details

Journal
AIMS Mathematics
Published
2025-01-01
DOI
https://doi.org/10.3934/math.2025560
Citations
1
Primary Topic
Energy Load and Power Forecasting
Type
article
Field-Weighted Citation Impact
0.73
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article

Modeling anomalous diffusion and volatility in the Australian national electricity market using a space-fractional Black-Scholes framework

Wannika Sawangtong, Yonghong Wu, Panumart Sawangtong, Doungporn Wiwatanapataphee
1 citations
AIMS Mathematics
Energy Load and Power Forecasting
0.73
article

Modeling anomalous diffusion and volatility in the Australian national electricity market using a space-fractional Black-Scholes framework

Wannika Sawangtong, Yonghong Wu, Panumart Sawangtong, Doungporn Wiwatanapataphee
article en
1 citations

Abstract

Extreme volatility, price spikes, and complex nonlinear dynamics are characteristics often shown in the electricity market, particularly the Australian national electricity market (NEM). These attributes are usually driven by supply-demand imbalances, renewable energy integration, and regulatory interventions, which make traditional pricing models, such as the Black-Scholes framework, inadequate for capturing key market behaviors like long-memory effects, heavy tails, and volatility clustering. This study developed and applied a fractional Black-Scholes model that integrated space-fractional derivatives to account for memory effects, anomalous diffusion, and extreme price movements. The proposed model was calibrated using historical NEM data, demonstrating significant improvements in the pricing of electricity options. The results suggested that it effectively captured key market behaviors. Overall, the findings offered valuable insights and provided a more accurate representation of the Australian electricity market's distinct dynamics.

AIMS MathematicsVol. 10(5)
Curtin University (AU), Mahidol University (TH), Centre of Excellence in Mathematics (TH), King Mongkut's University of Technology North Bangkok (TH)
Openalex Percentile: Top 28%
Energy Load and Power Forecasting
0.73
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