Filtering and Identification of Stochastic Risk Premium for Electricity Spot Price Models

Aihara, Shin Ichi; Bagchi, Arunabha; Imreizeeq, Emad

doi:10.3182/20140824-6-za-1003.00325

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2014

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“…Bringing in the compound Poisson jump process, the stochastic model for the electricity futures has been suggested. By using the idea proposed by (Aihara et al, 2014) the original filtering problem is changed to the Gaussian framework and its Kalman filter is derived. In the adaptive filtering algorithm, the parallel filtering method in (Anderson and Moore, 1979) is used to obtain the on-line parameter estimates with the new resampling procedure.…”

Section: Discussionmentioning

confidence: 99%

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Adaptive Filtering in Electricity Spot Price Models

Aihara

Bagchi

2014

Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics

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We study the adaptive filtering for risk premium and system parameters in electricity futures modes. Introducing the jump augmented Vasicek model as the spot price mode, the factor model of the electricity futures is constructed as the stochastic hyperbolic systems with jumps. Representing the main spike phenomena of the electricity spot price from one observed futures data by proxy, the filtering of the stochastic risk premium and its system parameters are developed in a Gaussian framework. By using the parallel filtering algorithm, the online system parameter estimation procedure is proposed.

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Section: Discussionmentioning

confidence: 99%

“…We also generate the observation data If all systems parameters are known, the Kalman filter works good and such simulation results are found in (Aihara et al, 2014). Here we shall look into the feasibility of the proposed on-line algorithm.…”

Section: Simulation Studiesmentioning

confidence: 99%