Modeling Electricity Price Using A Threshold Conditional Autoregressive Geometric Process Jump Model

DOI10.1080/03610926.2013.788714zbMath1462.62173OpenAlexW2041182578MaRDI QIDQ2876225

C. P. Y. Lam, S. T. Boris Choy, Jennifer So-Kuen Chan

Publication date: 18 August 2014

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2013.788714

zbMATH Keywords

seasonalitylong memoryforecastingmean reversionheteroskedasticityprice spike

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Bayesian inference (62F15) Signal detection and filtering (aspects of stochastic processes) (60G35) Prediction theory (aspects of stochastic processes) (60G25)

Related Items (5)

Statistical inference for doubly geometric process with exponential distribution ⋮ Numerical solution to an integral equation for the kth moment function of a geometric process ⋮ The double ratio geometric process for the analysis of recurrent events ⋮ Power series expansions for the probability distribution, mean value and variance functions of a geometric process with gamma interarrival times ⋮ Statistical inference for doubly geometric process with Weibull interarrival times

Uses Software

• WinBUGS

Cites Work

• Geometric processes and replacement problem
• A Bayesian conditional autoregressive geometric process model for range data
• Pricing in Electricity Markets: A Mean Reverting Jump Diffusion Model with Seasonality
• SCALE MIXTURES DISTRIBUTIONS IN STATISTICAL MODELLING
• A DIFFUSION MODEL FOR ELECTRICITY PRICES
• Bayesian Measures of Model Complexity and Fit

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