Forecasting extreme electricity spot prices
AbstractWe propose a model for forecasting extreme electricity prices in real time (high frequency) settings. The unique feature of our model is its ability to forecast electricity price exceedances over very high thresholds, where only a few (if any) observations are available. The model can also be applied for simulating times of occurrence and magnitudes of the extreme prices. We employ a copula with a changing dependence parameter for capturing serial dependence in the extreme prices and the censored GPD for modelling their marginal distributions. For modelling times of the extreme price occurrences we propose an approach based on a negative binomial distribution. The model is applied to electricity spot prices from Australia's national electricity market.
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Bibliographic InfoPaper provided by Cologne Graduate School in Management, Economics and Social Sciences in its series Cologne Graduate School Working Paper Series with number 03-14.
Date of creation: 27 Dec 2012
Date of revision:
electricity spot prices; copula; GPD; negative binomial distribution;
Find related papers by JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-01-19 (All new papers)
- NEP-ECM-2013-01-19 (Econometrics)
- NEP-ENE-2013-01-19 (Energy Economics)
- NEP-FOR-2013-01-19 (Forecasting)
- NEP-REG-2013-01-19 (Regulation)
- NEP-RMG-2013-01-19 (Risk Management)
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