EconPapers    
Economics at your fingertips  
 

Forecasting extreme electricity spot prices

Volodymyr Korniichuk

No 03-14, Cologne Graduate School Working Paper Series from Cologne Graduate School in Management, Economics and Social Sciences

Abstract: We 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.

Keywords: electricity spot prices; copula; GPD; negative binomial distribution (search for similar items in EconPapers)
JEL-codes: C53 C51 C32 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm, nep-ene, nep-for, nep-reg and nep-rmg
Date: 2012-12-27
References: View references in EconPapers View complete reference list from CitEc
Citations View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
http://www.cgs.uni-koeln.de/fileadmin/wiso_fak/cgs ... aper/cgswp_03-14.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:cgr:cgsser:03-14

Access Statistics for this paper

More papers in Cologne Graduate School Working Paper Series from Cologne Graduate School in Management, Economics and Social Sciences Contact information at EDIRC.
Series data maintained by David Kusterer ().

 
Page updated 2016-01-23
Handle: RePEc:cgr:cgsser:03-14