EconPapers    
Economics at your fingertips  
 

Assessment of probabilistic forecasts: Proper scoring rules and moments

Alexander Tsyplakov

Applied Econometrics, 2012, vol. 27, issue 3, 115-132

Abstract: The article provides an overview of probabilistic forecasting and discusses a theoretical approach to assessing the quality of density forecasts, based on proper scoring rules and moments. An artificial example of predicting second-order autoregression and an example of predicting RTSI stock index are used to try out this approach.

Keywords: probabilistic forecast; forecast calibration; probability integral transform; scoring rule (search for similar items in EconPapers)
JEL-codes: C18 C53 (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: Track citations by RSS feed

Downloads: (external link)
http://pe.cemi.rssi.ru/pe_2012_3_115-132.pdf Full text (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: https://EconPapers.repec.org/RePEc:ris:apltrx:0181

Access Statistics for this article

Applied Econometrics is currently edited by Anatoly Peresetsky

More articles in Applied Econometrics from Russian Presidential Academy of National Economy and Public Administration (RANEPA)
Bibliographic data for series maintained by Anatoly Peresetsky ().

 
Page updated 2021-07-09
Handle: RePEc:ris:apltrx:0181