Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/87068
Authors: 
Diks, Cees
Panchenko, Valentyn
van Dijk, Dick
Year of Publication: 
2008
Series/Report no.: 
Tinbergen Institute Discussion Paper 08-050/4
Abstract: 
We propose new scoring rules based on partial likelihood for assessing the relative out-of-sample predictive accuracy of competing density forecasts over a specific region of interest, such as the left tail in financial risk management. By construction, existing scoring rules based on weighted likelihood or censored normal likelihood favor density forecasts with more probability mass in the given region, rendering predictive accuracy tests biased towards such densities. Our novel partial likelihood-based scoring rules do not suffer from this problem, as illustrated by means of Monte Carlo simulations and an empirical application to daily S&P 500 index returns.
Subjects: 
density forecast evaluation
scoring rules
weighted likelihood ratio scores
partial likelihood
risk management
JEL: 
C12
C22
C52
C53
Document Type: 
Working Paper

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