Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails

Cees Diks (c.g.h.diks@uva.nl), Valentyn Panchenko and Dick van Dijk

No 2008-10, Discussion Papers from School of Economics, The University of New South Wales

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 likelihoodbased 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.

Keywords: density forecast evaluation; scoring rules; weighted likelihood ratio scores; partial likelihood; risk management. (search for similar items in EconPapers)
JEL-codes: C12 C22 C52 C53 (search for similar items in EconPapers)
Pages: 31 pages
Date: 2008-05
New Economics Papers: this item is included in nep-for, nep-ore and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6)

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Working Paper: Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails (2008)
Working Paper: Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails (2008)
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