期刊名称：Discussion Papers / School of Business, University of New South Wales
出版年度：2008
卷号：2008
出版社：Sydney
摘要：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.
