主题：A unified test for predictive quantile regression
主讲人：刘小惠 江西财经大学
主持人：姜云卢 暨南大学
时间：2023年6月16日（周五）上午10：30-11：30
地点：暨南大学石牌校区经济学院大楼（中惠楼）102室
摘要
The asymptotic behavior of quantile regression inference becomes dramatically different when it involves a persistent predictor with zero or nonzero intercept. Distinguishing various properties of a predictor is empirically challenging. This paper develops a unified predictability test for quantile regression regardless of the presence of nonzero intercept and persistence of a predictor. The developed test is a novel combination of data splitting, weighted inference, and a random weighted bootstrap method. Monte Carlo simulations show that the new approach displays significantly better size and power performance than other competing methods in various scenarios, particularly when the predictive regressor contains a nonzero intercept. In an empirical application, we revisit the quantile predictability of the monthly S&P 500 return between 1980 and 2019.
主讲人简介
刘小惠，江西财经大学统计学院，教授，博士生导师，副院长，主要研究领域为稳健统计、统计计算、时间序列分析、混合效应模型等，先后在《中国科学数学》，《数学学报》，Journal of American Statistical Association, Journal of Econometrics、Journal of Business & Economic Statistics、Journal of Computational and Graphical Statistics、Journal of Statistical Software、Statistica Sinica、Oxford Bulletin of Economics and Statistics及Annals of Tourism Research等国内外期刊上发表录用相关学术论文60余篇。先后主持江西省自然基金重点项目，杰出基金项目，国家自然科学基金地区项目、青年项目及面上项目等10余项省部级项目。
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校对|王国长
编辑|麦嘉杰
初审|黄振
终审发布|郑贤
（来源：暨南大学经济学院微信公众号）
