主  题： Quantile correlations and quantile autoregressive modeling

主讲人：李国栋博士（香港大学统计与精算学系副教授）

时 间：2015年7月10日（周五）下午16:00-17:00

地 点：北院卓远楼307

主办单位：统计与数学学院

摘要：In this paper, we propose two important measures, quantile correlation (QCOR) and quantile partial correlation (QPCOR). We then apply them to quantile autoregressive (QAR) models, and introduce two valuable quantities, the quantile autocorrelation function (QACF) and the quantile partial autocorrelation function (QPACF). This allows us to extend the Box-Jenkins three-stage procedure (model identification, model parameter estimation, and model diagnostic checking) from classical autoregressive models to quantile autoregressive models. Specifically, the QPACF of an observed time series can be employed to identify the autoregressive order, while the QACF of residuals obtained from the fitted model can be used to assess the model adequacy. We not only demonstrate the asymptotic properties of QCOR and QPCOR, but also show the large sample results of QACF, QPACF and the quantile version of the Box-Pierce test. Moreover, we obtain the bootstrap approximations to the distributions of parameter estimators and proposed measures. Simulation studies indicate that the proposed methods perform well in finite samples, and an empirical example is presented to illustrate usefulness.

李国栋博士简介：统计学博士，香港大学统计与精算学系副教授，研究领域包括时间序列分析、计量经济、金融风险管理等，在国际权威统计学、计量经济学期刊Journal of the American Statistical Association, Biometrika, Journal of Econometrics等发表20多篇论文。