教师论文被国际权威经济学期刊接收发表


2021年5月19日


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5月10日,我院助理教授吕耀廉与浙江大学管理学院副教授肖炜麟,新加坡管理大学经济学院、李光前商学院李光前经济金融学教授余俊合作的论文“The Grid Bootstrap for Continuous Time Models”被经济学领域权威期刊Journal of Business and Economics Statistics 接收发表。

该论文旨在通过提出新的Grid bootstrap方法,构建连续时间模型的持久性参数置信区间。作者证明,当取样间距(h)渐近为0,Hansen(1999)对于持久性参数置信区间不一定具备正确的置信水平,因为Hansen 生成bootstrap样本时忽略了初始值对in-fill极限分布的影响。该论文首先改良了Grid bootstrap置信区间的构建方法,使初始值呈现在in-fill极限分布中以获得正确的置信水平。另外,通过概率展开(Probabilistic expansion),作者证明,改良的bootstrap方法能够获得优于in-fill极限理论的置信区间。论文基于改良的bootstrap方法,提出新的中位数无偏估计量(median unbiased estimator)。论文发现,将此方法应用于检测不同到期收益率的债券利息及实际波动率(Realized volatility)的不稳定性时,两种bootstrap 方法在初始值较大时呈现显著差异。



Assistant Professor Yiu Lim LUI's Paper Accepted by Journal of Business and Economics Statistics

May 19, 2021

Yiu Lim LUI, IAER Assistant Professor, had his paper "The Grid Bootstrap for Continuous Time Models" accepted for publication in Journal of Business and Economics Statistics on May 10, 2021. The paper was co-authored with Weilin XIAO, associate professor at Zhejiang University, and Jun YU, Lee Kong Chian Professor of Economics and Finance at Singapore Management University. 

This paper proposes the new grid bootstrap to construct confidence intervals (CI) for the persistence parameter in a class of continuous-time models. It is different from the standard grid bootstrap of Hansen (1999) in dealing with the initial condition. The asymptotic validity of the CI is discussed under the in-fill scheme. The modified grid bootstrap leads to uniform inferences on the persistence parameter. Its improvement over in-fill asymptotics is achieved by expanding the coefficient-based statistic around its in-fill asymptotic distribution that is non-pivotal and depends on the initial condition. Monte Carlo studies show that the modified grid bootstrap performs better than Hansen's grid bootstrap. Empirical applications to U.S. interest rates and volatilities suggest significant differences between the two bootstrap procedures when the initial condition is large.