讲座题目： A Frequency Domain Analysis of High Frequency Financial Data

　　报告人：常晋源(西南财经政法大学)

　　报告时间：2017年3月24日(周五)下午3:30-5:00

　　报告地点：经管院B253

　　主办单位：数理经济与数理金融系

　　摘要: High frequency financial data are typically assumed to be an additive composite of a relatively slow-varying continuous-time stochastic process for the price and some measurement errors contaminating the observations. We propose new techniques for analyzing such noisy high frequency financial data, based on frequency domain methods which are extremely popular in simpler errors-in-variables problems for i.i.d. data. We propose to estimate the density function of the measurement error distribution by applying a deconvolution technique with appropriate localization, incorporating the slowly varying feature of the underlying stochastic process. Our analysis shows that the resulting density function estimator is consistent and minimax rate optimal. Estimators of moments of the error distributions and their properties are also investigated. With the estimated error density function, we further study a frequency domain estimator for integrated volatility of the stochastic price process. We show that our integrated volatility estimator achieves the optimal convergence rate when the financial data are contaminated with measurement errors. Numerical examples by simulations and a real data analysis are conducted to demonstrate and validate our analysis.

　　简介: 常晋源博士，2009年毕业于北京师范大学，2013年毕业于北京大学光华管理学院，获经济学博士学位，2013年-2016年墨尔本大学博士后。现任职于西南财经政法。研究方向计量经济学及统计学。已在统计国际顶尖期刊Annals of Statistics发表4篇文章以及其他统计杂志多篇，在计量经济学顶级杂志Journal of Econometrics 发表2篇。