报告题目：ModelingandAnalyzingHigh-FrequencyFinancialData
报告人：WangYazhen教授
UniversityofWisconsin-Madison,USA
时间：3月10日（周一）上午10：00-11：00
地点：数学楼第三报告厅
Abstract: Volatilities of asset returns are central to the theory and practice of asset pricing, portfolio allocation, and risk management. In financial economics, there is extensive research on modeling and forecasting volatility up to the daily level based on Black-Scholes, diffusion, GARCH, stochastic volatility models and implied volatilities from option prices. Nowadays, thanks to technological innovations, high-frequency financial data are available for a host of different financial instruments on markets of all locations and at scales like individual bids to buy and sell, and the full distribution of such bids. The availability of high-frequency data stimulates an upsurge interest in statistical research on better estimation of volatility.This talk will start with a review on low-frequency financial time series and high-frequency financial data. Then I will introduce popular realized volatility computed from high-frequency financial data and present my work on large volatility matrix estimation.
欢迎有兴趣的老师与同学参加！
统计研究院
2014年3月5日