统计与管理学院2017年学术报告第36期

【主  题】Statistical Analysis of High-Frequency Financial Data

【报告人】Yazhen Wang, 教授

University of Wisconsin-Madison

【时  间】 2017年05月26日（星期五）16:00－17:00

【地  点】 上海财经大学统计与管理学院大楼1208室

【摘  要】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 introduce statistical analysis of low-frequency and high-frequency financial data and present my work on volatility analysis.

【邀请人】 周勇