【摘 要】
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Volatilities of asset returns are central to the theory and practice of asset pricing, portfolio allocation, and risk management.In financial economics, the
【机 构】
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Department of Statistics, University of Connecticut
【出 处】
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IMS-China International Conference on Statistics and Probabi
论文部分内容阅读
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 BlackScholes, diffusion, GARCH, stochastic volatility models and implied volatilities from option prices.Nowadays, thanks to technological innovations, high-frequency finan cial 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 cstimation of volatility.This talk will present my work on multi-scale methods for analyzing jump and volatility variations and the matrix factor model for handling large size volatility matrices.
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