摘要：The availability of high-frequency intraday data allows us to accurately estimate stock volatility. This paper employs a bivariate diffusion to model the price and volatility of an asset and investigates kernel type estimators of spot volatility based on high-frequency return data. We establish both pointwise and global asymptotic distributions for the estimators.
关键词：asymptotic normality; CIR model; constant elasticity of diffusion; extreme distribution; kernel estimator; long memory; stock price
