Rolling-Sample Volatility Estimators
扩展了滚动样本方差估计量的连续记录渐近分析，用于估计资产收益的二次变分（即已实现波动率），讨论了渐近有效的窗口长度和加权方案，并通过蒙特卡洛模拟和实证研究验证了理论结果。
We propose extensions of the continuous record asymptotic analysis for rolling sample variance estimators developed for estimating the quadratic variation of asset returns, referred to as integrated or realized volatility. We treat integrated volatility as a continuous time stochastic process sampled at high frequencies and suggest rolling sample estimators which share many features with spot volatility estimators. We discuss asymptotically efficient window lengths and weighting schemes for estimators of the quadratic variation and establish links between various spot and integrated volatility estimators. Theoretical results are complemented with extensive Monte Carlo simulations and an empirical investigation.