Nonlinear Features of Realized FX Volatility
利用日内高频数据估计外汇波动率，发现标准时间序列模型存在测量误差，进而采用双随机过程捕捉波动率的非线性特征，如突变、时变持续性和波动方差，对预测、对冲和衍生品定价有启示。
This paper investigates nonlinear features of FX volatility dynamics using estimates of daily volatility based on the sum of intraday squared returns. Measurement errors associated with using realized volatility to estimate ex post latent volatility imply that standard time series models of the conditional variance become variants of an ARMAX model. We explore nonlinear departures from these linear specifications using a doubly stochastic process under duration-dependent mixing. This process can capture large abrupt changes in the level of volatility, time-varying persistence, and time-varying variance of volatility. The results have implications for forecast precision, hedging, and pricing of derivatives. © 2002 President and Fellows of Harvard College and the Massachusetts Institute of Technology.