In this paper, we suggest how to handle the issue of heteroskedasticity measurement errors when specifying dynamic models for conditional expectation realized variance. We show that either adding a GARCH correction within an asymmetric extension HAR class ( AHAR - ), or working multiplicative error AMEM ) greatly reduces need quarticity/quadratic terms capture attenuation bias. This feature in ...

This paper introduces a unified approach for modeling high-frequency financial data that can accommodate both the continuous-time jump–diffusion and discrete-time realized GARCH model by embedding discrete structure in continuous instantaneous volatility process. The key feature of proposed is corresponding conditional daily integrated adopts an autoregressive structure, where jump variation se...

Most procedures for modeling and forecasting financial asset return volatilities rely on restrictive and complicated parametric GARCH or stochastic volatility models. The method of realized volatility constructed from high-frequency intraday returns is an alternative choice for volatility measurement. In this paper we make an empirical analysis on Chinese stock index data by using the method of...

A measurement volatility of return process should be the primary object of traders and practitioners in financial market for management of their portfolios and making trading decisions. The realized volatility is the representative estimator of (integrated) volatility and is computed from historical data of the return. The sampling interval of the return plays a key role in computing the realiz...