Nonlinear Features of Realized FX Volatility

Nonlinear Features of Realized Fx Volatility

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 ARMAXmodel. We explore nonlinear departures from these lin...

Nonlinear Connections Between Realized Volatility and High/Low Range Information

In this paper we look at the relationship between daily realized volatility estimates using intraday data and range based estimates using daily high/low price range information. Several classical range based volatility estimators are compared with nonlinear functional forms in mapping range based information onto realized volatility measures. We find that the older range based estimators can be...

Forecasting Realized Volatility with Linear and Nonlinear Models

Modeling Gold Volatility: Realized GARCH Approach

F orecasting the volatility of a financial asset has wide implications in finance. Conditional variance extracted from the GARCH framework could be a suitable proxy of financial asset volatility. Option pricing, portfolio optimization, and risk management are examples of implications of conditional variance forecasting. One of the most recent methods of volatility forecasting is Real...

Asymmetric Realized Volatility Risk

In this paper, we document that realized variation measures constructed from high-frequency returns reveal a large degree of volatility risk in stock and index returns, where we characterize volatility risk by the extent to which forecasting errors in realized volatility are substantive. Even though returns standardized by ex post quadratic variation measures are nearly Gaussian, this unpredict...