ARFIMAX and ARFIMAX-TARCH realized volatility modeling

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...

Har Modeling for Realized Volatility Forecasting

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...

Realized Volatility Options

We will in some places restrict attention to puts, by put-call parity: for realized variance options, a long-call short-put combination pays [X]T −Q, equal to a Q-strike variance swap; and for realized volatility options, a long-call short-put combination pays [X] T − Q1/2, equal to a Q1/2-strike volatility swap. Unlike variance swaps [EQF07/024, EQF07/045], which admit exact model-free (assumi...

Realized Volatility When Sampling Times

When estimating integrated volatilities based on high-frequency data, simplifying assumptions are usually imposed on the relationship between the observation times and the price process. In this paper, we establish a central limit theorem for the Realized Volatility in a general endogenous time setting. We ∗We are grateful to Andrew Patton and Neil Shephard, and the participants of the Stevanov...