We investigate a model in which we connect slowly time varying unconditional long-run volatility with short …-run conditional volatility whose representation is given as a semi-strong GARCH (1,1) process with heavy tailed errors. We focus on … robust estimation of both long-run and short-run volatilities. Our estimation is semiparametric since the long-run volatility …

parametric short-memory models, can be used to estimate the long-memory stochastic volatility model parameters in the presence of …

parametric short-memory models, can be used to estimate the long-memory stochastic volatility model parameters in the presence of …-memory. -- stochastic volatility ; frequency domain estimation ; robust estimation ; spurious persistence ; long-memory ; level shifts …

Empirical volatility studies have discovered nonstationary, long-memory dynamics in the volatility of the stock market … with nonparametric estimates of the fractional differencing parameter d, for financial volatility. In this paper, a fully … volatility (SV-FIAR) model. Joint estimates of the autoregressive and fractional differencing parameters of volatility are found …

Empirical volatility studies have discovered nonstationary, long-memory dynamics in the volatility of the stock market … found with nonparametric estimates of the fractional differencing parameter d, for financial volatility. In this paper, a …, stochastic volatility (SV-FIAR) model. Joint estimates of the autoregressive and fractional differencing parameters of volatility …

of volatility in finance for portfolio allocation, derivative pricing and risk management. The method has a two … average realized volatility processes can achieve a convergence rate close to OP(n−4/9) , which is better than the convergence … based on average realized volatility processes indeed performs better than that based on the price processes. Empirically …

's dynamic properties may lead to misestimation of the intraday spot volatility …

This paper introduces a new specification for the heterogeneous autoregressive (HAR) model for the realized volatility …

two-scales realized volatility (S-TSRV). We derive a finite sample solution to controlling edge effects and for handling … components. As an application of this representation, the paper develops a central limit theory for multivariate volatility …