the variance matrix. Monte Carlo evidence for parameter estimation based on different small sample sizes is provided. We …

The sum of squared intraday returns provides an unbiased and almost error-free measure of ex-post volatility. In this … paper we develop a nonlinear Autoregressive Fractionally Integrated Moving Average (ARFIMA) model for realized volatility …, which accommodates level shifts, day-of-the-week effects, leverage effects and volatility level effects. Applying the model …

improved ex-post volatility measurements but has also inspired research into their potential value as an informa-tion source … for longer horizon volatility forecasts. In this paper we explore the forecasting value of these high fre-quency series in … conjunction with a variety of volatility models for returns on the Standard & Poor's 100 stock index. We consider two so …

. The methodology is hybrid because it combines a formaltesting procedure with volatility curve pattern recognition based …

the weighting of lagged squared innovations for the estimation of future correlations and volatilities. When we account …

Estimation of the volatility of time series has taken off since the introduction of the GARCH and stochastic volatility … unobserved stochastic volatility, and the varying approaches that have been taken for such estimation. In order to simplify the … comprehension of these estimation methods, the main methods for estimating stochastic volatility are discussed, with focus on their …

The paper considers the problem as to whether financial returns have a common volatility process in the framework of … stochastic volatility models that were suggested by Harvey et al. (1994). We propose a stochastic volatility version of the ARCH … test proposed by Engle and Susmel (1993), who investigated whether international equity markets have a common volatility …