The increasing availability of intraday financial data has led to improvements in daily volatility forecasting through … long-memory models of realized volatility. This paper demonstrates the merit of the non-parametric Nearest Neighbor (NN …

-day and intra-day volatility models by estimating the AR(1)-GARCH(1,1)-skT and the AR(1)-HAR-RV-skT frameworks, respectively … intra-day volatility model is not as appropriate as it was expected to be for each of the different asset classes; stock … performance of the inter-day and intra-day volatility models across various markets. The inter-day specification predicts and …

ARFIMAX models are applied in estimating the intra-day realized volatility of the CAC40 and DAX30 indices. Volatility … clustering and asymmetry characterize the logarithmic realized volatility of both indices. ARFIMAX model with time … superior next trading day's realized volatility forecasts …

such as the realized volatility and squared overnight returns, are confronted with those from ARFIMA realized volatility …

decades in the mean and volatility dynamics, including the underlying volatility persistence and volatility spillovers … existence of time varying correlations as well as time varying shock and volatility spillovers between the returns of FTSE and …

dynamics adapts to the non-normal nature of financial data, which helps to robustify the volatility estimates. The new model … volatility forecasting of stock returns and exchange rates. …

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 …

volatility of individual stock returns and exchange rate returns. …

improved volatility measurements but has also inspired research into their potential value as an information source for … volatility forecasting. In this paper we explore the forecasting value of historical volatility (extracted from daily return … series), of implied volatility (extracted from option pricing data) and of realised volatility (computed as the sum of …

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 …