. Applying our model to high-frequency transaction data, we detect two distinct regimes in the intraday volatility process: a … dominant volatility regime that is observable throughout the trading day representing the risk-transferring trading activity of … investors, and a minor volatility regime that concentrates around market liquidity shocks which mainly capture impacts of firm …

Forecasting volatility models typically rely on either daily or high frequency (HF) data and the choice between these … two categories is not obvious. In particular, the latter allows to treat volatility as observable but they suffer from … these two family forecasting-volatility models, comparing their performance (in terms of Value at Risk, VaR) under the …

This paper introduces novel volatility diffusion models to account for the stylized facts of high-frequency financial … data such as volatility clustering, intra-day U-shape, and leverage effect. For example, the daily integrated volatility of … the proposed volatility process has a realized GARCH structure with an asymmetric effect on log-returns. To further …

leverage effect and maintains a mathematical structure that facilitates volatility estimation. A class of bivariate models that … volatility information improves the day volatility estimation. The results indicate a forecasting improvement using bivariate …We propose a methodology to include night volatility estimates in the day volatility modeling problem with high …

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

In the class of univariate conditional volatility models, the three most popular are the generalized autoregressive … mathematical regularity properties, including invertibility, to determine the likelihood function for estimation, and the … effects on conditional volatility of positive and negative effects of equal magnitude, and possibly also leverage, which is …

forecasting the volatility of equity prices, using high-frequency data from 2000 to 2016. We consider the SPY and 20 stocks that …, 60 and 300 seconds), forecast horizons (1, 5, 22 and 66 days) and the use of standard and robust-to-noise volatility and …-time forecasts than the HAR-RV model, although no single extended model dominates. In general, standard volatility measures at the …

breaks) in the volatility of financial time series. Comparative study of three techniques: ICSS, NPCPM and Cheng's algorithm … breaks in volatility, while Cheng's technique works well only when a single break occurs. …

daily realized volatility data of Standard & Poor's 500 (S&P 500) and several other indices, we obtained good performance … heterogeneous autoregressive and other models of realized volatility. …