estimation procedures. Our key interest is the extraction of intra-day volatility patterns from high-frequency integer price …We investigate high-frequency volatility models for analyzing intra-day tick by tick stock price changes using Bayesian … distributions. We allow for stochastic volatility by modeling the variance as a stochastic function of time, with intra-day periodic …

back-testing models. We conclude by comparing in-sample and out-of-sample performances of complex volatility models. …

In this paper, we review the most common specifications of discrete-time stochastic volatility (SV) models and …

to overall realized variation and their contribution to predictive regressions of realized volatility. We find evidence …

. This makes the result markedly different from the volatility case. Observationally equivalent decompositions of the …

capability to capture the short-term behaviour of extremes without involving an arbitrary stochastic volatility model or a … prefiltration of the data, which certainly impacts the estimation. We make use of the proposed model to obtain an improved estimate …

mean and volatility. The endogenous structural breakpoint unit root test, ARDL model, and alternative volatility models … price while the volatility of global fertilizer prices and crude oil price from March to December 2008 are higher than in …

estimation of the tail of the predictive distribution. Two novel concepts are introduced that offer a specific focus on this part …

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 … of returns. Explicitly modeling this volatility risk is fundamental. We propose a dually asymmetric realized volatility …