expected earnings shock and its volatility, and establish properties of investor behavior on the stock price and its volatility … during financial crises and subsequent recovery. Thereafter, we develop properties to explain excess volatility, short …

vary according to whether they are in low or high volatility regimes. …

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

In this paper we present an exact maximum likelihood treatment forthe estimation of a Stochastic Volatility in Mean …(SVM) model based on Monte Carlo simulation methods. The SVM modelincorporates the unobserved volatility as anexplanatory variable … Stochastic Volatility (SV)model. However, efficient Monte Carlo simulationmethods for SV models have been developed to overcome …

, including market-based estimation of stochastic volatility models, the fine structure of equity-index option dynamics, leverage … and feedback effects in multifactor Wishart stochastic volatility for option pricing, option pricing with non …-Gaussian scaling and infinite-state switching volatility, stock return and cash flow predictability: the role of volatility risk, the …

We introduce a dynamic Skellam model that measures stochastic volatility from high-frequency tick-by-tick discrete … series per day varies from 1000 to 10,000. Complexities in the intraday dynamics of volatility and in the frequency of trades … intraday volatility shows that the dynamic modified Skellam model provides accurate forecasts compared to alternative modeling …