In this paper, we study the dynamic interdependencies between high-frequency volatility, liquidity demand as well as …. Liquidity is causal for future volatility but not vice versa. Furthermore, trade sizes are negatively driven by past trading …

differences of opinion is left, and hence volatility is decreased. …

direction of company-specific news. Information-implied reactions in returns, volatility as well as liquidity demand and supply … London Stock Exchange (LSE), we find market-wide robust news-dependent responses in volatility and trading volume. However …

differences of opinion is left, and hence volatility is decreased. …

direction of company-specific news. Information-implied reactions in returns, volatility as well as liquidity demand and supply … London Stock Exchange (LSE), we find market-wide robust news-dependent responses in volatility and trading volume. However …

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 …

on some high frequency basis has spurred the research in the field of volatility modeling and forecasting into new … directions. First, the realized variance is a much better estimate of the latent volatility than the sum of the weighted daily … squared returns. As such it is better suited for comparing the out-of-sample performances of competing volatility models …

We investigate the predictability of both volatility and volume for a large sample of Japanese stocks. The particular … practically always improves upon the na?ve forecast provided by historical volatility. As a somewhat surprising result, we also …

We investigate the predictability of both volatility and volume for a large sample of Japanese stocks. The particular … practically always improves upon the na?ve forecast provided by historical volatility. As a somewhat surprising result, we also …

-switching multi-fractal model in Calvet and Fisher (2001) which allows for estimation of its parameters via maximum likelihood and … Bayesian forecasting of volatility. However, applicability of MLE is restricted to cases with a discrete distribution of … volatility components. From a practical point of view, ML also becomes computationally unfeasible for large numbers of components …