time-varying parameter vector autoregression with stochastic volatility. The empirical analysis reveals several new …

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 …

flows, and examines its incremental role in explaining stock return volatility. We suggest that “other information” contains … timely basis than dividends or earnings. The link between “other information” and volatility can be derived from a … Ohlson's (1995) linear information dynamics. Using standardized regressions we find volatility increases when current “other …

Aggregate implied volatility spread (IVS), defined as the cross-sectional average difference in the implied …

We use realized volatilities based on after hours high frequency returns to predict next day volatility. We extend … inclusion of the preopen variance can improve the out-of-sample forecastability of the next day conditional day volatility … day conditional volatility. Our findings support the results of prior studies that traders trade for non …

; indeed, structural estimation of a news-diffusion model indicates that return shocks emanating in the United States are only …

We investigate the daily short-selling by foreign investors and their impact on stock price, liquidity, and volatility … volatility, providing evidence against the foreign investors' destabilizing role in emerging markets …

with within-year seasonality. We reduce the effect of price volatility on the dividend-price ratio by applying a simple …