crises, liquidity variables have a negative influence on the volatility, in contrast to the time period after the outbrake of …

estimation of market returns by providing a new indicator that accounts for the information content in prices and trading volumes …

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

This study investigates the relation between volatility in the returns and trading volume adjusted for overall up … variance equation of the GARCH(1,1) model tend to reduce persistence in volatility more than the contemporaneous and lagged … trading volume. The overnight non-trading period downward price movement induced trading volume affect conditional volatility …

before the event, as suggested by significantly lower trading volumes and volatilities. The high event-day volatility is …

measurement in economics. Unlike econometrics, ML models are not designed for parameter estimation and inference, but similar to …

Rogers-Satchell (RS) measure is an efficient volatility measure. This paper proposes quantile RS (QRS) measure to … on Standard and Poor 500 and Dow Jones Industrial Average indices show that volatility estimates using QRS measures …-of-sample forecast. For return models, the constant mean structure with Student-t errors and QRS volatility estimates provides the best …

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 …

framework is a bivariate volatility model, where volatility spillovers of either positive or negative sign are allowed for. Our … countries. Regarding the volatility spillovers, such spillovers from bond returns to those of stocks are stronger than the other … results show that by considering time-varying return and volatility spillovers when calculating the risk-minimising portfolio …

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 …