This study explores the benefits of incorporating fat-tailed innovations, asymmetric volatility response, and an … extended information set into crude oil return modeling and forecasting. To this end, we utilize standard volatility models … Stochastic Volatility (SV), along with Mixed Data Sampling (MIDAS) regressions, which enable us to incorporate the impacts of …

We propose a multiplicative component model for intraday volatility. The model consists of a seasonality factor, as … volatility, while the latter two account for the impact of the state of the limit order book, utilizing an additive structure … non-linearities in the relationship between the limit order book and subsequent return volatility and underlines the …

We present a two-factor volatility model to study the impact of news arrival and trading volume on stock returns … variance. The model can explicitly account for the association between volatility and volume, as well as the persistence in … volatility variations. The common observation that large volumes are associated with high volatility is explained by the fact …

Does media coverage of a firm have a causal effect on the volatility of its stock price and, if so, is this of … firm’s intra-day stock price volatility. This effect is not driven by persistence in volatility or anticipation of future … over into firms related by the structure of the production network, but does not affect the aggregate level of volatility …

One of the most popular univariate asymmetric conditional volatility models is the exponential GARCH (or EGARCH …) specification. In addition to asymmetry, which captures the different effects on conditional volatility of positive and negative … subsequent shocks to volatility. However, there are as yet no statistical properties available for the (quasi-) maximum …

Of the two most widely estimated univariate asymmetric conditional volatility models, the exponential GARCH (or EGARCH …) specification can capture asymmetry, which refers to the different effects on conditional volatility of positive and negative … shocks to volatility. However, the statistical properties of the (quasi-) maximum likelihood estimator (QMLE) of the EGARCH …

Of the two most widely estimated univariate asymmetric conditional volatility models, the exponential GARCH (or EGARCH …) specification can capture asymmetry, which refers to the different effects on conditional volatility of positive and negative … shocks to volatility. However, the statistical properties of the (quasi-) maximum likelihood estimator (QMLE) of the EGARCH …

One of the most popular univariate asymmetric conditional volatility models is the exponential GARCH (or EGARCH …) specification. In addition to asymmetry, which captures the different effects on conditional volatility of positive and negative … subsequent shocks to volatility. However, the statistical properties of the (quasi-) maximum likelihood estimator of the EGARCH …