We examine the efficacy with which the CBOE Volatility Index (VIX) predicts future (30 day forward) S&P realized volatility. We find that the VIX’s accuracy is about 63%. An alternative framework that we present, built on asymptotic distribution theory, predicts this volatility with an...

This study examines the nexus between precious metals (gold and silver) and oil (crude oil and heating oil) realized volatilities introducing a novel quantile extended joint connectedness framework combining quantile vector autoregression (White et al., 2015) with the extended joint...

This study proposes a GARCH copula quantile regression model to capture the downside and upside tail dependence between oil price change and stock market returns at different risk levels. In the model, ten copulas are provided to measure the nonlinearity of the tail dependence with the marginal...

This study examines the effect of oil price uncertainty (OPU) on corporate innovation productivity. Using firm-level innovation data of US firms, we find that an increase in OPU causes a reduction in future innovation outcomes, proxied by the number of patents and subsequent citations. This...

In this paper we consider the Markov Switching GARCH model suggested by Haas, Mittnik, and Paolella (2004) and obtain the functional central limit theorems for and . The functional central limit theorem for is also obtained

We use weekly data on returns and range-based volatility over 2005-2017 to examine the degree of interconnectedness in financial markets of eleven MENA and four Western economies using the methodology proposed by Diebold and Yilmaz (2009, 2012, 2014). Our findings suggest (a) similar patterns of...

This study investigates return and asymmetric volatility spillovers and dynamic correlations between the main and small and medium-sized enterprise (SME) stock markets in Saudi Arabia and Egypt for the periods before and during the COVID-19 pandemic. Return and volatility spillovers are modelled...

This study aims to overcome the problem of dimensionality, accurate estimation, and forecasting Value-at-Risk (VaR) and Expected Shortfall (ES) uncertainty intervals in high frequency data. A Bayesian bootstrapping and backtest density forecasts, which are based on a weighted threshold and...

Using Dutch time-diary data from 1975-2005 covering over 10,000 respondents for 7 consecutive days each, we show that individuals' sleep time exhibits both variability and volatility characterized by stationary autoregressive conditional heteroscedasticity: The absolute values of deviations from...