long-term interaction between these variables. The volatility models show a significant association between the …

volatility. We extend a reduced form Structural Break Threshold Vector Autoregressive (SBT-VAR) model to a structural SBT … geopolitical risk shock, the other with a simultaneous shale production shock and a geopolitical risk shock. The volatility … volatility response of oil prices to a geopolitical risk shock is higher, but the response is less correlated with the …

Crude oil price volatility has been analyzed extensively for organized spot, forward and futures markets for well over … a decade, and is crucial for forecasting volatility and Value-at-Risk (VaR). There are four major benchmarks in the …-Pacific), which are likely to be highly correlated. This paper analyses the volatility spillover effects across and within the four …

This paper estimates univariate and multivariate conditional volatility and conditional correlation models of spot … volatilities across returns for each market. The estimates of volatility spillovers and asymmetric effects for negative and …

This paper analyses the attributes and the significance of the roughness of oil market volatility. We employ unspanned … stochastic volatility models driven by rough Brownian motions that yield semi-analytical prices for futures options entailing … futures and provide empirical evidence of the roughness in oil volatility. Introducing just one additional parameter, the …

through a new adaptation of the Monte Carlo simulation approach for forecasting multi-period volatility to a fractionally …

Expected Shortfall, for a given volatility model. We obtain precise forecasts of the tail of the distribution of returns not …