The paper investigates the time-varying correlation between stock market prices and oil prices for oil-importing and oil-exporting countries. A DCC-GARCH-GJR approach is

We evaluate the performance of an extensive family of ARCH models in modeling the daily Value-at-Risk (VaR) of perfectly diversified portfolios in five stock indices, using a number of distributional assumptions and sample sizes. We find, first, that leptokurtic distributions are able to produce better one-step-ahead VaR forecasts; second, the choice of sample size is important for the accuracy of the forecast, whereas the specification of the conditional mean is indifferent. Finally, the ARCH structure producing the most accurate forecasts is different for every portfolio and specific to each equity index.

Motivated from Ross (1989) who maintains that asset volatilities are synonymous to the information flow, we claim that cross-market volatility transmission effects are synonymous to cross-market information flows or "information channels" from one market to another. Based on this assertion we assess whether cross-market volatility flows contain important information that can improve the accuracy of oil price realized volatility forecasting. We concentrate on realized volatilities derived from the intra-day prices of the Brent crude oil and four different asset classes (Stocks, Forex, Commodities and Macro), which represent the different "information channels" by which oil price volatility is impacted from. We employ a HAR framework and estimate forecasts for 1-day to 66-days ahead. Our findings provide strong evidence that the use of the different "information channels" enhances the predictive accuracy of oil price realized volatility at all forecasting horizons. Numerous forecasting evaluation tests and alternative model specifications confirm the robustness of our results.

The paper investigates the effects of oil price shocks on stock market volatility in Europe by focusing on three measures of volatility, i.e. the conditional, the realised and the implied volatility. The findings suggest that supply-side shocks and oil specific demand shocks do not affect volatility, whereas, oil price changes due to aggregate demand shocks lead to a reduction in stock market volatility. More specifically, the aggregate demand oil price shocks have a significant explanatory power on both current-and forward-looking volatilities. The results are qualitatively similar for the aggregate stock market volatility and the industrial sectors' volatilities. Finally, a robustness exercise using short-and long-run volatility models supports the findings. JEL: C13, C32, G10, G15, Q40

Do oil prices and stock markets move in tandem or in opposite directions? The complex and time varying relationship between oil prices and stock markets has caught the attention of the financial press, investors, policymakers, researchers, and the general public in recent years. In light of such attention, this paper reviews research on the oil price and stock market relationship. The majority of papers we survey study the impacts of oil markets on stock markets, whereas, little research in the reverse direction exists. Our review finds that the causal effects between oil and stock markets depend heavily on whether research is performed using aggregate stock market indices, sectorial indices, or firm-level data and whether stock markets operate in net oil-importing or net oil-exporting countries. Additionally, conclusions vary depending on whether studies use symmetric or asymmetric changes in the price of oil, or whether they focus on unexpected changes in oil prices. Finally, we find that most studies show oil price volatility transmits to stock market volatility, and that including measures of stock market performance improves forecasts of oil prices and oil price volatility. Several important avenues for further research are identified.

This paper investigates the time-varying conditional correlation between oil price and stock market volatility for six major oil-importing and oil-exporting countries.

The time-varying correlation between oil prices returns and European industrial sector indices returns, considering the origin of the oil price shock, is investigated. A time-varying multivariate heteroskedastic framework is employed to test the above hypothesis based on data from 10 European sectors. The contemporaneous correlations suggest that the relationship between sector indices and oil prices change over time and they are industry specific. In addition, the supply-side oil price shocks result in low to moderate positive correlation levels, the precautionary demand oil price shocks lead to almost zero correlation levels, whereas the aggregate demand oil price shocks generate significant changes in the correlation levels (either positive or negative). Both the origin of the oil price shock and the type of industry are important determinants of the correlation level between industrial sectors' returns and oil prices. Prominent among the results is the fact that during the financial crisis of 2008 some sectors were providing diversification opportunities to investors dealing with the crude oil market.JEL: C32, C51, G1, Q4.

This paper investigates the time-varying relationship between economic/financial uncertainty and oil price shocks in the US. A structural VAR (SVAR) model and a time-varying parameter VAR (TVP-VAR) model are estimated, using six indicators that reflect economic and financial uncertainty. The findings of the study reveal that static frameworks (SVAR) do not show the full dynamics of the oil price shocks effects to the US economic/financial uncertainty. This is owing to the evidence provided by the time-varying framework (TVP-VAR), which convincingly shows that uncertainty responses to the three oil price shocks are heterogeneous both over time and over the different oil price shocks. In particular, uncertainty responses seem to experience a shift in the post global financial crisis period. Thus, the conventional findings that economic fundamentals response marginally, positively or negatively to supply-side, aggregate demand and oil specific demand shocks, respectively, do not necessarily hold at all periods. Rather, they are impacted by the prevailing economic conditions at each time period. The findings are important to policy makers and investors, as they provide new insights on the said relationships.