
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
Testing for Granger causality in distribution tails: An application to oil markets integration

This paper proposes an original procedure which allows for testing of Granger-causality for multiple risk levels across tail distributions, hence extending the procedure proposed by Hong et al. (2009). Asymptotic and finite sample properties of the test are considered. This new Granger-causality framework is applied for a set of regional oil markets series. It helps to tackle two main questions 1) Whether oil markets are more or less integrated during periods of extreme energetic prices movements and 2) Whether price-setter markets change during such periods. Our findings indicate that the integration level between crude oil markets tends to decrease during extreme periods and that price-setter markets also change. Such results have policy implication and stress the importance of an active energetic policy during episode of extreme movements. (C) 2012 Elsevier B.V. All rights reserved.
- University of Paris France
- Maastricht University Netherlands
- Paris Nanterre University France
RISK, AUTOCORRELATIONS, 2 International, Distribution tails, Value-at-Risk, LONG-RUN, SHOCKS, Granger-causality in risk, INFLATION, PRICES, CONDITIONAL SKEWNESS, Extreme risk spillovers, Crude oil markets integration, REGRESSION QUANTILES, REGIONALIZATION
RISK, AUTOCORRELATIONS, 2 International, Distribution tails, Value-at-Risk, LONG-RUN, SHOCKS, Granger-causality in risk, INFLATION, PRICES, CONDITIONAL SKEWNESS, Extreme risk spillovers, Crude oil markets integration, REGRESSION QUANTILES, REGIONALIZATION
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).33 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
