Dynamic D-Vine copula model with applications to Value-at-Risk (VaR)

Regular vine copulas are multivariate dependence models constructed from pair-copulas (bivariate copulas). In this paper, we allow the dependence parameters of the pair-copulas in a D-vine decomposition to be potentially time-varying, following a nonlinear restricted ARMA(1,m) process, in order to obtain a very flexible dependence model for applications to multivariate financial return data. We investigate the dependence among the broad stock market indexes from Germany (DAX), France (CAC 40), Britain (FTSE 100), the United States (S&P 500) and Brazil (IBOVESPA) both in a crisis and in a non-crisis period. We find evidence of stronger dependence among the indexes in bear markets. Surprisingly, though, the dynamic D-vine copula indicates the occurrence of a sharp decrease in dependence between the indexes FTSE and CAC in the beginning of 2011, and also between CAC and DAX during mid-2011 and in the beginning of 2008, suggesting the absence of contagion in these cases. We also evaluate the dynamic D-vine copula with respect to Value-at-Risk (VaR) forecasting accuracy in crisis periods. The dynamic D-vine outperforms the static D-vine in terms of predictive accuracy for our real data sets.

Young driver risk-taking research: the state of the art. Interim report.

National Highway Traffic Safety Administration, Office of Driver and Pedestrian Safety, Washington, D.C.

The development of an improved railroad-highway grade crossing risk factor. Executive summry report.

Ohio Department of Transportation, Columbus

The development of an improved railroad-highway grade crossing risk factor. Final report.

Ohio Department of Transportation, Columbus

Development of a methodology for accident causation research. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Manual for accident causation research.

National Highway Traffic Safety Administration, Washington, D.C.

Tri-level study: modification. Task 5: an examination of driver characteristics and collision producing errors of accident and traffic violation repeaters. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Statistical analyses of commercial vehicle accident factors. Volume II - summary report. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Comparison of California accident rates for single and double tractor-trailer combination trucks. Final report.

Federal Highway Administration, Washington, D.C.

Alcohol and highway safety 1978: a review of the state of knowledge (summary volume).

Mode of access: Internet.

Accident causation methodology development for the National Accident Sampling System: final report.

National Highway Traffic Safety Administration, Washington, D.C.

The effect of truck size and weight on accident experience and traffic operations. Volume IV: truck exposure classification by size and weight. Final report.

Federal Highway Administration, Washington, D.C.

Development of a systems risk methodology for single and multi-modal transportation systems. Final report.

Transportation Department, Research and Special Programs Administration, Washington, D.C.

Tri-level accident research study. Second annual report. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Techniques for predicting high-risk drivers for alcohol countermeasures. Volume II. User manual. Final report.

National Highway Traffic Safety Administration, Washington, D.C.