The uncertainty of conditional returns, volatilities and correlations in DCC models Articles uri icon

publication date

  • August 2016

start page

  • 170

end page

  • 185

volume

  • 100

international standard serial number (ISSN)

  • 0167-9473

electronic international standard serial number (EISSN)

  • 1872-7352

abstract

  • Point forecasts can be obtained at each moment of time when forecasting conditional correlations that evolve according to a Dynamic Conditional Correlation (DCC) model. However, measuring the uncertainty associated with these forecasts is of interest in many situations. The finite sample properties of a bootstrap procedure for approximating the forecast densities of future returns, volatilities and correlations, are analyzed using simulated data and illustrated by obtaining conditional forecast intervals and regions in the context of a three-dimensional system of daily exchange rate returns. (C) 2015 Elsevier B.V. All rights reserved.

keywords

  • multivariate garch models; risk; heteroskedasticity; heteroscedasticity; estimators; variance; tests; simulation; prediction; regression; bootstrap forecast intervals; dynamic conditional correlation; exchange rates; forecast regions; realized correlation; resampling methods