@techreport{Voev2007Dynamic,
abstract = {Modelling and forecasting the covariance of financial return series has always been a challenge due to the so-called curse of dimensionality. This paper proposes a methodology that is applicable in large dimensional cases and is based on a time series of realized covariance matrices. Some solutions are also presented to the problem of non-positive definite forecasts. This methodology is then compared to some traditional models on the basis of its forecasting performance employing Diebold-Mariano tests. We show that our approach is better suited to capture the dynamic features of volatilities and covolatilities compared to the sample covariance based models.},
address = {Konstanz},
author = {Valeri Voev},
copyright = {http://www.econstor.eu/dspace/Nutzungsbedingungen},
keywords = {330; Varianzanalyse; Zeitreihenanalyse; Kapitalertrag; Prognoseverfahren; Theorie},
language = {eng},
number = {2007,01},
publisher = {CoFE},
title = {Dynamic modeling of large dimensional covariance matrices},
type = {Discussion paper series // Zentrum f\"{u}r Finanzen und \"{O}konometrie, Universit\"{a}t Konstanz},
url = {http://hdl.handle.net/10419/32175},
year = {2007}
}
