RT Report
T1 Bayesian analysis of realized matrix-exponentialGARCH models
A1 Asai, Manabu
A1 McAleer, Michael
AB The paper develops a new realized matrix-exponential GARCH (MEGARCH) model, which uses the information of returns and realized measure of co-volatility matrix simultaneously. The paper also considers an alternative multivariate asymmetric function to develop news impact curves. We consider Bayesian MCMC estimation to allow non-normal posterior distributions. For three US financial assets, we compare the realized MEGARCH models with existing multivariate GARCH class models. The empirical results indicate that the realized MEGARCH models outperform the other models regarding in-sample and out-of-sample performance. The news impact curves based on the posterior densities provide reasonable results.
PB Facultad de Ciencias Económicas y Empresariales. Instituto Complutense de Análisis Económico (ICAE)
SN 2341-2356
YR 2018
FD 2018
LK https://hdl.handle.net/20.500.14352/17409
UL https://hdl.handle.net/20.500.14352/17409
LA eng
DS Docta Complutense
RD 10 abr 2025