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We discuss several multivariate extensions of the Multiplicative Error Model to take into account dynamic interdependence and contemporaneously correlated innovations (vector MEM or vMEM). We suggest copula functions to link Gamma marginals of the innovations, in a specification where past...
Persistent link: https://www.econbiz.de/10011755372
We discuss several multivariate extensions of the Multiplicative Error Model to take into account dynamic interdependence and contemporaneously correlated innovations (vector MEM or vMEM). We suggest copula functions to link Gamma marginals of the innovations, in a specification where past...
Persistent link: https://www.econbiz.de/10011654447
estimator for forecasting time series, with a special attention to GARCH and ACD models. The local large sample properties of …
Persistent link: https://www.econbiz.de/10005075728
baseline GARCH but not so relative to the range; there are relevant gains from modeling volatility trends and using realized …
Persistent link: https://www.econbiz.de/10005075734
The Multiplicative Error Model introduced by Engle (2002) for non-negative valued processes is specified as the product of a (conditionally autoregressive) scale factor and an innovation process with positive support. In this paper we propose a multivariate extension of such a model, by taking...
Persistent link: https://www.econbiz.de/10005731544
This paper assesses the performance of volatility forecasting using focused selection and combination strategies to include relevant explanatory variables in the forecasting model. The focused selection/combination strategies consist of picking up the model that minimizes the estimated risk...
Persistent link: https://www.econbiz.de/10005731546