We propose a new method for multivariate forecasting which combines the Generalized Dynamic Factor Model (GDFM) and the multivariate Generalized Autoregressive Conditionally Heteroskedastic (GARCH) model. We assume that the dynamic common factors are conditionally heteroskedastic. The GDFM,...

We propose a new model for volatility forecasting which combines the Generalized Dynamic Factor Model (GDFM) and the GARCH model. The GDFM, applied to a large number of series, captures the multivariate information and disentangles the common and the idiosyncratic part of each series of returns....

We propose a new model for volatility forecasting which combines the Generalized Dynamic Factor Model (GDFM) and the GARCH model. The GDFM, applied to a large number of series, captures the multivariate information and disentangles the common and the idiosyncratic part of each series of returns....

We propose a new method for multivariate forecasting which combines the Generalized Dynamic Factor Model (GDFM) and the multivariate Generalized Autoregressive Conditionally Heteroskedastic (GARCH) model. We assume that the dynamic common factors are conditionally heteroskedastic. The GDFM,...

Building on the growing evidence on the importance of large data sets for empirical macroeconomic modeling, we estimate a large-scale FAVAR model for 18 OECD member countries. We quantify the global effects of economic policy uncertainty shocks and check whether the signs, the magnitude, and the...

Building on the growing evidence on the importance of large data sets for empirical macroeconomic modeling, we estimate a large-scale FAVAR model for 18 OECD member countries. We quantify the global effects of economic policy uncertainty shocks and check whether the signs, the magnitude, and the...

Building on the growing evidence on the importance of large data sets for empirical macroe-conomic modeling, we estimate a large-scale FAVAR model for 18 OECD member countries. We quantify the global effects of economic policy uncertainty shocks and check whether the signs, the magnitude, and...

This paper provides the first study of foreign investors' trading in a sizeable European emerging stock market, using a combination of daily and monthly complete data collected at the destination. It also introduces the structural conditional correlation (SCC) methodology to identify the...

This paper investigates the capital market relations between Euroland and the USA from 1990 until 2006. Formally based on the uncovered interest rate parity (UIP), backward recursive estimations establish a long-run equilibrium between European and US government bond yields. Since the mid-1990s...

The present paper embarks on an analysis of interactions between the US and Euroland in the capital, foreign exchange, money and stock markets from 1994 until 2006. Considering influences on financial market volatility, the estimations are carried out in multivariate EGARCH models using...