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framework is a bivariate volatility model, where volatility spillovers of either positive or negative sign are allowed for. Our … countries. Regarding the volatility spillovers, such spillovers from bond returns to those of stocks are stronger than the other … results show that by considering time-varying return and volatility spillovers when calculating the risk-minimising portfolio …
Persistent link: https://www.econbiz.de/10011663407
To simultaneously consider mixed-frequency time series, their joint dynamics, and possible structural changes, we introduce a time-varying parameter mixed-frequency VAR. To keep our approach from becoming too complex, we implement time variation parsimoniously: only the intercepts and a common...
Persistent link: https://www.econbiz.de/10011903709
The evolution of the yields of different maturities is related and can be described by a reduced number of commom latent factors. Multifactor interest rate models of the finance literature, common factor models of the time series literature and others use this property. Each model has advantages...
Persistent link: https://www.econbiz.de/10012053243
VARs. To address these issues, we propose VAR models with outlier-augmented stochastic volatility (SV) that combine … transitory and persistent changes in volatility. The resulting density forecasts are much less sensitive to outliers in the data … the pandemic period, as well as for earlier subsamples of relatively high volatility. In historical forecasting, outlier …
Persistent link: https://www.econbiz.de/10013184356
Persistent link: https://www.econbiz.de/10001399838
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-time data flow as well as parameter uncertainty and time-varying volatility. In addition, we develop a fast estimation algorithm …
Persistent link: https://www.econbiz.de/10012119825
There has been increased interest in the use of "big data" when it comes to forecasting macroeconomic time series such as private consumption or unemployment. However, applications on forecasting GDP are rather rare. In this paper we incorporate Google search data into a Bridge Equation Model, a...
Persistent link: https://www.econbiz.de/10011667109
Since the influential paper of Stock and Watson (2002), the dynamic factor model (DFM) has been widely used for forecasting macroeconomic key variables such as GDP. However, the DFM has some weaknesses. For nowcasting, the dynamic factor model is modified by using the mixed data sampling...
Persistent link: https://www.econbiz.de/10011566828
Multivariate distributional forecasts have become widespread in recent years. To assess the quality of such forecasts, suitable evaluation methods are needed. In the univariate case, calibration tests based on the probability integral transform (PIT) are routinely used. However, multivariate...
Persistent link: https://www.econbiz.de/10013472781