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Models with Time-varying Mean and Variance: A Robust Analysis of U.S. Industrial Production
Bos, Charles S.; Koopman, Siem Jan - 2010
Many seasonal macroeconomic time series are subject to changes in their means and variances over a long time horizon. In this paper we propose a general treatment for the modelling of time-varying features in economic time series. We show that time series models with mean and variance functions...
Persistent link: https://www.econbiz.de/10010326058
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Models with time-varying mean and variance : a robust analysis of US industrial production
Bos, Charles S.; Koopman, Siem Jan - 2010
Many seasonal macroeconomic time series are subject to changes in their means and variances over a long time horizon. In this paper we propose a general treatment for the modelling of time-varying features in economic time series. We show that time series models with mean and variance functions...
Persistent link: https://www.econbiz.de/10011379641
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Outlier detection in structural time series models : the indicator saturation approach
Marczak, Martyna; Proietti, Tommaso - 2014
Structural change affects the estimation of economic signals, like the underlying growth rate or the seasonally adjusted series. An important issue, which has at- tracted a great deal of attention also in the seasonal adjustment literature, is its detection by an expert procedure. The...
Persistent link: https://www.econbiz.de/10010402941
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Price Dividend Ratio and Long-Run Stock Returns : A Score Driven State Space Model
Delle Monache, Davide - 2020
In this paper we develop a general framework to analyze state space models with time-varying system matrices where time variation is driven by the score of the conditional likelihood. We derive a new filter that allows for the simultaneous estimation of the state vector and of the time-varying...
Persistent link: https://www.econbiz.de/10012842441
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Price dividend ratio and long-run stock returns : a score driven state space model
Delle Monache, Davide; Petrella, Ivan; Venditti, Fabrizio - 2020
In this paper we develop a general framework to analyze state space models with timevarying system matrices where time variation is driven by the score of the conditional likelihood. We derive a new filter that allows for the simultaneous estimation of the state vector and of the time-varying...
Persistent link: https://www.econbiz.de/10012156426
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Predictability, Real Time Estimation, and the Formulation of Unobserved Components Models
Proietti, Tommaso - 2019
The formulation of unobserved components models raises some relevant interpretative issues, owing to the existence of alternative observationally equivalent specifi cations, differing for the timing of the disturbances and their covariance matrix. We illustrate them with reference to unobserved...
Persistent link: https://www.econbiz.de/10014107235
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Observation-driven filters for timeseries with stochastic trends and mixed causal non-causal dynamics
Blasques, Francisco; Koopman, Siem Jan; Mingoli, Gabriele - 2023
the forecasting accuracy against competitive alternative methods and conclude that our model-based forecasts outperform …
Persistent link: https://www.econbiz.de/10014380706
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Using wavelets for time series forecasting: Does it pay off?
Schlüter, Stephan; Deuschle, Carola - 2010
forecasting horizon we either favour a denoising step plus an ARIMA forecast or an multiscale wavelet decomposition plus an ARIMA … incorporating the wavelet transform in existing forecasting methods can improve their quality. The article aims to verify this by … characteristics. We find that wavelets do improve the forecasting quality. Depending on the data's characteristics and on the …
Persistent link: https://www.econbiz.de/10010300727
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Large mixed-frequency VARs with a parsimonious time-varying parameter structure
Götz, Thomas B.; Hauzenberger, Klemens - 2018
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
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Diffusion index model specification and estimation using mixed frequency datasets
Kim, Kihwan; Swanson, Norman R. - 2013
. Preliminary evidence that mixed frequency based forecasting models yield improvements over standard fixed frequency models is …
Persistent link: https://www.econbiz.de/10009766691