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~accessRights:"free"
~isPartOf:"CESifo working papers"
~isPartOf:"Discussion paper / Tinbergen Institute"
~isPartOf:"Discussion paper series / LSE Financial Markets Group"
~isPartOf:"Discussion paper series / UCL Economics"
~isPartOf:"Discussion papers in economics"
~isPartOf:"Discussion papers of interdisciplinary research project 373"
~isPartOf:"Global COE Hi-Stat discussion paper series"
~language:"eng"
~person:"Gautier, Pieter"
~person:"Gil-Alaña, Luis A."
~person:"Heckman, James J."
~person:"Hinloopen, Jeroen"
~person:"Koopman, Siem Jan"
~person:"Pesaran, M. Hashem"
~subject:"EU-Staaten"
~subject:"Kreditrisiko"
~subject:"Monte-Carlo-Simulation"
~subject:"Schätzung"
~subject:"Statistische Verteilung"
~subject:"USA"
~subject:"United States"
~subject:"Volatilität"
~subject:"Zustandsraummodell"
~type:"book"
~type_genre:"Collection of articles written by one author"
~type_genre:"Handbuch"
~type_genre:"Non-commercial literature"
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61
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
Saved in:
62
Modeling trigonometric seasonal components for monthly economic time series
Hindrayanto, Irma
;
Aston, John A.D.
;
Koopman, Siem Jan
; …
-
2010
The basic structural time series model has been designed for the modelling and forecasting of seasonal economic time series. In this paper we explore a generalisation of the basic structural time series model in which the time-varying trigonometric terms associated with different seasonal...
Persistent link: https://www.econbiz.de/10011379642
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63
A dynamic multivariate heavy-tailed model for time-varying volatilities and correlations
Creal, Drew
;
Koopman, Siem Jan
;
Lucas, André
-
2010
We propose a new class of observation-driven time-varying parameter models for dynamic volatilities and correlations to handle time series from heavy-tailed distributions. The model adopts generalized autoregressive score dynamics to obtain a time-varying covariance matrix of the multivariate...
Persistent link: https://www.econbiz.de/10011380135
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64
Identifying all distinct sample p-p plots, with an application to the exact finite sample distribution of the L1-FCvM test statistic
Hinloopen, Jeroen
;
Wagenvoort, Rien
-
2010
P-p plots contain all the information that is needed for scale-invariant comparisons. Indeed, Empirical Distribution Function (EDF) tests translate sample p-p plots into a single number. In this paper we characterize the set of all distinct p-p plots for two balanced sample of size n absent...
Persistent link: https://www.econbiz.de/10011381382
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65
Systemic risk diagnostics
Schwaab, Bernd
;
Lucas, André
;
Koopman, Siem Jan
-
2010
, and the rest of the
world
. Controlling for global,region-specific, and industry effects, we construct coincident measures …
Persistent link: https://www.econbiz.de/10011382067
Saved in:
66
Observation driven mixed-measurement dynamic factor models with an application to credit risk
Creal, Drew
;
Schwaab, Bernd
;
Koopman, Siem Jan
;
Lucas, …
-
2011
This paper has been accepted for publication in the 'Review of Economics and Statistics'.We propose a dynamic factor model for mixed-measurement and mixed-frequency panel data. In this framework time series observations may come from a range of families of parametric distributions, may be...
Persistent link: https://www.econbiz.de/10011383248
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67
Numerically accelerated importance sampling for nonlinear non-Gaussian state space models
Koopman, Siem Jan
;
Lucas, André
;
Scharth, Marcel
-
2012
We introduce a new efficient importance sampler for nonlinear non-Gaussian state space models. We propose a general and efficient likelihood evaluation method for this class of models via the combination of numerical and Monte Carlo integration methods. Our methodology explores the idea that...
Persistent link: https://www.econbiz.de/10011386179
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68
Modeling dynamic volatilities and correlations under skewness and fat tails
Zhang, Xin
;
Creal, Drew
;
Koopman, Siem Jan
;
Lucas, André
-
2011
We propose a new model for dynamic volatilities and correlations of skewed and heavy-tailed data. Our model endows the Generalized Hyperbolic distribution with time-varying parameters driven by the score of the observation density function. The key novelty in our approach is the fact that the...
Persistent link: https://www.econbiz.de/10011386468
Saved in:
69
Time series models with a common stochastic variance for analysing economic time series
Koopman, Siem Jan
;
Bos, Charles S.
-
2002
Persistent link: https://www.econbiz.de/10001718624
Saved in:
70
Business and default cycles for credit risk
Koopman, Siem Jan
;
Lucas, André
-
2003
Persistent link: https://www.econbiz.de/10001792714
Saved in:
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