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~isPartOf:"CREATES research paper"
~isPartOf:"Discussion paper / Tinbergen Institute"
~isPartOf:"Discussion paper series / UCL Economics"
~isPartOf:"HWWA discussion paper"
~language:"eng"
~person:"Florax, Raymond J. G. M."
~person:"Gil-Alaña, Luis A."
~person:"Heckman, James J."
~person:"Koopman, Siem Jan"
~subject:"Credit risk"
~subject:"Kreditrisiko"
~subject:"Maximum likelihood estimation"
~subject:"Maximum-Likelihood-Schätzung"
~subject:"Meta-Analyse"
~subject:"Meta-analysis"
~subject:"Monte Carlo simulation"
~subject:"Schätzung"
~subject:"USA"
~subject:"United States"
~subject:"Volatilität"
~subject:"World"
~type:"book"
~type_genre:"Collection of articles written by one author"
~type_genre:"Handbuch"
~type_genre:"Non-commercial literature"
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31
In-sample confidence bands and out-of-sample forecast bands for time-varying parameters in observation driven models
Blasques, Francisco
;
Koopman, Siem Jan
;
Łasak, Katarzyna
; …
-
2015
We study the performance of alternative methods for calculating in-sample confidence and out of-sample forecast bands for time-varying parameters. The in-sample bands reflect parameter uncertainty only. The out-of-sample bands reflect both parameter uncertainty and innovation uncertainty. The...
Persistent link: https://www.econbiz.de/10011295703
Saved in:
32
Intraday stochastic volatility in discrete price changes : the dynamic Skellam model
Koopman, Siem Jan
;
Lit, Rutger
;
Lucas, André
-
2015
We introduce a dynamic Skellam model that measures stochastic volatility from high-frequency tick-by-tick discrete stock price changes. The likelihood function for our model is analytically intractable and requires Monte Carlo integration methods for its numerical evaluation. The proposed...
Persistent link: https://www.econbiz.de/10011295740
Saved in:
33
Unobserved components with stochastic volatility in U.S. inflation : estimation and signal extraction
Li, Mengheng
;
Koopman, Siem Jan
-
2018
We consider unobserved components time series models where the components are stochastically evolving over time and are subject to stochastic volatility. It enables the disentanglement of dynamic structures in both the mean and the variance of the observed time series. We develop a simulated...
Persistent link: https://www.econbiz.de/10011809984
Saved in:
34
Environmental regulation and competitiveness
Mulatu, Abay
;
Florax, Raymond J. G. M.
;
Withagen, Cees
-
2001
The potential relationship between domestic environmental regulation and internationalcompetitiveness has evoked various speculations. The common neoclassical train of thought is thatstrict environmental regulation is detrimental to the competitiveness of industry, and that itinduces phenomena...
Persistent link: https://www.econbiz.de/10011316876
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35
Time series models with a common stochastic variance for analysing economic time series
Koopman, Siem Jan
;
Bos, Charles S.
-
2002
The linear Gaussian state space model for which the common variance istreated as a stochastic time-varying variable is considered for themodelling of economic time series. The focus of this paper is on thesimultaneous estimation of parameters related to the stochasticprocesses of the mean part...
Persistent link: https://www.econbiz.de/10011327834
Saved in:
36
In-sample bounds for time-varying parameters of observation driven models
Blasques, Francisco
;
Koopman, Siem Jan
;
Łasak, Katarzyna
; …
-
2015
We study the performance of two analytical methods and one simulation method for computing in-sample confidence bounds for time-varying parameters. These in-sample bounds are designed to reflect parameter uncertainty in the associated filter. They are applicable to the complete class of...
Persistent link: https://www.econbiz.de/10010484891
Saved in:
37
Spillover dynamics for systemic risk measurement using spatial financial time series models
Blasques, Francisco
;
Koopman, Siem Jan
;
Lucas, André
; …
-
2014
We introduce a new model for time-varying spatial dependence. The model extends the well-known static spatial lag model. All parameters can be estimated conveniently by maximum likelihood. We establish the theoretical properties of the model and show that the maximum likelihood estimator for the...
Persistent link: https://www.econbiz.de/10010391531
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38
Macro, industry and frailty effects in defaults : the 2008 credit crisis in perspective
Koopman, Siem Jan
;
Lucas, André
;
Schwaab, Bernd
-
2010
We determine the magnitude and nature of systematic default risk using 1971{2009) default data from Moody's. We disentangle systematic risk factors due to business cycle effects, common default dynamics (frailty), and industry-specific dynamics (including contagion). To quantify the contribution...
Persistent link: https://www.econbiz.de/10011379607
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39
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
Saved in:
40
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
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