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Robust inference intime-varying structural VAR models : the DC-Cholesky multivariate stochasticvolatility model
Hartwig, Benny - 2020
Cholesky multivariate stochastic volatility model.It establishes that systematically different dynamic restrictions are imposed … divergent when volatility clusters idiosyncratically.It is illustrated that this property is important for empirical …
Persistent link: https://www.econbiz.de/10012250452
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Inference for structural impulse responses in SVAR-GARCH models
Bruder, Stefan - 2018
Conditional heteroskedasticity can be exploited to identify the structural vector autoregressions (SVAR) but the implications for inference on structural impulse responses have not been investigated in detail yet. We consider the conditionally heteroskedastic SVAR-GARCH model and propose a...
Persistent link: https://www.econbiz.de/10011817166
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Multivariate Time Series Forecasting : Nonparametric Vector Autoregression Using NNS
Viole, Fred - 2019
Persistent link: https://www.econbiz.de/10012859140
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Multivariate Least Squares Forecasting Averaging by Vector Autoregressive Models
Liao, Jen-Che - 2016
This paper proposes a multivariate least squares Mallows averaging approach to the issue of forecast combination by vector autoregressive (VAR) model fitting. Our approach extends the current literature on frequentist least squares model/forecast averaging methods, in particular Hansen (2008),...
Persistent link: https://www.econbiz.de/10012984785
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Volatility spillover and multivariate volatility impulse response analysis of GFC news events
Allen, David E.; McAleer, Michael; Powell, Robert; … - 2016
Hafner and Herwartz (2006) analysis of multivariate GARCH models using volatility impulse response analysis. We use two sets … of data, daily realized volatility estimates taken from the Oxford Man RV library, running from the beginning of 2000 to …) and the subsequent European Sovereign Debt Crisis (ESDC). The spillover index captures the transmission of volatility to …
Persistent link: https://www.econbiz.de/10011556166
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Shortcomings of a parametric VaR approach and nonparametric improvements based on a non-stationary return series model
Gürtler, Marc; Rauh, Ronald - 2009 - This Version: 2009-09-09
A non-stationary regression model for financial returns is examined theoretically in this paper. Volatility dynamics …. -- heteroscedastic asset returns ; non-stationarity ; nonparametric regression ; volatility ; innovation modelling ; asymmetric heavy …
Persistent link: https://www.econbiz.de/10009487233
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Shortcomings of a Parametric VaR Approach and Nonparametric Improvements Based on a Non-Stationary Return Series Model
Gürtler, Marc - 2009
volatility dynamics are modelled both exogenously and deterministic, captured by a nonparametric regression-type approach …. Consistency and asymptotic normality of a symmetric and of a one-sided kernel estimator of volatility are outlined with remarks on …
Persistent link: https://www.econbiz.de/10013159079
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Testing for Parameter Restrictions in a Stationary VAR Model : A Bootstrap Alternative
Kim, Jae H. - 2014
This paper proposes the use of the bootstrap when the system Wald test is employed to test for linear restrictions in a stationary vector autoregressive (VAR) model. The bootstrap test is conducted using the generalized least square estimator for VAR parameters, which takes account of...
Persistent link: https://www.econbiz.de/10013058819
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SVARs in the frequency domain using a continuum of restrictions
Guay, Alain; Pelgrin, Florian - 2021 - This version: June 15, 2021
This paper proposes a joint methodology for the identification and inference of structural vector autoregressive models in the frequency domain. We show that identifying restrictions can be written naturally as an asymptotic least squares problem (Gourieroux, Monfort and Trognon, 1985) in which...
Persistent link: https://www.econbiz.de/10012697868
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Balanced bootstrap joint confidence bands for structural impulse response functions
Bruder, Stefan; Wolf, Michael - 2017
Constructing joint confidence bands for structural impulse response functions based on a VAR model is a difficult task because of the non-linear nature of such functions. We propose new joint confidence bands that cover the entire true structural impulse response function up to a chosen maximum...
Persistent link: https://www.econbiz.de/10011630774