WorldCat Identities

Meitz, Mika

Overview
Works: 14 works in 24 publications in 1 language and 180 library holdings
Roles: Editor, Author, Thesis advisor
Publication Timeline
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Most widely held works by Mika Meitz
Essays in nonlinear time series econometrics( Book )

10 editions published in 2014 in English and held by 165 WorldCat member libraries worldwide

This edited collection concerns nonlinear economic relations that involve time. It is divided into four broad themes that all reflect the work and methodology of Professor Timo Teräsvirta, one of the leading scholars in the field of nonlinear time series econometrics. The themes are: Testing for linearity and functional form, specification testing and estimation of nonlinear time series models in the form of smooth transition models, model selection and econometric methodology, and finally applications within the area of financial econometrics. All these research fields include contributions that represent state of the art in econometrics such as testing for neglected nonlinearity in neural network models, time-varying GARCH and smooth transition models, STAR models and common factors in volatility modeling, semi-automatic general to specific model selection for nonlinear dynamic models, high-dimensional data analysis for parametric and semi-parametric regression models with dependent data, commodity price modeling, financial analysts earnings forecasts based on asymmetric loss function, local Gaussian correlation and dependence for asymmetric return dependence, and the use of bootstrap aggregation to improve forecast accuracy. Each chapter represents original scholarly work, and reflects the intellectual impact that Timo Teräsvirta has had and will continue to have, on the profession
Parameter estimation in nonlinear AR-GARCH models by Mika Meitz( )

1 edition published in 2008 in English and held by 2 WorldCat member libraries worldwide

Parameter estimation in nonlinear AR-GARCH models by Mika Meitz( )

2 editions published between 2008 and 2010 in English and held by 2 WorldCat member libraries worldwide

This paper develops an asymptotic estimation theory for nonlinear autoregressive models with conditionally heteroskedastic errors. We consider a general nonlinear autoregression of order p (AR(p)) with the conditional variance specified as a general nonlinear first order generalized autoregressive conditional heteroskedasticity (GARCH(1,1)) model. We do not require the rescaled errors to be independent, but instead only to form a stationary and ergodic martingale difference sequence. Strong consistency and asymptotic normality of the global Gaussian quasi maximum likelihood (QML) estimator are established under conditions comparable to those recently used in the corresponding linear case. To the best of our knowledge, this paper provides the first results on consistency and asymptotic normality of the QML estimator in nonlinear autoregressive models with GARCH errors
Testing for predictability in a noninvertible ARMA model by Markku Lanne( )

1 edition published in 2012 in English and held by 1 WorldCat member library worldwide

We develop likelihood-based tests for autocorrelation and predictability in a first order non-Gaussian and noninvertible ARMA model. Tests based on a special case of the general model, referred to as an all-pass model, are also obtained. Data generated by an all-pass process are uncorrelated but, in the non-Gaussian case, dependent and nonlinearly predictable. Therefore, in addition to autocorrelation the proposed tests can also be used to test for nonlinear predictability. This makes our tests different from their previous counterparts based on conventional invertible ARMA models. Unlike in the invertible case, our tests can also be derived by standard methods that lead to chi-squared or standard normal limiting distributions. A further convenience of the noninvertible ARMA model is that, to some extent, it can allow for conditional heteroskedasticity in the data which is useful when testing for predictability in economic and financial data. This is also illustrated by our empirical application to U.S. stock returns, where our tests indicate the presence of nonlinear predictability. -- Non-Gaussian time series ; noninvertible ARMA model ; all-pass process
Parameter estimation in nonlinear AR-GARCH models by Mika Meitz( Book )

1 edition published in 2008 in English and held by 1 WorldCat member library worldwide

Identification and estimation of non-Gaussian structural vector autoregressions by Markku Lanne( )

1 edition published in 2015 in English and held by 1 WorldCat member library worldwide

Testing for predictability in a noninvertible ARMA model by Markku Lanne( )

1 edition published in 2012 in English and held by 1 WorldCat member library worldwide

Maximum likelihood estimation of a noninvertible ARMA model with autoregressive conditional heteroskedasticity by Mika Meitz( )

1 edition published in 2012 in English and held by 1 WorldCat member library worldwide

We consider maximum likelihood estimation of a particular noninvertible ARMA model with autoregressive conditionally heteroskedastic (ARCH) errors. The model can be seen as an extension to so-called all-pass models in that it allows for autocorrelation and for more fl exible forms of conditional heteroskedasticity. These features may be attractive especially in economic and financial applications. Unlike in previous literature on maximum likelihood estimation of noncausal and/or noninvertible ARMA models and all-pass models, our estimation theory does allow for Gaussian innovations. We give conditions under which a strongly consistent and asymptotically normally distributed solution to the likelihood equations exists, and we also provide a consistent estimator of the limiting covariance matrix. -- maximum likelihood estimation ; autoregressive moving average ; ARMA ; autoregressive conditional heteroskedasticity ; ARCH ; noninvertible ; noncausal ; all-pass ; nonminimum phase
A Gaussian mixture autoregressive model for univariate time series by Leena Kalliovirta( )

1 edition published in 2012 in English and held by 1 WorldCat member library worldwide

Gaussian mixture vector autoregression by Leena Kalliovirta( )

1 edition published in 2014 in English and held by 1 WorldCat member library worldwide

A note on the geometric ergodicity of a nonlinear AR-ARCH model by Mika Meitz( )

1 edition published in 2010 in English and held by 1 WorldCat member library worldwide

This note studies the geometric ergodicity of nonlinear autoregressive models with conditionally heteroskedastic errors. A nonlinear autoregression of order p (AR(p)) with the conditional variance specified as the conventional linear autoregressive conditional heteroskedasticity model of order q (ARCH(q)) is considered. Conditions under which the Markov chain representation of this nonlinear AR-ARCH model is geometrically ergodic and has moments of known order are provided. The obtained results complement those of Liebscher [Journal of Time Series Analysis, 26 (2005), 669-689] by showing how his approach based on the concept of the joint spectral radius of a set of matrices can be extended to establish geometric ergodicity in nonlinear autoregressions with conventional ARCH(q) errors
Maximum likelihood estimation of a noninvertible ARMA model with autoregressive conditional heteroskedasticity by Mika Meitz( )

1 edition published in 2011 in English and held by 1 WorldCat member library worldwide

Asymptotic properties of the QML estimator in a smooth transition GARCH (1,1) model by Kerem Tuzcuoğlu( Book )

1 edition published in 2010 in English and held by 1 WorldCat member library worldwide

Asymptotic properites of the QML estimator in linear and smooth transition autoregressive conditional duration models by Neslihan Sakarya( Book )

1 edition published in 2011 in English and held by 1 WorldCat member library worldwide

 
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Languages
English (24)