Essays in nonlinear time series econometrics edited by Niels Haldrup, Mika Meitz, and Pentti Saikkonen

Colaborador(es): Idioma: Inglés Detalles de publicación: Oxford (Inglaterra) Oxford University Press 2014Edición: 5th edDescripción: xxiii, 367 páginas ilustraciones, gráficasISBN:
  • 0199679959
  • 9780199679959
Tema(s):
Contenidos:
Pt. I Testing for Linearity and Functional Form. -- 1.Testing for Neglected Nonlinearity Using Twofold Unidentified Models under the Null and Hexic Expansions / Jin Seo Cho, Isao Ishida, and Halbert White. -- 2.Consistent Testing of Functional Form in Time Series Models / James Davidson and Andreea G. Halunga. -- 3.Linearity Testing for Trending Data with an Application of the Wild Bootstrap / Robinson Kruse and Rickard Sandberg. -- pt. II Smooth Transition Models. -- 4.Common Nonlinearities in Multiple Series of Stock Market Volatility / Heather M. Anderson and Farshid Vahid. -- 5.Balance Sheet Recessions and Time-Varying Coefficients in a Phillips Curve Relationship: An Application to Finnish Data / Katarina Juselius and Mikael Juselius. -- 6.Modeling Time-Varying Volatility in Financial Returns: Evidence from the Bond Markets / Cristina Amado and Helina Laakkonen. -- pt. III Model Selection and Econometric Methodology. -- 7.Semi-Automatic Nonlinear Model Selection / Jennifer L. Castle and David F. Hendry. -- 8.Fundamental Problems with Nonfundamental Shocks / Helmut Lutkepohl
9.Penalized Estimation of Semi-Parametric Additive Time-Series Models / Marcelo C. Medeiros and Eduardo F. Mendes. -- 10.Oracle Efficient Estimation and Forecasting With the Adaptive Lasso and the Adaptive Group Lasso in Vector Autoregressions / Laurent A.F. Callot and Anders Bredahl Kock. -- pt. IV Applied Financial Econometrics. -- 11.Modeling Commodity Prices with Dynamic Conditional Beta / Robert Engle. -- 12.Bias and Uncertainty in Analyst Earnings Expectations at Different Forecast Horizons / Marco Aiolfi, Marius Rodriguez, and Allan Timmermann. -- 13.Asymmetric Dependence Patterns in Financial Returns: An Empirical Investigation Using Local Gaussian Correlation / Bard Støve and Dag Tjøstheim. -- 14.Bagging Constrained Equity Premium Predictors / Eric Hillebrand, Tae-Hwy Lee, and Marcelo C. Medeiros.
Resumen: 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.
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Incluye índice

Pt. I Testing for Linearity and Functional Form. -- 1.Testing for Neglected Nonlinearity Using Twofold Unidentified Models under the Null and Hexic Expansions / Jin Seo Cho, Isao Ishida, and Halbert White. -- 2.Consistent Testing of Functional Form in Time Series Models / James Davidson and Andreea G. Halunga. -- 3.Linearity Testing for Trending Data with an Application of the Wild Bootstrap / Robinson Kruse and Rickard Sandberg. -- pt. II Smooth Transition Models. -- 4.Common Nonlinearities in Multiple Series of Stock Market Volatility / Heather M. Anderson and Farshid Vahid. -- 5.Balance Sheet Recessions and Time-Varying Coefficients in a Phillips Curve Relationship: An Application to Finnish Data / Katarina Juselius and Mikael Juselius. -- 6.Modeling Time-Varying Volatility in Financial Returns: Evidence from the Bond Markets / Cristina Amado and Helina Laakkonen. -- pt. III Model Selection and Econometric Methodology. -- 7.Semi-Automatic Nonlinear Model Selection / Jennifer L. Castle and David F. Hendry. -- 8.Fundamental Problems with Nonfundamental Shocks / Helmut Lutkepohl

9.Penalized Estimation of Semi-Parametric Additive Time-Series Models / Marcelo C. Medeiros and Eduardo F. Mendes. -- 10.Oracle Efficient Estimation and Forecasting With the Adaptive Lasso and the Adaptive Group Lasso in Vector Autoregressions / Laurent A.F. Callot and Anders Bredahl Kock. -- pt. IV Applied Financial Econometrics. -- 11.Modeling Commodity Prices with Dynamic Conditional Beta / Robert Engle. -- 12.Bias and Uncertainty in Analyst Earnings Expectations at Different Forecast Horizons / Marco Aiolfi, Marius Rodriguez, and Allan Timmermann. -- 13.Asymmetric Dependence Patterns in Financial Returns: An Empirical Investigation Using Local Gaussian Correlation / Bard Støve and Dag Tjøstheim. -- 14.Bagging Constrained Equity Premium Predictors / Eric Hillebrand, Tae-Hwy Lee, and Marcelo C. Medeiros.

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.

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