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Testing The Structure Of Conditional Correlations In Multivariate Garch Models
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Book Synopsis Testing the Structure of Conditional Correlations in Multivariate GARCH Models by : Nadine McCloud
Download or read book Testing the Structure of Conditional Correlations in Multivariate GARCH Models written by Nadine McCloud and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: We introduce a class of generally applicable specification tests for constant and dynamic structures of conditional correlations in multivariate GARCH models. The tests are robust to the presence of time-varying higher-order conditional moments of unknown form and are pure significance tests. The tests can identify linear and nonlinear misspecifications in conditional correlations. Our approach does not necessitate a particular parameter estimation method and distributional assumption on the error process. The asymptotic distribution of the tests is invariant to the uncertainty in parameter estimation. We assess the finite sample performance of our tests using simulated and real data.
Book Synopsis Average Conditional Correlation and Tree Structures for Multivariate GARCH Models by : Francesco Audrino
Download or read book Average Conditional Correlation and Tree Structures for Multivariate GARCH Models written by Francesco Audrino and published by . This book was released on 2004 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a simple class of multivariate GARCH models, allowing for time-varying conditional correlations. Estimates for time-varying conditional correlations are constructed by means of a convex combination of averaged correlations (across all series) and dynamic realized (historical) correlations. Our model is very parsimonious. Estimation is computationally feasible in very large dimensions without resorting to any variance reduction technique. We back-test the models on a six-dimensional exchange-rate time series using different goodness-of-fit criteria and statistical tests. We collect empirical evidence of their strong predictive power, also in comparison to alternative benchmark procedures.
Author :Torben Gustav Andersen Publisher :Springer Science & Business Media ISBN 13 :3540712976 Total Pages :1045 pages Book Rating :4.5/5 (47 download)
Book Synopsis Handbook of Financial Time Series by : Torben Gustav Andersen
Download or read book Handbook of Financial Time Series written by Torben Gustav Andersen and published by Springer Science & Business Media. This book was released on 2009-04-21 with total page 1045 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Financial Time Series gives an up-to-date overview of the field and covers all relevant topics both from a statistical and an econometrical point of view. There are many fine contributions, and a preamble by Nobel Prize winner Robert F. Engle.
Book Synopsis Modelling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH Model by : Annastiina Silvennoinen
Download or read book Modelling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH Model written by Annastiina Silvennoinen and published by . This book was released on 2009 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we propose a multivariate GARCH model with a time-varying conditional correlation structure. The new Double Smooth Transition Conditional Correlation GARCH model extends the Smooth Transition Conditional Correlation GARCH model of Silvennoinen and Terasvirta (2005) by including another variable according to which the correlations change smoothly between states of constant correlations. A Lagrange multiplier test is derived to test the constancy of correlations against the DSTCC-GARCH model, and another one to test for another transition in the STCC-GARCH framework. In addition, other specification tests, with the aim of aiding the model building procedure, are considered. Analytical expressions for the test statistics and the required derivatives are provided. The model is applied to a selection of world stock indices, and it is found that time is an important factor affecting correlations between them.
Download or read book GARCH Models written by Christian Francq and published by John Wiley & Sons. This book was released on 2019-03-21 with total page 714 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides a comprehensive and updated study of GARCH models and their applications in finance, covering new developments in the discipline This book provides a comprehensive and systematic approach to understanding GARCH time series models and their applications whilst presenting the most advanced results concerning the theory and practical aspects of GARCH. The probability structure of standard GARCH models is studied in detail as well as statistical inference such as identification, estimation, and tests. The book also provides new coverage of several extensions such as multivariate models, looks at financial applications, and explores the very validation of the models used. GARCH Models: Structure, Statistical Inference and Financial Applications, 2nd Edition features a new chapter on Parameter-Driven Volatility Models, which covers Stochastic Volatility Models and Markov Switching Volatility Models. A second new chapter titled Alternative Models for the Conditional Variance contains a section on Stochastic Recurrence Equations and additional material on EGARCH, Log-GARCH, GAS, MIDAS, and intraday volatility models, among others. The book is also updated with a more complete discussion of multivariate GARCH; a new section on Cholesky GARCH; a larger emphasis on the inference of multivariate GARCH models; a new set of corrected problems available online; and an up-to-date list of references. Features up-to-date coverage of the current research in the probability, statistics, and econometric theory of GARCH models Covers significant developments in the field, especially in multivariate models Contains completely renewed chapters with new topics and results Handles both theoretical and applied aspects Applies to researchers in different fields (time series, econometrics, finance) Includes numerous illustrations and applications to real financial series Presents a large collection of exercises with corrections Supplemented by a supporting website featuring R codes, Fortran programs, data sets and Problems with corrections GARCH Models, 2nd Edition is an authoritative, state-of-the-art reference that is ideal for graduate students, researchers, and practitioners in business and finance seeking to broaden their skills of understanding of econometric time series models.
Book Synopsis Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH by : Robert F. Engle
Download or read book Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH written by Robert F. Engle and published by . This book was released on 2001 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we develop the theoretical and empirical properties of a new class of multi-variate GARCH models capable of estimating large time-varying covariance matrices, Dynamic Conditional Correlation Multivariate GARCH. We show that the problem of multivariate conditional variance estimation can be simplified by estimating univariate GARCH models for each asset, and then, using transformed residuals resulting from the first stage, estimating a conditional correlation estimator. The standard errors for the first stage parameters remain consistent, and only the standard errors for the correlation parameters need be modified. We use the model to estimate the conditional covariance of up to 100 assets using S&P 500 Sector Indices and Dow Jones Industrial Average stocks, and conduct specification tests of the estimator using an industry standard benchmark for volatility models. This new estimator demonstrates very strong performance especially considering ease of implementation of the estimator
Book Synopsis Specification Testing of Garch Regression Models by : Wasel Bin Shadat
Download or read book Specification Testing of Garch Regression Models written by Wasel Bin Shadat and published by . This book was released on 2011 with total page 237 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Three Essays on Modeling Conditional Correlation by : Kevin Sheppard
Download or read book Three Essays on Modeling Conditional Correlation written by Kevin Sheppard and published by . This book was released on 2004 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book GARCH Models written by Christian Francq and published by John Wiley & Sons. This book was released on 2011-06-24 with total page 469 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive and systematic approach to understanding GARCH time series models and their applications whilst presenting the most advanced results concerning the theory and practical aspects of GARCH. The probability structure of standard GARCH models is studied in detail as well as statistical inference such as identification, estimation and tests. The book also provides coverage of several extensions such as asymmetric and multivariate models and looks at financial applications. Key features: Provides up-to-date coverage of the current research in the probability, statistics and econometric theory of GARCH models. Numerous illustrations and applications to real financial series are provided. Supporting website featuring R codes, Fortran programs and data sets. Presents a large collection of problems and exercises. This authoritative, state-of-the-art reference is ideal for graduate students, researchers and practitioners in business and finance seeking to broaden their skills of understanding of econometric time series models.
Book Synopsis Dynamic Conditional Correlation by : Robert F. Engle
Download or read book Dynamic Conditional Correlation written by Robert F. Engle and published by . This book was released on 2000 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH. by : Robert F. Engle
Download or read book Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH. written by Robert F. Engle and published by . This book was released on 2008 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper, we develop the theoretical and empirical properties of a new class of multivariate GARCH models capable of estimating large time-varying covariance matrices, Dynamic Conditional Correlation Multivariate GARCH. We show that the problem of multivariate conditional variance estimation can be simplified by estimating univariate GARCH models for each asset, and then, using transformed residuals resulting from the first stage, estimating a conditional correlation estimator. The standard errors for the first stage parameters remain consistent, and only the standard errors for the correlation parameters need to be modified. We use the model to estimate the conditional covariance of up to 100 assets using Samp;P 500 Sector Indices and Dow Jones Industrial Average stocks, and conduct specification tests of the estimator using an industry standard benchmark for volatility models. This new estimator demonstrates very strong performance especially considering ease of implementation of the estimator.
Book Synopsis Inference and Testing on the Boundary in Extended Constant Conditional Correlation GARCH Models by : Rasmus Søndergaard Pedersen
Download or read book Inference and Testing on the Boundary in Extended Constant Conditional Correlation GARCH Models written by Rasmus Søndergaard Pedersen and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Multivariate GARCH Model with Time-Varying Correlations by : Yiu Kuen Tse
Download or read book A Multivariate GARCH Model with Time-Varying Correlations written by Yiu Kuen Tse and published by . This book was released on 2000 with total page 30 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we propose a new multivariate GARCH model with time-varying correlations. We adopt the vech representation based on the conditional variances and the conditional correlations. While each conditional-variance term is assumed to follow a univariate GARCH formulation, the conditional-correlation matrix is postulated to follow an autoregressive moving average type of analogue. By imposing some suitable restrictions on the conditional-correlation-matrix equation, we construct a MGARCH model in which the conditional-correlation matrix is guaranteed to be positive definite during the optimisation. Thus, our new model retains the intuition and interpretation of the univariate GARCH model and yet satisfies the positive-definite condition as found in the constant-correlation and BEKK models. We report some Monte Carlo results on the finite-sample distributions of the MLE of the varying-correlation MGARCH model. The new model is applied to some real data sets. It is found that extending the constant-correlation model to allow for time-varying correlations provides some interesting time histories that are not available in a constant-correlation model.
Book Synopsis An Extended Constant Conditional Correlation GARCH Model and Its Fourth-moment-structure by : Changli He
Download or read book An Extended Constant Conditional Correlation GARCH Model and Its Fourth-moment-structure written by Changli He and published by . This book was released on 2002 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The constant conditional correlation GARCH model is probably the most frequently applied multivariate GARCH model. In this paper we consider an extension to this model and examine its fourth-moment structure. The extension, first considered by Jeantheau (1998), is motivated by the result found and discussed in the paper that the squared observations from the extended model have a rich autocorrelation structure. This means that already the first-order model is capable of reproducing a whole variety of autocorrelation structures observed in financial return series. These autocorrelations are derived for the first and the second-order constant conditional correlation GARCH model. The usefulness of the theoretical results of the paper is demonstrated by reconsidering an empirical example that appeared in the original paper on the constant conditional correlation GARCH model. -- Autoregressive conditional heteroskedasticity ; moment structure of GARCH ; multivariate conditional heteroskedasticity ; volatility dynamics
Book Synopsis Change-Point Detection in the Covariance Structure of Multivariate Volatility Models by : Marco R. Barassi
Download or read book Change-Point Detection in the Covariance Structure of Multivariate Volatility Models written by Marco R. Barassi and published by . This book was released on 2017 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose semi-parametric CUSUM tests to detect a change point in the covariance structure of non-linear multivariate models with dynamically evolving volatilities and correlations. The asymptotic distributions of the proposed statistics are derived under mild conditions. We discuss the applicability of our method to the most often used models, including constant conditional correlation (CCC), dynamic conditional correlation (DCC), factor, asymmetric DCC and BEKK. Our simulations show that, even though the near-unit root property distorts the size and power of tests, de-volatizing the data by means of appropriate multivariate GARCH models can correct such distortions. We apply the semi-parametric CUSUM tests in the attempt to date the occurrence of financial contagion during the great recession.
Book Synopsis A General Multivariate Threshold GARCH Model for Dynamic Correlations by : Francesco Audrino
Download or read book A General Multivariate Threshold GARCH Model for Dynamic Correlations written by Francesco Audrino and published by . This book was released on 2005 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt: We propose a new multivariate DCC-GARCH model that extends existing approaches by admitting multivariate thresholds in conditional volatilities and conditional correlations. Model estimation is numerically feasible in large dimensions and positive semi-definiteness of conditional covariance matrices is naturally ensured by the pure model structure. Conditional thresholds in volatilities and correlations are estimated from the data, together with all other model parameters. We study the performance of our approach in some Monte Carlo simulations, where it is shown that the model is able to fit correctly a GARCH-type dynamics and a complex threshold structure in conditional volatilities and correlations of simulated data. In a real data application to international equity markets, we observe estimated conditional volatilities that are strongly influenced by GARCH-type and multivariate threshold effects. Conditional correlations, instead, are determined by simple threshold structures where no GARCH-type effect could be identified.
Book Synopsis Structural Vector Autoregressive Analysis by : Lutz Kilian
Download or read book Structural Vector Autoregressive Analysis written by Lutz Kilian and published by Cambridge University Press. This book was released on 2017-11-23 with total page 757 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses the econometric foundations of structural vector autoregressive modeling, as used in empirical macroeconomics, finance, and related fields.
