Download or read book Asymptotic Normality of the QML Estimator of the EGARCH 1 1 Model written by Dimitra Kyriakopoulou and published by . This book was released on 2015 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper investigates the asymptotic properties of the quasi-maximum likelihood estimator (QMLE) for the EGARCH model. Sufficient conditions under which the EGARCH(1,1) processes have stationary first and second order variance derivatives, and the expectation of the supremum norm of the second order log-likelihood derivative is finite are established. The existence of such moment bounds permits the establishment of the CLT of the score and the uniform SLLN of the hessian, so that the asymptotic normality of the QML estimators is proved.
Download or read book Asymptotic Theory for QMLE for Real Time GARCH 1 1 Model written by Ekaterina Smetanina and published by . This book was released on 2019 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt: We investigate the asymptotic properties of the Gaussian Quasi-Maximum-Likelihood estimator (QMLE) for the Real-time GARCH(1,1) model of Smetanina (2017). The developed theory relies on the new dependence measure developed in Wu (2005) and is substantially different to the standard asymptotic theory for GARCH models. We prove consistency and asymptotic normality for the parameter vector at the usual √T rate. Finally, as part of the developed theory we also demonstrate how convergence rates of uniform laws of large numbers can be established via the powerful maximal inequalities for high-dimensional heavy-tailed time series using uniform functional dependence measure.
Download or read book Asymptotic Properties of the QML Estimator in a Smooth Transition GARCH 1 1 Model written by Kerem Tuzcuoğlu and published by . This book was released on 2010 with total page 126 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 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.
Download or read book Asymptotic Theory for GARCH in mean Models written by Weiwei Liu and published by . This book was released on 2013 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: The GARCH-in-mean process is an important extension of the standard GARCH (generalized autoregressive conditional heteroscedastic) process and it has wide applications in economics and finance. The parameter estimation of GARCH type models usually involves the quasi-maximum likelihood (QML) technique as it produces consistent and asymptotically Gaussian distributed estimators under certain regularity conditions. For a pure GARCH model, such conditions were already found with asymptotic properties of its QML estimator well understood. However, when it comes to GARCH-in-mean models those properties are still largely unknown. The focus of this work is to establish a set of conditions under which the QML estimator of GARCH-in-mean models will have the desired asymptotic properties. Some general Markov model tools are applied to derive the result.
Download or read book Quasi Maximum Likelihood Estimation of Semi Strong GARCH Models written by Juan Carlos Escanciano and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This note proves the consistency and asymptotic normality of the Quasi-Maximum Likelihood Estimator (QMLE) of the parameters of a GARCH model with martingale difference centered squared innovations. The results are obtained under mild conditions and generalize and improve those in Lee and Hansen (1994) for the local QMLE in semi-strong GARCH(1,1) models. In particular, no restrictions on the conditional mean are imposed. Our proofs closely follow those in Francq and Zakoian (2004) for independent and identically distributed innovations.
Download or read book A Time Series Approach to Option Pricing written by Christophe Chorro and published by Springer. This book was released on 2014-12-04 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: The current world financial scene indicates at an intertwined and interdependent relationship between financial market activity and economic health. This book explains how the economic messages delivered by the dynamic evolution of financial asset returns are strongly related to option prices. The Black Scholes framework is introduced and by underlining its shortcomings, an alternative approach is presented that has emerged over the past ten years of academic research, an approach that is much more grounded on a realistic statistical analysis of data rather than on ad hoc tractable continuous time option pricing models. The reader then learns what it takes to understand and implement these option pricing models based on time series analysis in a self-contained way. The discussion covers modeling choices available to the quantitative analyst, as well as the tools to decide upon a particular model based on the historical datasets of financial returns. The reader is then guided into numerical deduction of option prices from these models and illustrations with real examples are used to reflect the accuracy of the approach using datasets of options on equity indices.
Download or read book A Closed Form Asymptotic Variance Covariance Matrix for the Quasi Maximum Likelihood Estimator of the Garch 1 1 Model written by Jun Ma and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper presents a closed-form asymptotic variance-covariance matrix of the Quasi-Maximum Likelihood Estimator (QMLE) for the GARCH(1,1) model. The robust 'sandwich' asymptotic variance matrix is shown to be a product of the function of higher moments of innovation and the inverse of negative expected Hessian, whose closed-form in terms of only model parameters is then derived via a local approximation. Taking inverse of it, the variance-covariance matrix is readily obtained. A Monte Carlo simulation experiment demonstrates that this analytical formula works well for both normal and non-normal innovations in admissible parameter regions.
Download or read book Essentials of Time Series for Financial Applications written by Massimo Guidolin and published by Academic Press. This book was released on 2018-05-29 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Essentials of Time Series for Financial Applications serves as an agile reference for upper level students and practitioners who desire a formal, easy-to-follow introduction to the most important time series methods applied in financial applications (pricing, asset management, quant strategies, and risk management). Real-life data and examples developed with EViews illustrate the links between the formal apparatus and the applications. The examples either directly exploit the tools that EViews makes available or use programs that by employing EViews implement specific topics or techniques. The book balances a formal framework with as few proofs as possible against many examples that support its central ideas. Boxes are used throughout to remind readers of technical aspects and definitions and to present examples in a compact fashion, with full details (workout files) available in an on-line appendix. The more advanced chapters provide discussion sections that refer to more advanced textbooks or detailed proofs. Provides practical, hands-on examples in time-series econometrics Presents a more application-oriented, less technical book on financial econometrics Offers rigorous coverage, including technical aspects and references for the proofs, despite being an introduction Features examples worked out in EViews (9 or higher)
Download or read book Statistics of Financial Markets written by Jürgen Franke and published by Springer Science & Business Media. This book was released on 2010-11-22 with total page 599 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistics of Financial Markets offers a vivid yet concise introduction to the growing field of statistical application in finance. The reader will learn the basic methods of evaluating option contracts, analysing financial time series, selecting portfolios and managing risks making realistic assumptions of the market behaviour. The focus is both on the fundamentals of mathematical finance and financial time series analysis and on applications to given problems of financial markets, thus making the book the ideal basis for lecturers, seminars and crash courses on the topic. For the third edition the book has been updated and extensively revised. Several new aspects have been included: new chapters on long memory models, copulae and CDO valuation. Practical exercises have been added, the solutions of which are provided in the book by S. Borak, W. Härdle and B. Lopez Cabrera (2010) ISBN 978-3-642-11133-4. “Both R and Matlab Code, together with the data, can be downloaded by clicking on the Additional Information tab labeled “R and Matlab Code,” which you will find on the right-hand side of the webpage.”
Download or read book Asymptotic Expansions of MM type and QML Estimators for the MA 1 with Mean Models written by Antonis Demos and published by . This book was released on 2009 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second order asymptotic expansions, of the Edgeworth type, of an MM-type and the QML estimators for the MA(1) with mean model are given. We also derive the second order expansions of the sample autocorrelation and the autocorrelation based on the QML estimator of the MA parameter. By employing Nagar type expansions, we compare the estimators in terms of bias and mean squared error. The results presented here are important for deciding on the estimation method we choose, as well as for bias reduction and increasing the efficiency of the estimators. The theoretical results are generally confirmed by a Monte-Carlo exercise.
Download or read book Extreme Values and Financial Risk written by Saralees Nadarajah and published by MDPI. This book was released on 2019-01-15 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Extreme Values and Financial Risk" that was published in JRFM
Download or read book A GARCH 1 1 Estimator with almost No Moment Conditions on the Error Term written by Arie Preminger and published by . This book was released on 2006 with total page 24 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Research Report written by and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
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.
Download or read book Asymptotic Theory for a Factor GARCH Model written by Christian M. Hafner and published by . This book was released on 2006 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Yule Walker Type Estimators in GARCH 1 1 Models Asymptotic Normality and Bootstrap written by Gisela Maercker and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
