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EBookClubs

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Book Nonparametric Estimation of Time Series Volatility Model Estimation

Download or read book Nonparametric Estimation of Time Series Volatility Model Estimation written by Teng Tu (Mathematician) and published by . This book was released on 2018 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this article we consider two estimation methods of a non-parametric volatility model with autoregressive error of order two. The first estimation method based on the two- lag difference. To get a better result, we consider the second approach based on the general quadratic forms. For illustration, we provided several data sets from different simulation models to support the procedures of both two methods, and prove that the second approach can make a better estimation.

Book Nonparametric Estimation in a Stochastic Volatility Model

Download or read book Nonparametric Estimation in a Stochastic Volatility Model written by Jürgen Franke and published by . This book was released on 1998 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Nonlinear Time Series

Download or read book Nonlinear Time Series written by Jiti Gao and published by CRC Press. This book was released on 2007-03-22 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention in the economics and statistics communities over the past twenty years. Recent studies show that semiparametric methods and models may be applied to solve dimensionality reduction problems arising from using fully

Book Tilted Nonparametric Estimation of Volatility Functions with Empirical Applications

Download or read book Tilted Nonparametric Estimation of Volatility Functions with Empirical Applications written by Peter C. B. Phillips and published by . This book was released on 2010 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper proposes a novel positive nonparametric estimator of the conditional variance function without reliance on logarithmic or other transformations. The estimator is based on an empirical likelihood modification of conventional local level nonparametric regression applied to squared mean regression residuals. The estimator is shown to be asymptotically equivalent to the local linear estimator in the case of unbounded support but, unlike that estimator, is restricted to be non-negative in finite samples. It is fully adaptive to the unknown conditional mean function. Simulations are conducted to evaluate the finite sample performance of the estimator. Two empirical applications are reported. One uses cross section data and studies the relationship between occupational prestige and income. The other uses time series data on Treasury bill rates to fit the total volatility function in a continuous-time jump diffusion model.

Book Handbook of Volatility Models and Their Applications

Download or read book Handbook of Volatility Models and Their Applications written by Luc Bauwens and published by John Wiley & Sons. This book was released on 2012-03-22 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete guide to the theory and practice of volatility models in financial engineering Volatility has become a hot topic in this era of instant communications, spawning a great deal of research in empirical finance and time series econometrics. Providing an overview of the most recent advances, Handbook of Volatility Models and Their Applications explores key concepts and topics essential for modeling the volatility of financial time series, both univariate and multivariate, parametric and non-parametric, high-frequency and low-frequency. Featuring contributions from international experts in the field, the book features numerous examples and applications from real-world projects and cutting-edge research, showing step by step how to use various methods accurately and efficiently when assessing volatility rates. Following a comprehensive introduction to the topic, readers are provided with three distinct sections that unify the statistical and practical aspects of volatility: Autoregressive Conditional Heteroskedasticity and Stochastic Volatility presents ARCH and stochastic volatility models, with a focus on recent research topics including mean, volatility, and skewness spillovers in equity markets Other Models and Methods presents alternative approaches, such as multiplicative error models, nonparametric and semi-parametric models, and copula-based models of (co)volatilities Realized Volatility explores issues of the measurement of volatility by realized variances and covariances, guiding readers on how to successfully model and forecast these measures Handbook of Volatility Models and Their Applications is an essential reference for academics and practitioners in finance, business, and econometrics who work with volatility models in their everyday work. The book also serves as a supplement for courses on risk management and volatility at the upper-undergraduate and graduate levels.

Book Nonlinear Time Series

    Book Details:
  • Author : Jianqing Fan
  • Publisher : Springer Science & Business Media
  • Release : 2008-09-11
  • ISBN : 0387693955
  • Pages : 565 pages

Download or read book Nonlinear Time Series written by Jianqing Fan and published by Springer Science & Business Media. This book was released on 2008-09-11 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book that integrates useful parametric and nonparametric techniques with time series modeling and prediction, the two important goals of time series analysis. Such a book will benefit researchers and practitioners in various fields such as econometricians, meteorologists, biologists, among others who wish to learn useful time series methods within a short period of time. The book also intends to serve as a reference or text book for graduate students in statistics and econometrics.

Book Nonparametric Estimation of Stochastic Volatility Models

Download or read book Nonparametric Estimation of Stochastic Volatility Models written by Steven Cannon Hogan and published by . This book was released on 2000 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Tilted Nonparametric Estimation of Volatility Functions with Empirical Applications  2nd Version

Download or read book Tilted Nonparametric Estimation of Volatility Functions with Empirical Applications 2nd Version written by Ke-Li Xu and published by . This book was released on 2010 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper proposes a novel positive nonparametric estimator of the conditional variance function without reliance on logarithmic or other transformations. The estimator is based on an empirical likelihood modification of conventional local level nonparametric regression applied to squared mean regression residuals. The estimator is shown to be asymptotically equivalent to the local linear estimator in the case of unbounded support but, unlike that estimator, is restricted to be non-negative in finite samples. It is fully adaptive to the unknown conditional mean function. Simulations are conducted to evaluate the finite sample performance of the estimator. Two empirical applications are reported. One uses cross section data and studies the relationship between occupational prestige and income. The other uses time series data on Treasury bill rates to fit the total volatility function in a continuous-time jump diffusion model.

Book Nonlinear Time Series Analysis with Applications to Foreign Exchange Rate Volatility

Download or read book Nonlinear Time Series Analysis with Applications to Foreign Exchange Rate Volatility written by Christian Hafner and published by Springer Science & Business Media. This book was released on 2013-11-27 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book deals with the econometric analysis of high frequency financial time series. It emphasizes a new nonparametric approach to volatility models and provides theoretical and empirical comparisons with conventional ARCH models, applied to foreign exchange rates. Nonparametric models are discussed that cope with asymmetry and long memory of volatility as well as heterogeneity of higher conditional moments.

Book Statistics And Finance  An Interface   Proceedings Of The Hong Kong International Workshop On Statistics In Finance

Download or read book Statistics And Finance An Interface Proceedings Of The Hong Kong International Workshop On Statistics In Finance written by Wai-sum Chan and published by World Scientific. This book was released on 2000-04-28 with total page 396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contents:Heavy-Tailed and Nonlinear Continuous-Time ARMA Models for Financial Time Series (P J Brockwell)Nonlinear State Space Model Approach to Financial Time Series with Time-Varying Variance (G Kitagawa & S Sato)Nonparametric Estimation and Bootstrap for Financial Time Series (J-P Kreiβ)A Note on Kernel Estimation in Integrated Time Series (Y-C Xia et al.)Stylized Facts on the Temporal and Distributional Properties of Absolute Returns: An Update (C W J Granger et al.)Volatility Computed by Time Series Operators at High Frequency (U A Müller)Missing Values in ARFIMA Models (W Palma)Second Order Tail Effects (C G de Vries)Bayesian Estimation of Stochastic Volatility Model via Scale Mixtures Distributions (S T B Choy & C M Chan)On a Smooth Transition Double Threshold Model (Y N Lee & W K Li)Interval Prediction of Financial Time Series (B Cheng & H Tong)A Decision Theoretic Approach to Forecast Evaluation (C W J Granger & M H Pesaran)Portfolio Management and Market Risk Quantification Using Neural Networks (J Franke)Detecting Structural Changes Using Genetic Programming with an Application to the Greater-China Stock Markets (X B Zhang et al.)and other papers Readership: Researchers in finance, time series analysis, economics and actuarial science, as well as investment bankers, stock market analysts and risk managers. Keywords:Proceedings;Workshop;Statistics;Finance;Hongkong (China)

Book Estimation of Stochastic Volatility Models with Diagnostics

Download or read book Estimation of Stochastic Volatility Models with Diagnostics written by A. Ronald Gallant and published by . This book was released on 2008 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Efficient Method of Moments (EMM) is used to fit the standard stochastic volatility model and various extensions to several daily financial time series. EMM matches to the score of a model determined by data analysis called the score generator. Discrepancies reveal characteristics of data that stochastic volatility models cannot approximate. The two score generators employed here are "Semiparametric ARCH" and "Nonlinear Nonparametric". With the first, the standard model is rejected, although some extensions are accepted. With the second, all versions are rejected. The extensions required for an adequate fit are so elaborate that nonparametric specifications are probably more convenient.

Book Nonparametric Estimation in Models with L  vy Type Jumps and Stochastic Volatility

Download or read book Nonparametric Estimation in Models with L vy Type Jumps and Stochastic Volatility written by Cecilia Mancini and published by . This book was released on 2005 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Nonparametric estimation in models with Levy Type Jumps and stochastic volatility

Download or read book Nonparametric estimation in models with Levy Type Jumps and stochastic volatility written by Cecilia Mancini and published by . This book was released on 2005 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Nonparametric Estimation in Model with Levy Type Jumps and Stochastic Volatility

Download or read book Nonparametric Estimation in Model with Levy Type Jumps and Stochastic Volatility written by Cecilia Mancini and published by . This book was released on 2005 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Prediction and Nonparametric Estimation for Time Series with Heavy Tails

Download or read book Prediction and Nonparametric Estimation for Time Series with Heavy Tails written by Peter Hall and published by . This book was released on 2004 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Motivated by prediction problems for time series with heavy-tailed marginal distributions, we consider methods based on 'local least absolute deviations' for estimating a regression median from dependent data. Unlike more conventional 'local median' methods, which are in effect based on locally fitting a polynomial of degree 0, techniques founded on local least absolute deviations have quadratic bias right up to the boundary of the design interval. Also in contrast to local least-squares methods based on linear fits, the order of magnitude of variance does not depend on tail-weight of the error distribution. To make these points clear, we develop theory describing local applications to time series of both least-squares and least-absolute-deviations methods, showing for example that, in the case of heavy-tailed data, the conventional local-linear least-squares estimator suffers from an additional bias term as well as increased variance.

Book Handbook of Financial Time Series

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 New Directions in Time Series Analysis

Download or read book New Directions in Time Series Analysis written by David Brillinger and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: This IMA Volume in Mathematics and its Applications NEW DIRECTIONS IN TIME SERIES ANALYSIS, PART II is based on the proceedings of the IMA summer program "New Directions in Time Series Analysis. " We are grateful to David Brillinger, Peter Caines, John Geweke, Emanuel Parzen, Murray Rosenblatt, and Murad Taqqu for organizing the program and we hope that the remarkable excitement and enthusiasm of the participants in this interdisciplinary effort are communicated to the reader. A vner Friedman Willard Miller, Jr. PREFACE Time Series Analysis is truly an interdisciplinary field because development of its theory and methods requires interaction between the diverse disciplines in which it is applied. To harness its great potential, strong interaction must be encouraged among the diverse community of statisticians and other scientists whose research involves the analysis of time series data. This was the goal of the IMA Workshop on "New Directions in Time Series Analysis. " The workshop was held July 2-July 27, 1990 and was organized by a committee consisting of Emanuel Parzen (chair), David Brillinger, Murray Rosenblatt, Murad S. Taqqu, John Geweke, and Peter Caines. Constant guidance and encouragement was provided by Avner Friedman, Director of the IMA, and his very helpful and efficient staff. The workshops were organized by weeks. It may be of interest to record the themes that were announced in the IMA newsletter describing the workshop: l.