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Three Essays On Shrinkage Estimation And Model Selection Of Linear And Nonlinear Time Series Models
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Book Synopsis Three Essays on Shrinkage Estimation and Model Selection of Linear and Nonlinear Time Series Models by : Mario Giacomazzo
Download or read book Three Essays on Shrinkage Estimation and Model Selection of Linear and Nonlinear Time Series Models written by Mario Giacomazzo and published by . This book was released on 2018 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: The primary objective in time series analysis is forecasting. Raw data often exhibits nonstationary behavior: trends, seasonal cycles, and heteroskedasticity. After data is transformed to a weakly stationary process, autoregressive moving average (ARMA) models may capture the remaining temporal dynamics to improve forecasting. Estimation of ARMA can be performed through regressing current values on previous realizations and proxy innovations. The classic paradigm fails when dynamics are nonlinear; in this case, parametric, regime-switching specifications model changes in level, ARMA dynamics, and volatility, using a finite number of latent states. If the states can be identified using past endogenous or exogenous information, a threshold autoregressive (TAR) or logistic smooth transition autoregressive (LSTAR) model may simplify complex nonlinear associations to conditional weakly stationary processes. For ARMA, TAR, and STAR, order parameters quantify the extent past information is associated with the future. Unfortunately, even if model orders are known a priori, the possibility of over-fitting can lead to sub-optimal forecasting performance. By intentionally overestimating these orders, a linear representation of the full model is exploited and Bayesian regularization can be used to achieve sparsity. Global-local shrinkage priors for AR, MA, and exogenous coefficients are adopted to pull posterior means toward 0 without over-shrinking relevant effects. This dissertation introduces, evaluates, and compares Bayesian techniques that automatically perform model selection and coefficient estimation of ARMA, TAR, and STAR models. Multiple Monte Carlo experiments illustrate the accuracy of these methods in finding the "true" data generating process. Practical applications demonstrate their efficacy in forecasting.
Book Synopsis Three Essays on Nonlinear Time Series by : Jin-Lung Lin
Download or read book Three Essays on Nonlinear Time Series written by Jin-Lung Lin and published by . This book was released on 1991 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Essays in Nonlinear Time Series Econometrics by : Niels Haldrup
Download or read book Essays in Nonlinear Time Series Econometrics written by Niels Haldrup and published by OUP Oxford. This book was released on 2014-06-26 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Book Synopsis Three Essays on Nonlinear Time Series Econometrics by : Zhengfeng Guo
Download or read book Three Essays on Nonlinear Time Series Econometrics written by Zhengfeng Guo and published by . This book was released on 2011 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Nonlinear Time Series Analysis by : Ruey S. Tsay
Download or read book Nonlinear Time Series Analysis written by Ruey S. Tsay and published by John Wiley & Sons. This book was released on 2018-09-14 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive resource that draws a balance between theory and applications of nonlinear time series analysis Nonlinear Time Series Analysis offers an important guide to both parametric and nonparametric methods, nonlinear state-space models, and Bayesian as well as classical approaches to nonlinear time series analysis. The authors—noted experts in the field—explore the advantages and limitations of the nonlinear models and methods and review the improvements upon linear time series models. The need for this book is based on the recent developments in nonlinear time series analysis, statistical learning, dynamic systems and advanced computational methods. Parametric and nonparametric methods and nonlinear and non-Gaussian state space models provide a much wider range of tools for time series analysis. In addition, advances in computing and data collection have made available large data sets and high-frequency data. These new data make it not only feasible, but also necessary to take into consideration the nonlinearity embedded in most real-world time series. This vital guide: • Offers research developed by leading scholars of time series analysis • Presents R commands making it possible to reproduce all the analyses included in the text • Contains real-world examples throughout the book • Recommends exercises to test understanding of material presented • Includes an instructor solutions manual and companion website Written for students, researchers, and practitioners who are interested in exploring nonlinearity in time series, Nonlinear Time Series Analysis offers a comprehensive text that explores the advantages and limitations of the nonlinear models and methods and demonstrates the improvements upon linear time series models.
Book Synopsis Three Essays on Nonstationary Time Series Analysis by :
Download or read book Three Essays on Nonstationary Time Series Analysis written by and published by . This book was released on 2014 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Financial and macroeconomic time series data are often nonstationary. My dissertation consists of three essays concerning time series models with nonstationarity. Chapter 1 develops a new jackknife estimator for nonstationary autoregressive model. The remaining two chapters explore the restricted maximum likelihood (REML hereafter) estimation and the restricted maximum likelihood based likelihood ratio test (RLRT hereafter) in predictive regression...."--Author's abstract.
Book Synopsis Estimation for Some Linear and Nonlinear Time Series Models by : Rongning Wu
Download or read book Estimation for Some Linear and Nonlinear Time Series Models written by Rongning Wu and published by . This book was released on 2007 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Time-Series Forecasting by : Chris Chatfield
Download or read book Time-Series Forecasting written by Chris Chatfield and published by CRC Press. This book was released on 2000-10-25 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the author of the bestselling "Analysis of Time Series," Time-Series Forecasting offers a comprehensive, up-to-date review of forecasting methods. It provides a summary of time-series modelling procedures, followed by a brief catalogue of many different time-series forecasting methods, ranging from ad-hoc methods through ARIMA and state-space
Book Synopsis Three Essays on Model Selection in Time Series Econometrics by : Niels Mariano Aka
Download or read book Three Essays on Model Selection in Time Series Econometrics written by Niels Mariano Aka and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Essays on Modeling Nonlinear Time Series by : Paul Tjeerd Bruin (de.)
Download or read book Essays on Modeling Nonlinear Time Series written by Paul Tjeerd Bruin (de.) and published by . This book was released on 2002 with total page 133 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Three Essays on Nonlinear Time-series Econometrics by : Novella Maugeri
Download or read book Three Essays on Nonlinear Time-series Econometrics written by Novella Maugeri and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Essays on Dynamic Nonlinear Time Series Models and on Gender Inequality by : Deepankar Basu
Download or read book Essays on Dynamic Nonlinear Time Series Models and on Gender Inequality written by Deepankar Basu and published by . This book was released on 2008 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: Abstract: My dissertation research has two distinct foci: one, studying problems of estimation and inference in dynamic nonlinear econometric models (first three chapters); and two, studying issues related to the problem of gender inequality in developing countries (last two chapters). The first chapter develops a framework to study dynamic discrete ordered choice behavior in situations where past choices directly influence current choices. I study such choice situations - in a time series setting - with a novel specification of a dynamic multinomial ordered choice model, where the latent variable is allowed to depend on lags of the choice variable. The second chapter highlights a potential problem in a binary choice duration model, where duration dependence is used as a regressor to capture persistence. I show that if such a model is extended to a situation where T is large, a problem of internal consistency will arise. This is because the dependent variable converges in probability to unity and the information matrix becomes singular. The third chapter develops a random threshold autoregressive (RTAR) model which generalizes the standard threshold autoregressive (TAR) models by allowing the threshold parameter in a two regime TAR model to be a random variable. I demonstrate that the RTAR model has a strictly stationarity solution which is also near epoch dependent. The fourth chapter develops and tests a simple model for the generation of gender inequality at the aggregate level in the absence of direct discrimination against girls. The results of the model is driven by son preference leading to male-preferring stopping rules on fertility decisions; this results in girls being born, on average, into larger families and as elder children within families. Both these generate disadvantageous position for girls at the aggregate level. In the backdrop of the debate on missing women (Oster, 2005), the fifth chapter of my dissertation empirically tests for two competing explanations of the increasing sex ratio at birth (SRB) in India: prevalence of hepatitis B and human intervention in the form of sex selective abortion or female infanticide. I find that human intervention rather than hepatitis B explains the increasing SRB in India.
Book Synopsis Index to Theses with Abstracts Accepted for Higher Degrees by the Universities of Great Britain and Ireland and the Council for National Academic Awards by :
Download or read book Index to Theses with Abstracts Accepted for Higher Degrees by the Universities of Great Britain and Ireland and the Council for National Academic Awards written by and published by . This book was released on 2008 with total page 716 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Macroeconomic Forecasting in the Era of Big Data by : Peter Fuleky
Download or read book Macroeconomic Forecasting in the Era of Big Data written by Peter Fuleky and published by Springer Nature. This book was released on 2019-11-28 with total page 716 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; how to select parsimonious models; how to deal with model uncertainty, instability, non-stationarity, and mixed frequency data; and how to evaluate forecasts, among others. Each chapter is self-contained with references, and provides solid background information, while also reviewing the latest advances in the field. Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.
Book Synopsis Dynamic Linear Models with R by : Giovanni Petris
Download or read book Dynamic Linear Models with R written by Giovanni Petris and published by Springer Science & Business Media. This book was released on 2009-06-12 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: State space models have gained tremendous popularity in recent years in as disparate fields as engineering, economics, genetics and ecology. After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. Whenever possible it is shown how to compute estimates and forecasts in closed form; for more complex models, simulation techniques are used. A final chapter covers modern sequential Monte Carlo algorithms. The book illustrates all the fundamental steps needed to use dynamic linear models in practice, using R. Many detailed examples based on real data sets are provided to show how to set up a specific model, estimate its parameters, and use it for forecasting. All the code used in the book is available online. No prior knowledge of Bayesian statistics or time series analysis is required, although familiarity with basic statistics and R is assumed.
Book Synopsis Time Series Analysis and Its Applications by : Robert H. Shumway
Download or read book Time Series Analysis and Its Applications written by Robert H. Shumway and published by . This book was released on 2014-01-15 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Mathematical Reviews written by and published by . This book was released on 2004 with total page 1124 pages. Available in PDF, EPUB and Kindle. Book excerpt:
