Modeling Time-Varying Unconditional Variance by Means of a Free-Knot Spline-GARCH Model PDF Download

Author: Oliver Old
Publisher:
ISBN: 9783658386191
Category :
Languages : en
Pages : 0

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Book Description
The book addresses the problem of a time-varying unconditional variance of return processes utilizing a spline function. The knots of the spline functions are estimated as free parameters within a joined estimation process together with the parameters of the mean, the conditional variance and the spline function. With the help of this method, the knots are placed in regions where the unconditional variance is not smooth. The results are tested within an extensive simulation study and an empirical study employing the S&P500 index. About the author: The dissertation was written at the Chair of Applied Statistics and Methods of Empirical Social Research at the Faculty of Economics and Business Administration of the FernUniversität in Hagen. From 2021 Oliver Old researched in the field of applied statistics, machine learning and data science at two EU-Horizon projects at the Department of Anesthesiology, Intensive Care and Pain Therapy at the University Hospital Frankfurt.

Author: Oliver Old
Publisher: Springer Nature
ISBN: 3658386185
Category : Business & Economics
Languages : en
Pages : 260

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Book Description
The book addresses the problem of a time-varying unconditional variance of return processes utilizing a spline function. The knots of the spline functions are estimated as free parameters within a joined estimation process together with the parameters of the mean, the conditional variance and the spline function. With the help of this method, the knots are placed in regions where the unconditional variance is not smooth. The results are tested within an extensive simulation study and an empirical study employing the S&P500 index.

Author: David Ruppert
Publisher: Springer
ISBN: 1493926144
Category : Business & Economics
Languages : en
Pages : 736

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Book Description
The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest.

Author: Robert H. Shumway
Publisher:
ISBN: 9781475732627
Category :
Languages : en
Pages : 568

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Book Description

Author: Ruey S. Tsay
Publisher: John Wiley & Sons
ISBN: 1119264073
Category : Mathematics
Languages : en
Pages : 512

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Book Description
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.

Author: Shuangzhe Li
Publisher: MDPI
ISBN: 3039439758
Category : Business & Economics
Languages : en
Pages : 232

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Book Description
Modern financial management is largely about risk management, which is increasingly data-driven. The problem is how to extract information from the data overload. It is here that advanced statistical and machine learning techniques can help. Accordingly, finance, statistics, and data analytics go hand in hand. The purpose of this book is to bring the state-of-art research in these three areas to the fore and especially research that juxtaposes these three.

Author: Julien Chevallier
Publisher: Routledge
ISBN: 1351669095
Category : Business & Economics
Languages : en
Pages : 381

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Book Description
This book provides an up-to-date series of advanced chapters on applied financial econometric techniques pertaining the various fields of commodities finance, mathematics & stochastics, international macroeconomics and financial econometrics. Financial Mathematics, Volatility and Covariance Modelling: Volume 2 provides a key repository on the current state of knowledge, the latest debates and recent literature on financial mathematics, volatility and covariance modelling. The first section is devoted to mathematical finance, stochastic modelling and control optimization. Chapters explore the recent financial crisis, the increase of uncertainty and volatility, and propose an alternative approach to deal with these issues. The second section covers financial volatility and covariance modelling and explores proposals for dealing with recent developments in financial econometrics This book will be useful to students and researchers in applied econometrics; academics and students seeking convenient access to an unfamiliar area. It will also be of great interest established researchers seeking a single repository on the current state of knowledge, current debates and relevant literature.

Author: Luc Bauwens
Publisher: John Wiley & Sons
ISBN: 1118272056
Category : Business & Economics
Languages : en
Pages : 566

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Book Description
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.

Author: Celso Gustavo Stall Sikora
Publisher: Springer Gabler
ISBN: 9783658362812
Category : Business & Economics
Languages : en
Pages : 178

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Book Description
Assembly lines are productive systems, which are very efficient for homogeneous products. In the automotive industry, an assembly line is used in the production of several vehicle variants, including numerous configurations, options, and add-ins. As a result, assembly lines must be at the same time specialized to provide high efficiency, but also flexible to allow the mass customization of the vehicles. In this book, the planning of assembly lines for uncertain demand is tackled and optimization algorithms are offered for the balancing of such lines. Building an assembly line is a commitment of several months or even years, it is understandable that the demand will fluctuate during the lifetime of an assembly line. New products are developed, others are removed from the market, and the decision of the final customer plays a role on the immediate demand. Therefore, the variation and uncertainty of the demand must be accounted for in an assembly line. In this book, methods dealing with random demand or random production sequence are presented, so that the practitioners can plan more robust and efficient production systems.

Author: Benjamin Robert Schiller
Publisher: Springer Nature
ISBN: 3658365269
Category : Business & Economics
Languages : en
Pages : 352

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Book Description
This book appeals to higher education scholars from various disciplines and practitioners looking for an overview and in-depth insight into cooperative study programs (CSPs). The CSPs combine elements of higher education with elements of professional work and illustrate how a teaching-related third mission achieves a socioeconomic contribution through its underlying stakeholder interactions. In Germany, CSPs are a growing phenomenon and, at the same time, a niche in higher education with approximately 100,000 students. Higher education scholars identified CSPs a challenge to higher education governance despite the simultaneous lack of empirical data. In this vein, this book pursues the question of how stakeholders influence the governance of the third mission in the case of CSPs. The study in this book refers to the “prime” example of CSPs at a German university of applied sciences—the Baden-Wuerttemberg Cooperative State University. The analysis revealed that four stakeholder groups are salient and influence the governance of the CSPs. These include professors, industry representatives, students, and representatives of government and higher education policy.