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Author : Kai Ming Lee
Publisher : Rozenberg Publishers
Page : 150 pages
File Size : 52,5 Mb
Release : 2010
Category : Electronic
ISBN : 9789036101691
Author : Yong Zeng,Shu Wu
Publisher : Springer Science & Business Media
Page : 358 pages
File Size : 53,7 Mb
Release : 2013-08-15
Category : Business & Economics
ISBN : 9781461477891
State-space models as an important mathematical tool has been widely used in many different fields. This edited collection explores recent theoretical developments of the models and their applications in economics and finance. The book includes nonlinear and non-Gaussian time series models, regime-switching and hidden Markov models, continuous- or discrete-time state processes, and models of equally-spaced or irregularly-spaced (discrete or continuous) observations. The contributed chapters are divided into four parts. The first part is on Particle Filtering and Parameter Learning in Nonlinear State-Space Models. The second part focuses on the application of Linear State-Space Models in Macroeconomics and Finance. The third part deals with Hidden Markov Models, Regime Switching and Mathematical Finance and the fourth part is on Nonlinear State-Space Models for High Frequency Financial Data. The book will appeal to graduate students and researchers studying state-space modeling in economics, statistics, and mathematics, as well as to finance professionals.
Author : Hisashi Tanizaki
Publisher : Springer Science & Business Media
Page : 264 pages
File Size : 51,8 Mb
Release : 2013-03-09
Category : Business & Economics
ISBN : 9783662032237
Nonlinear and nonnormal filters are introduced and developed. Traditional nonlinear filters such as the extended Kalman filter and the Gaussian sum filter give biased filtering estimates, and therefore several nonlinear and nonnormal filters have been derived from the underlying probability density functions. The density-based nonlinear filters introduced in this book utilize numerical integration, Monte-Carlo integration with importance sampling or rejection sampling and the obtained filtering estimates are asymptotically unbiased and efficient. By Monte-Carlo simulation studies, all the nonlinear filters are compared. Finally, as an empirical application, consumption functions based on the rational expectation model are estimated for the nonlinear filters, where US, UK and Japan economies are compared.
Author : Christian L. Dunis,Jason Laws,Patrick Naïm
Publisher : John Wiley & Sons
Page : 426 pages
File Size : 53,8 Mb
Release : 2004-01-09
Category : Business & Economics
ISBN : 9780470871348
This book provides a manual on quantitative financial analysis. Focusing on advanced methods for modelling financial markets in the context of practical financial applications, it will cover data, software and techniques that will enable the reader to implement and interpret quantitative methodologies, specifically for trading and investment. Includes contributions from an international team of academics and quantitative asset managers from Morgan Stanley, Barclays Global Investors, ABN AMRO and Credit Suisse First Boston. Fills the gap for a book on applied quantitative investment & trading models Provides details of how to combine various models to manage and trade a portfolio
Author : Arnaud Doucet,Nando de Freitas,Neil Gordon
Publisher : Springer Science & Business Media
Page : 590 pages
File Size : 55,7 Mb
Release : 2013-03-09
Category : Mathematics
ISBN : 9781475734379
Monte Carlo methods are revolutionizing the on-line analysis of data in many fileds. They have made it possible to solve numerically many complex, non-standard problems that were previously intractable. This book presents the first comprehensive treatment of these techniques.
Author : Andrew Harvey,Tommaso Proietti
Publisher : OUP Oxford
Page : 472 pages
File Size : 50,7 Mb
Release : 2005-04-07
Category : Business & Economics
ISBN : 9780191515545
This volume presents a collection of readings which give the reader an idea of the nature and scope of unobserved components (UC) models and the methods used to deal with them. The book is intended to give a self-contained presentation of the methods and applicative issues. Harvey has made major contributions to this field and provides substantial introductions throughout the book to form a unified view of the literature. - ;This book presents a collection of readings which give the reader an idea of the nature and scope of unobserved components (UC) models and the methods used to deal with them. It contains four parts, three of which concern recent theoretical developments in classical and Bayesian estimation of linear, nonlinear, and non Gaussian UC models, signal extraction and testing, and one is devoted to selected econometric applications. The first part focuses on the linear state space model; the readings provide insight on prediction theory, signal extraction, and likelihood inference for non stationary and non invertible processes, diagnostic checking, and the use of state space methods for spline smoothing. Part II deals with applications of linear UC models to various estimation problems concerning economic time series, such as trend-cycle decompositions, seasonal adjustment, and the modelling of the serial correlation induced by survey sample design. The issues involved in testing in linear UC models are the theme of part III, which considers tests concerned with whether or not certain variance parameters are zero, with special reference to stationarity tests. Finally, part IV is devoted to the advances concerning classical and Bayesian inference for non linear and non Gaussian state space models, an area that has been evolving very rapidly during the last decade, paralleling the advances in computational inference using stochastic simulation techniques. The book is intended to give a relatively self-contained presentation of the methods and applicative issues. For this purpose, each part comes with an introductory chapter by the editors that provides a unified view of the literature and the many important developments that have occurred in the last years. -
Author : Kostas Triantafyllopoulos
Publisher : Springer Nature
Page : 503 pages
File Size : 42,7 Mb
Release : 2021-11-12
Category : Mathematics
ISBN : 9783030761240
Bayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space models. The celebrated Kalman filter, with its numerous extensions, takes centre stage in the book. Univariate and multivariate models, linear Gaussian, non-linear and non-Gaussian models are discussed with applications to signal processing, environmetrics, economics and systems engineering. Over the past years there has been a growing literature on Bayesian inference of state space models, focusing on multivariate models as well as on non-linear and non-Gaussian models. The availability of time series data in many fields of science and industry on the one hand, and the development of low-cost computational capabilities on the other, have resulted in a wealth of statistical methods aimed at parameter estimation and forecasting. This book brings together many of these methods, presenting an accessible and comprehensive introduction to state space models. A number of data sets from different disciplines are used to illustrate the methods and show how they are applied in practice. The R package BTSA, created for the book, includes many of the algorithms and examples presented. The book is essentially self-contained and includes a chapter summarising the prerequisites in undergraduate linear algebra, probability and statistics. An up-to-date and complete account of state space methods, illustrated by real-life data sets and R code, this textbook will appeal to a wide range of students and scientists, notably in the disciplines of statistics, systems engineering, signal processing, data science, finance and econometrics. With numerous exercises in each chapter, and prerequisite knowledge conveniently recalled, it is suitable for upper undergraduate and graduate courses.
Author : Eva Gutiérrez Puigarnau
Publisher : Rozenberg Publishers
Page : 140 pages
File Size : 54,5 Mb
Release : 2011
Category : Electronic
ISBN : 9789036102155
Author : Andrey Andreyevich Dubovik
Publisher : Rozenberg Publishers
Page : 121 pages
File Size : 49,9 Mb
Release : 2010
Category : Electronic
ISBN : 9789036102094
Author : Hui-Ting Wu
Publisher : Rozenberg Publishers
Page : 196 pages
File Size : 43,6 Mb
Release : 2010
Category : Electronic
ISBN : 9789036101912
Author : Andrey M. Lizyayev
Publisher : Rozenberg Publishers
Page : 136 pages
File Size : 48,5 Mb
Release : 2010
Category : Electronic
ISBN : 9789036101875
Author : Xiaolong Liu
Publisher : Rozenberg Publishers
Page : 132 pages
File Size : 52,5 Mb
Release : 2010
Category : Electronic
ISBN : 9789036101998
Author : Anonim
Publisher : Rozenberg Publishers
Page : 244 pages
File Size : 42,8 Mb
Release : 2024-07-02
Category : Electronic
ISBN : 9789036101844
Author : Sumedha Gupta
Publisher : Rozenberg Publishers
Page : 259 pages
File Size : 48,5 Mb
Release : 2010
Category : Electronic
ISBN : 9789036101790
Author : James Durbin,Andrew Harvey,Siem Jan Koopman,Neil Shephard
Publisher : Cambridge University Press
Page : 398 pages
File Size : 49,5 Mb
Release : 2004-06-10
Category : Business & Economics
ISBN : 052183595X
A comprehensive overview of developments in the theory and application of state space modeling, first published in 2004.