000695595 000__ 03635cam\a2200445Ki\4500
000695595 001__ 695595
000695595 005__ 20230306135447.0
000695595 006__ m\\\\\o\\d\\\\\\\\
000695595 007__ cr\cnu|||unuuu
000695595 008__ 131015s2014\\\\xxua\\\\ob\\\\000\0\eng\d
000695595 020__ $$a9781461480600 $$qelectronic book
000695595 020__ $$a1461480604 $$qelectronic book
000695595 020__ $$z9781461480594
000695595 0247_ $$a10.1007/978-1-4614-8060-0$$2doi
000695595 035__ $$aSP(OCoLC)ocn860775015
000695595 035__ $$aSP(OCoLC)860775015
000695595 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dN$T$$dYDXCP$$dIDEBK$$dCOO
000695595 049__ $$aISEA
000695595 050_4 $$aQA276.8
000695595 08204 $$a519.5/44$$223
000695595 24500 $$aRecent advances in estimating nonlinear models$$h[electronic resource] :$$bwith applications in economics and finance /$$cJun Ma, Mark Wohar, editors.
000695595 264_1 $$aNew York :$$bSpringer,$$c[2013?]
000695595 264_4 $$c©2014
000695595 300__ $$a1 online resource (xvi, 299 pages) :$$billustrations (some color)
000695595 336__ $$atext$$btxt$$2rdacontent
000695595 337__ $$acomputer$$bc$$2rdamedia
000695595 338__ $$aonline resource$$bcr$$2rdacarrier
000695595 504__ $$aIncludes bibliographical references.
000695595 5050_ $$aStock Return and Inflation: An Analysis Based on the State-Space Framework -- Diffusion Index Model Specification and Estimation: Using Mixed Frequency Datasets -- Testing for Neglected Nonlinearity Using Regularized Artificial Neural Networks -- On the Use of the Flexible Fourier Form in Unit Roots Tests, Endogenous Breaks, and Parameter Instability -- Testing for a Markov-Switching Mean in Serially-Correlated Data -- Nonlinear Time Series Models and Model Selection -- Nonstationarities and Markov Switching Models -- Has Wealth Effect Changed Over Time? Evidence from Four Industrial Countries -- A Simple Specification Procedure for the Transition Function in Persistent Nonlinear Times Series Models -- Small Area Estimation with Correctly Specified Linking Models -- Forecasting Stock Returns: Does Switching between Models Help? -- The Global Joint Distribution of Income and Health.
000695595 506__ $$aAccess limited to authorized users.
000695595 520__ $$aThis edited volume provides a timely overview of nonlinear estimation techniques, offering new methods and insights into nonlinear time series analysis. The focus is on such topics as state-space model and the identification issue, use of Markov Switching Models and Smooth Transition Models to analyze economic series, and how best to distinguish between competing nonlinear models. Most economic theory suggests that the economic relationships among economic variables in the real world are fairly complex and nonlinear. Nonlinear models are necessary to capture these important channels through which economic variables can influence each other and various policies can affect economic activities. This volume features cutting-edge research from leading academics in economics, finance, and business management. The principles and techniques used here will appeal to econometricians, finance professors teaching quantitative finance, researchers, and graduate students interested in learning how to apply advances in nonlinear time series modeling to solve complex problems in economics and finance.
000695595 588__ $$aDescription based on online resource; title from PDF title page (SpringerLink, viewed October 1, 2013).
000695595 650_0 $$aEstimation theory.
000695595 650_0 $$aNonlinear theories.
000695595 7001_ $$aMa, Jun,$$eeditor of compilation.
000695595 7001_ $$aWohar, Mark E.,$$eeditor of compilation.
000695595 85280 $$bebk$$hSpringerLink
000695595 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://dx.doi.org/10.1007/978-1-4614-8060-0$$zOnline Access
000695595 909CO $$ooai:library.usi.edu:695595$$pGLOBAL_SET
000695595 980__ $$aEBOOK
000695595 980__ $$aBIB
000695595 982__ $$aEbook
000695595 983__ $$aOnline
000695595 994__ $$a92$$bISE