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On robust testing and estimation of SETAR models.

Hung, King Chi. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 78-52). / Abstracts in English and Chinese. / Abstract --- p.i / Acknowledgement --- p.iii / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Non-linear Time Series Models and Their Applications --- p.2 / Chapter 1.2 --- The SETAR Model --- p.4 / Chapter 1.3 --- Objectives and Organization of the Thesis --- p.6 / Chapter 2 --- The SETAR Model and Robust Test for Non-linearity --- p.8 / Chapter 2.1 --- A Brief Review of Existing Tests for Threshold-type Non-linearity --- p.9 / Chapter 2.2 --- Robust Tests for Threshold-type Non-linearity --- p.11 / Chapter 2.2.1 --- Tsay´ةs F Test --- p.12 / Chapter 2.2.2 --- The Proposed Test --- p.15 / Chapter 2.3 --- The Choice of the ψ-function --- p.23 / Chapter 2.4 --- A Simulation Study --- p.26 / Chapter 2.4.1 --- Data Generation Process (DGP) --- p.26 / Chapter 2.4.2 --- Simulation Findings --- p.29 / Chapter 3 --- Robust Estimation and Asymptotic Properties --- p.34 / Chapter 3.1 --- Least Squares Estimation --- p.37 / Chapter 3.2 --- Robust Estimation --- p.38 / Chapter 3.2.1 --- Asymptotic Properties --- p.40 / Chapter 3.3 --- A Simulation Study --- p.52 / Chapter 3.3.1 --- Data Generation Process (DGP) --- p.53 / Chapter 3.3.2 --- Simulation Findings --- p.55 / Chapter 3.3.3 --- Objective Function over r --- p.56 / Chapter 4 --- Numerical Example --- p.67 / Chapter 4.1 --- Methodology --- p.68 / Chapter 4.2 --- ASEAN Background --- p.69 / Chapter 4.2.1 --- Non-linearity tests on ASEAN Exchange Rate --- p.72 / Chapter 4.2.2 --- Estimation of the Return of Singaporean Dollar --- p.73 / Chapter 5 --- Conclusions and Further Research --- p.76 / References --- p.78

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_326267
Date January 2008
ContributorsHung, King Chi., Chinese University of Hong Kong Graduate School. Division of Statistics.
Source SetsThe Chinese University of Hong Kong
LanguageEnglish, Chinese
Detected LanguageEnglish
TypeText, bibliography
Formatprint, viii, 52 leaves : ill. ; 30 cm.
RightsUse of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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