Cheung Tsai-Yee Crystal. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 83-85). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- The Importance of Forecasting --- p.1 / Chapter 2 --- Methodology --- p.5 / Chapter 2.1 --- Basic Idea --- p.5 / Chapter 2.2 --- Outliers in Time Series --- p.9 / Chapter 2.2.1 --- One Outlier Case --- p.9 / Chapter 2.2.2 --- Two Outliers Case --- p.17 / Chapter 2.2.3 --- General Case --- p.22 / Chapter 2.2.4 --- Time Series Parameters are Unknown --- p.24 / Chapter 2.3 --- Iterative Procedure for Detecting Outliers --- p.25 / Chapter 2.3.1 --- General Procedure for Detecting Outliers --- p.25 / Chapter 2.4 --- Methods of Constructing Simultaneous Prediction Intervals --- p.27 / Chapter 2.4.1 --- The Bonferroni Method --- p.28 / Chapter 2.4.2 --- The Exact Method --- p.28 / Chapter 3 --- An Illustrative Example --- p.29 / Chapter 3.1 --- Case A --- p.31 / Chapter 3.2 --- Case B --- p.32 / Chapter 3.3 --- Comparison --- p.33 / Chapter 4 --- Simulation Study --- p.36 / Chapter 4.1 --- Generate AR(1) with an Outlier --- p.36 / Chapter 4.1.1 --- Case A --- p.38 / Chapter 4.1.2 --- Case B --- p.40 / Chapter 4.2 --- Simulation Results I --- p.42 / Chapter 4.3 --- Generate AR(1) with Two Outliers --- p.45 / Chapter 4.4 --- Simulation Results II --- p.46 / Chapter 4.5 --- Concluding Remarks --- p.47 / Bibliography --- p.83

Thesis (M.A.)--University of Notre Dame, 2009. / Thesis directed by Scott E. Maxwell for the Department of Psychology. "November 2009." Includes bibliographical references (leaves 105-107).

published_or_final_version / Statistics and Actuarial Science / Master / Master of Philosophy

Thesis (Ph.D.)--Hong Kong University of Science and Technology, 2009. / Includes bibliographical references (p. 72-75).

Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2004. / Includes bibliographical references (leaves 49-55). Also available in electronic version. Access restricted to campus users.

Thesis (Ph. D.)--University of Hong Kong, 1995. / Includes bibliographical references (leave 113-123).

University of Macau / Faculty of Science and Technology / Department of Computer and Information Science

Chau Ka Pik. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 39-40). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Maximum Probability Estimator --- p.1 / Chapter 1.2 --- An Outline of the Thesis --- p.4 / Chapter 2 --- Asymptotic Distribution Theory --- p.7 / Chapter 3 --- Exponential Family Noise --- p.16 / Chapter 3.1 --- Stationary Case --- p.16 / Chapter 3.2 --- Nonstationary Case --- p.25 / Chapter 4 --- Conclusions --- p.37 / Bibliography --- p.39

"As a part of an effective SETAR (self-exciting threshold autoregressive) mod- eling methodology, it is important to identify processes exhibiting SETAR-type non- linearity. A number of tests of nonlinearity have been developed in the literature, including those of Keenan (1985), Petruccelli and Davies (1986), Tsay (1986, 1989), Luukkonen (1988), and Chan and Tong (1990). However, it has recently been shown that all these tests perform poorly for SETAR-type nonlinearity detection in the presence of outliers. In this project we develop an improved test for SETAR-type nonlinearity in time series. The test is an outlier-robust variant of the Petruccelli and Davies (1986) test based on the cumulative sums of ordered weighted residuals from generalized maximum likelihood fits (which we call CUSUM-GM). The properties of the proposed CUSUM-GM test are illustrated by means of Monte Carlo simulations. The merits, in terms of size and power, of the proposed test are evaluated relative to the test based on ordered residuals from the ordinary least squares fit (which we call CUSUM-LS) and also to that of other tests for nonlinearity developed in literature. The simulations are run for uncontaminated data and for data contaminated with additive and innovational outliers. The simulation study strongly supports the validity of the proposed robust CUSUM-GM test, particularly in situations in which outliers might be a problem."

She, Yingni. / "August 2011." / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 43-49). / Abstracts in English and Chinese. / Chapter 1. --- Introduction --- p.1 / Chapter 2. --- Literature Review --- p.6 / Chapter 2.1 --- Investor Sentiment Measures --- p.6 / Chapter 2.2 --- Chinese Stock Market Overview --- p.13 / Chapter 3. --- Chinese Investor Sentiment Measure --- p.16 / Chapter 3.1 --- Data and Variables --- p.16 / Chapter 3.2 --- Methodology --- p.21 / Chapter 3.3 --- Empirical Results --- p.22 / Chapter 3.4 --- Investor Sentiment Behavior --- p.24 / Chapter 4. --- Threshold Autoregressive Model --- p.29 / Chapter 4.1 --- Methodology --- p.29 / Chapter 4.2 --- Estimated Results --- p.31 / Chapter 4.3 --- Forecasting Performance --- p.36 / Chapter 4.4 --- Trading Strategy --- p.38 / Chapter 5. --- Conclusion --- p.41 / References --- p.43