Cross market monitoring on financial markets.

by Lee Yue, Wefield.Thesis (M.Phil.)--Chinese University of Hong Kong, 2001.Includes bibliographical references (leaves 105-111).Abstracts in English and Chinese.Abstract --- p.IAbstract (Chinese) --- p.IIAcknowledgement --- p.IIITable of Content --- p.IVList of Figures --- p.VIIList of Tables --- p.VIIIChapter 1 --- Introduction --- p.1Chapter 1.1 --- Background --- p.1Chapter 1.2 --- Motivation --- p.2Chapter 1.3 --- Organization --- p.4Chapter 2 --- Literature Review --- p.5Chapter 2.1 --- Market Monitoring --- p.5Chapter 2.1.1 --- Regulatory Framework --- p.5Chapter 2.1.2 --- Surveillance Technology --- p.6Chapter 2.2 --- Cross Market Relationship --- p.7Chapter 2.3 --- Knowledge Management --- p.9Chapter 2.3.1 --- From Data and Information to Knowledge --- p.9Chapter 2.3.2 --- From Knowledge to Knowledge Management --- p.10Chapter 3 --- Market Activities and Market Surveillance --- p.13Chapter 3.1 --- Overview of Market Structure --- p.13Chapter 3.1.1 --- Monetary Market --- p.13Chapter 3.1.2 --- Stock and its Derivatives Market --- p.14Chapter 3.1.3 --- Futures --- p.19Chapter 3.2 --- Cross-Market Activities and Manipulation --- p.20Chapter 3.3 --- Monitoring and Surveillance --- p.22Chapter 3.4 --- Stock Monitoring Systems --- p.23Chapter 4 --- Financial Knowledge Management (FKM) Model --- p.27Chapter 4.1 --- Introduction --- p.27Chapter 4.2 --- Knowledge Management cycle --- p.28Chapter 4.2.1 --- Information Collection --- p.29Chapter 4.2.2 --- Information Storage --- p.29Chapter 4.2.3 --- Knowledge Generation --- p.30Chapter 4.2.4 --- Knowledge Dissemination --- p.30Chapter 4.3 --- The 4 levels of FKM --- p.31Chapter 5 --- Level 1: Range Detection --- p.32Chapter 5.1 --- Basic idea --- p.32Chapter 5.2 --- Detection cycle --- p.32Chapter 5.3 --- Mathematical Model --- p.32Chapter 5.4 --- Knowledge generation --- p.34Chapter 6 --- Level 2: Momentum Detection --- p.36Chapter 6.1 --- Basic idea --- p.36Chapter 6.2 --- Detection cycle --- p.36Chapter 6.3 --- Mathematical Model --- p.37Chapter 6.4 --- Knowledge generation --- p.38Chapter 7 --- Level 3: Case Detection --- p.40Chapter 7.1 --- Basic Idea --- p.40Chapter 7.2 --- Technical Analysis --- p.40Chapter 7.3 --- Details and Characteristics of Chart Patterns --- p.41Chapter 7.3.1 --- Continuation and Reversal Patterns --- p.41Chapter 7.3.2 --- Bar Charts --- p.42Chapter 7.3.3 --- Different Patterns --- p.42Chapter 7.4 --- Mathematical Model --- p.54Chapter 7.4.1 --- Smoothing of Data 一 Exponential Smoothing --- p.55Chapter 7.4.2 --- Recognition of Different Patterns --- p.57Chapter 7.4.3 --- Detection Cycle --- p.59Chapter 7.5 --- Knowledge generation --- p.60Chapter 8 --- Level 4: Scenario Detection --- p.62Chapter 8.1 --- Basic idea --- p.62Chapter 8.2 --- Detection cycle --- p.65Chapter 8.2.1 --- RETRIEVE --- p.66Chapter 8.2.2 --- REUSE --- p.75Chapter 8.2.3 --- REVISE --- p.76Chapter 8.2.4 --- RETAIN --- p.82Chapter 8.3 --- Knowledge Generation --- p.82Chapter 9 --- Experiments and Research Findings --- p.85Chapter 9.1 --- Experiments on Monitoring and Detection --- p.85Chapter 9.1.1 --- Precision and Recall --- p.85Chapter 9.1.2 --- Architecture of FKM --- p.86Chapter 9.1.3 --- Experiment and Result Analysis --- p.88Chapter 9.2 --- Evaluation of Knowledge Management --- p.89Chapter 9.2.1 --- Evaluation Design --- p.90Chapter 9.2.2 --- Result Analysis --- p.91Chapter 10 --- Conclusion and Future Work --- p.94Chapter 10.1 --- Conclusion --- p.94Chapter 10.2 --- Future Direction --- p.95Appendix I A Survey on Investors of Hong Kong --- p.96Appendix II Theories on Cross-Market Relation --- p.99Appendix III Mathematical Model for Patterns --- p.102Bibliography --- p.10