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Stock market forecasting by integrating time-series and textual information.

Fung Pui Cheong Gabriel. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2003. / Includes bibliographical references (leaves 88-93). / Abstracts in English and Chinese. / Abstract (English) --- p.i / Abstract (Chinese) --- p.ii / Acknowledgement --- p.iii / Contents --- p.v / List of Figures --- p.ix / List of Tables --- p.x / Chapter Part I --- The Very Beginning --- p.1 / Chapter 1 --- Introduction --- p.2 / Chapter 1.1 --- Contributions --- p.3 / Chapter 1.2 --- Dissertation Organization --- p.4 / Chapter 2 --- Problem Formulation --- p.6 / Chapter 2.1 --- Defining the Prediction Task --- p.6 / Chapter 2.2 --- Overview of the System Architecture --- p.8 / Chapter Part II --- Literatures Review --- p.11 / Chapter 3 --- The Social Dynamics of Financial Markets --- p.12 / Chapter 3.1 --- The Collective Behavior of Groups --- p.13 / Chapter 3.2 --- Prediction Based on Publicity Information --- p.16 / Chapter 4 --- Time Series Representation --- p.20 / Chapter 4.1 --- Technical Analysis --- p.20 / Chapter 4.2 --- Piecewise Linear Approximation --- p.23 / Chapter 5 --- Text Classification --- p.27 / Chapter 5.1 --- Document Representation --- p.28 / Chapter 5.2 --- Document Pre-processing --- p.30 / Chapter 5.3 --- Classifier Construction --- p.31 / Chapter 5.3.1 --- Naive Bayes (NB) --- p.31 / Chapter 5.3.2 --- Support Vectors Machine (SVM) --- p.33 / Chapter Part III --- Mining Financial Time Series and Textual Doc- uments Concurrently --- p.36 / Chapter 6 --- Time Series Representation --- p.37 / Chapter 6.1 --- Discovering Trends on the Time Series --- p.37 / Chapter 6.2 --- t-test Based Split and Merge Segmentation Algorithm ´ؤ Splitting Phrase --- p.39 / Chapter 6.3 --- t-test Based Split and Merge Segmentation Algorithm - Merging Phrase --- p.41 / Chapter 7 --- Article Alignment and Pre-processing --- p.43 / Chapter 7.1 --- Aligning News Articles to the Stock Trends --- p.44 / Chapter 7.2 --- Selecting Positive Training Examples --- p.46 / Chapter 7.3 --- Selecting Negative Training Examples --- p.48 / Chapter 8 --- System Learning --- p.52 / Chapter 8.1 --- Similarity Based Classification Approach --- p.53 / Chapter 8.2 --- Category Sketch Generation --- p.55 / Chapter 8.2.1 --- Within-Category Coefficient --- p.55 / Chapter 8.2.2 --- Cross-Category Coefficient --- p.56 / Chapter 8.2.3 --- Average-Importance Coefficient --- p.57 / Chapter 8.3 --- Document Sketch Generation --- p.58 / Chapter 9 --- System Operation --- p.60 / Chapter 9.1 --- System Operation --- p.60 / Chapter Part IV --- Results and Discussions --- p.62 / Chapter 10 --- Evaluations --- p.63 / Chapter 10.1 --- Time Series Evaluations --- p.64 / Chapter 10.2 --- Classifier Evaluations --- p.64 / Chapter 10.2.1 --- Batch Classification Evaluation --- p.69 / Chapter 10.2.2 --- Online Classification Evaluation --- p.71 / Chapter 10.2.3 --- Components Analysis --- p.74 / Chapter 10.2.4 --- Document Sketch Analysis --- p.75 / Chapter 10.3 --- Prediction Evaluations --- p.75 / Chapter 10.3.1 --- Simulation Results --- p.77 / Chapter 10.3.2 --- Hit Rate Analysis --- p.78 / Chapter Part V --- The Final Words --- p.80 / Chapter 11 --- Conclusion and Future Work --- p.81 / Appendix --- p.84 / Chapter A --- Hong Kong Stocks Categorization Powered by Reuters --- p.84 / Chapter B --- Morgan Stanley Capital International (MSCI) Classification --- p.85 / Chapter C --- "Precision, Recall and F1 measure" --- p.86 / Bibliography --- p.88

Identiferoai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_324329
Date January 2003
ContributorsFung, Pui Cheong Gabriel., Chinese University of Hong Kong Graduate School. Division of Systems Engineering and Engineering Management.
Source SetsThe Chinese University of Hong Kong
LanguageEnglish, Chinese
Detected LanguageEnglish
TypeText, bibliography
Formatprint, xi, 93 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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