The purpose of this investigation was to explore the relationship between the general psychological mood of the population regarding the national economy and its effect upon the level of stock market prices. It was hypothesized that there should be evidence of a positive relation between the two. In an effort to explain stock price levels several models were constructed which contained various component variables, among which were an Index of Consumer Mood, GNP, Corporate Earnings Before Tax, Money Supply and Canadian Government Long-Term Bond Interest Rates. All datum covered 38 quarters, from 3rd quarter I960 to 4th quarter 1969. From these variables five models were constructed containing three equations each. Five tests were conducted on the five individual models in which the correlations, multiple regressions and polynomial distributed lags were measured. Various tests contained data based on first differences deflated values, relative differences and combinations thereof. A final test was with the exclusion of the Consumer Mood variable in order to judge the effect its presence had made upon the accuracy of the equations. The conclusions based upon the results of the tests must initially indicate that the general psychological consumer attitude has little bearing upon the level of stock prices. Deflated money supply however, proved to be highly relevant and a valuable predictor. The total picture presented by the models is unsatisfactory, requiring either the substitution of more accurate variables or the inclusion of further data to supplant the inefficiency of the variables that were used. The components employed in the tests were both inefficient in some cases and insufficient in others. The results must only indicate areas for further investigation and refinement of the datum. Any generalization on the lack of statistical support for a relationship between consumer confidence and stock prices to the effect of consumer opinions about the economy as a whole would neither be reasonable nor justifiable at this time. / Business, Sauder School of / Finance, Division of / Graduate

This research tested whether wavelet based algorithms can improve the performance of intraday share trading algorithms. The trading algorithms investigated, each consisted of two parts: the first part performed share price prediction and the second part traded based on the prediction. All the trades in the shares BTI, MTN, NPN and SBK through 2013 on the JSE with the associated time stamps, transaction share prices and volumes, served as the basic sample. The sample was further reduced by using end-of-interval transaction share prices at intervals of one, two, five and ten minutes throughout the trade days. Three types of prediction algorithms were employed: auto regressive moving average (ARMA), wavelet-ARMA and wavelet regressive algorithms. The wavelet based algorithms were further broken down by using up to six different levels of scales in each of the algorithms. These algorithms were fitted using the first half year of data while the tests were conducted on the second half year of data. Two trade algorithms were created by the researcher: One algorithm for buyand- sell and another for short-and-close. Both algorithms used the predicted share price one and two intervals ahead as input and took transaction cost into account. The trade algorithms entered the market daily after opening time and exited the market before closing time. The wavelet based algorithms were not found to improve the accuracy of share price prediction. However, in agreement with previous research, wavelet based algorithms were found to improve the accuracy of predicting the direction of the share prices. The wavelet based algorithms were also found to improve trading performance. Short-and-close algorithms outperformed buy-and-sell. None of the intraday trade algorithms were found to outperform buy-and-hold over the test period. This study contributes to academic research regarding the manner in which wavelet based and ARMA algorithms were combined, the application of a wavelet-regressive prediction method to financial time series and the application of wavelet based trading algorithms on an intraday time scale. / Dissertation (MBA)--University of Pretoria, 2014. / lmgibs2015 / Gordon Institute of Business Science (GIBS) / MBA / Unrestricted

published_or_final_version / abstract / Economics and Finance / Doctoral / Doctor of Philosophy

by Lo Yat-keung & Ma Kwok-wa. / Bibliography: leaves 46-47 / Thesis (M.B.A.)--Chinese University of Hong Kong, 1986

Hao He. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2006. / Includes bibliographical references (leaves 84-86). / Abstracts in English and Chinese. / Abstract / Chapter Chapter 1. --- Introduction --- p.1 / Chapter Chapter 2. --- Literature Review --- p.3 / Chapter 2.1 --- Recent Work on Synchronicity --- p.3 / Chapter 2.2 --- Recent Work on Corporate Governance --- p.5 / Chapter 2.3 --- Motivation´ؤWhy Stock Return Synchronicity Matters --- p.6 / Chapter Chapter 3. --- Theory and Hypotheses --- p.9 / Chapter 3.1 --- Derivation of Dependent Variables --- p.9 / Chapter 3.1.1 --- Corporate Governance Mechanisms --- p.9 / Chapter 3.1.1.1 --- Static Corporate Governance Mechanisms --- p.9 / Chapter 3.1.1.2 --- Dynamic Corporate Governance Mechanisms --- p.11 / Chapter 3.1.2 --- Regional Governance Mechanisms --- p.12 / Chapter 3.2 --- Quantification of Dependent Variables --- p.14 / Chapter 3.2.1 --- Quantifying corporate Governance Mechanisms --- p.14 / Chapter 3.2.1.1 --- Quantifying Static Corporate Governance Mechanisms --- p.14 / Chapter 3.2.1.2 --- Quantifying Dynamic Corporate Governance Mechanisms --- p.15 / Chapter 3.2.2 --- Quantifying Regional Governance Mechanisms --- p.19 / Chapter 3.2.3 --- Quantifying Control Variables --- p.22 / Chapter Chapter 4. --- Data --- p.23 / Chapter 4.1 --- Sample --- p.23 / Chapter 4.2 --- Definitions of Main Synchronicity Measures --- p.25 / Chapter 4.3 --- Methdology --- p.26 / Chapter Chapter 5 --- Empirical Results --- p.27 / Chapter 5.1 --- Results on Corporate Governance Mechanisms --- p.27 / Chapter 5.1.1 --- Results on Static Corporate Governance Mechanisms --- p.27 / Chapter 5.1.2 --- Results on Dynamic Corporate Governance Mechanisms --- p.29 / Chapter 5.1.2.1 --- Results on President-Changing Variables --- p.29 / Chapter 5.1.2.2 --- Results on General manager-change Variables --- p.31 / Chapter 5.2 --- Results on Regional Governance Mechanisms --- p.34 / Chapter Chapter 6. --- Conclusion --- p.36 / Reference --- p.38 / Tables and Figures --- p.41

by Ho Man Shing, William. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 41-42). / ABSTRACT --- p.i / TABLE OF CONTENTS --- p.iii / LIST OF FIGURE --- p.v / LIST OF TABLES --- p.v / Chapter / Chapter I. --- INTRODUCTION --- p.1 / Objectives of Research Project --- p.2 / Chapter II. --- LITERATURE REVIEW --- p.4 / Research work in the U. S --- p.4 / Research work in Japan and H. K --- p.5 / Chapter III. --- METHODOLOGY --- p.7 / Research design --- p.9 / Formation of portfolios --- p.10 / Univariate Analysis --- p.11 / Regression Analysis --- p.11 / Data collection --- p.12 / Chapter IV. --- RESULTS --- p.13 / Univariate analysis of returns and fundamental variables --- p.13 / Regression analysis of returns and fimdamental variables --- p.17 / Security level regression analysis of returns and fimdamental variables --- p.17 / Portfolio level regression analysis of returns and fundamental variables (ranked by different fundamental variables) --- p.21 / Portfolio level regression analysis of returns and fundamental variables (ranked by two different fundamental variables) --- p.27 / Effects of order of agglomeration and different combinations --- p.30 / Chapter V. --- SUMMARY AND CONCLUDING REMARKS --- p.37 / BIBLIOGRAPHY --- p.41 / APPENDICES / Chapter A --- List of Hang Seng Index Constituent Stocks during 1989 to1994 / Chapter B --- Print-out of the Regression Results at Security Level / Chapter C --- Print-out of the Regression Results at Portfolio Level (E/P then LS) / Chapter D --- Print-out of the Regression Results at Portfolio Level (LS then E/P)

published_or_final_version / Business Administration / Master / Master of Business Administration

published_or_final_version / Business Administration / Master / Master of Business Administration

Thesis. 1980. Ph.D.--Massachusetts Institute of Technology. Alfred P. Sloan School of Management. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND DEWEY. / Vita. / Bibliography: leaves 103-106. / Ph.D.

by Lam Suk-ting, Angelina, Lin Yuen-tung, Anthony. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1995. / Includes bibliographical references (leaves 59-64). / ABSTRACT --- p.ii / ACKNOWLEDGMENTS --- p.iii / TABLE OF CONTENTS --- p.iv / LIST OF FIGURES --- p.vi / LIST OF TABLES --- p.vii / Chapter CHAPTER I. --- INTRODUCTION --- p.1 / Pre-Holiday Effect --- p.1 / Hong Kong Situation --- p.2 / Objectives of The Research --- p.3 / Outline of The Report --- p.3 / Chapter CHAPTER II. --- LITERATURE REVIEW --- p.4 / Literature on Holiday Effect --- p.4 / "Possible Explanations for the "" Holiday Effect""" --- p.7 / Literature Review on Other Anomalies --- p.10 / """January Effect""" --- p.10 / """ Firm Size Effect""" --- p.12 / """ Weekend Effect"" and ""Monday Effect""" --- p.14 / Monthly Effect'' --- p.15 / Literature on Hong Kong Market's Anomalies --- p.16 / Chapter CHAPTER III. --- DATA AND METHODOLOGY --- p.18 / Data --- p.18 / Holiday Selection --- p.19 / Data Source --- p.19 / Methodology --- p.20 / Procedure of Analysis --- p.21 / General Effect Before Holidays --- p.21 / General Effect After Holidays --- p.22 / Individual Holiday Effect --- p.22 / Length of Holiday vs. Market Performance --- p.25 / Theoretical Framework --- p.26 / Student's t Test For Two Separated Samples --- p.27 / Wilcoxon Signed Rank Test --- p.28 / One-Way ANOVA --- p.31 / Chapter CHAPTER IV. --- RESULT --- p.33 / General Pre-Holiday Effect --- p.33 / General Post-Holiday Effect --- p.35 / Individual Holiday Effect --- p.36 / The Pre-Holiday Effect Of Individual Holiday --- p.37 / Returns On Pre-Holiday Trading Day vs. Returns On Three Days Before Holiday --- p.39 / The Post-Holiday Effect Of Individual Holiday --- p.40 / Christmas-New Year Holiday Effect --- p.41 / The Relationship Between Length Of Holiday And Market Performance --- p.42 / Chapter CHAPTER V. --- FURTHER ANALYSIS OF RESULT --- p.44 / "Is the ""Pre-Holiday Effect"" a manifestation of other anomalies ？" --- p.45 / "Not A ""January Effect""" --- p.45 / "Not a "" Week-End Effect""" --- p.48 / Existence of the effect across the whole test period --- p.51 / Chapter CHAPTER VI. --- CONCLUSION --- p.53 / APPENDIX I. LIST OF GENERAL HOLIDAYS IN HONG KONG --- p.55 / APPENDIX II. LENGTH OF HOLIDAY VS. MARKET RETURN --- p.56 / APPENDIX III. CONSTITUENT STOCKS OF HANG SENG INDEX --- p.58 / BIBLIOGRAPHY --- p.59