by Lau Chung-Hing. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1988. / Includes bibliographical references.

by Ip Ka Tsun Anthony and Tang Ying Wa. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1998. / Includes bibliographical references (leaves 42-46). / ABSTRACT --- p.i / TABLE OF CONTENTS --- p.iii / LIST OF TABLES --- p.iv / ACKNOWLEDGMENTS --- p.v / Chapter / Chapter I. --- INTRODUCTION --- p.1 / Chapter II . --- LITERATURE REVIEW --- p.4 / Selection Criteria of the Neglected Markets --- p.4 / Market Review --- p.4 / Day-of-the-Week Effect --- p.9 / Month- of - the - Year Effect --- p.11 / Spill´ؤOver Effect Across National Stock Markets --- p.11 / Granger Causality Between Aggregate Stock Price and Trading Volume --- p.13 / Chapter III. --- DATA and METHODOLOGY --- p.16 / Day-of-the-Week Effect and Month-of-the-Year Effect --- p.16 / Spill-Over Effect Across National Stock Markets and Granger Causality Between Aggregate Stock Price and Trading Volume --- p.18 / Chapter IV. --- EMPIRICAL RESULTS --- p.24 / Day-of-the-Week Effect --- p.24 / Month-of-the-Year Effect --- p.26 / Spill-Over Effect Across National Stock Markets --- p.28 / Granger Causality Between Aggregate Stock Price and Trading Volume --- p.31 / Chapter V. --- CONCLUSION --- p.36 / Direction of Further Studies --- p.38 / APPENDIX --- p.40 / BIBLIOGRAPHY --- p.42

published_or_final_version / Applied Statistics / Master / Master of Social Sciences

This thesis examines the theoretical underpinnings and practical construction of select economic and financial indexes. Such indexes are used for a variety of purposes, including the measurement of inflation, portfolio return performance, and firm productivity. Chapter 1 motivates interest in economic and financial indexes and introduces the principal ideas in the thesis. Chapter 2 focuses on one potential source of bias in the Canadian consumer price index (CPI) that arises from the emergence of large discount/warehouse stores—the so-called outlet substitution bias. Such outlets have gained market share in Canada in recent years, but current CPI procedures fail to capture the declines in average prices that consumers enjoy when they switch to such outlets. Unrepresentative sampling, and the fact that discount stores often deliver lower rates of price increase can further bias the CPI. Bias estimates for some elementary indexes are computed using data from Statistics Canada's CPI production files for the province of Ontario. It is shown that the effect on the Canadian CPI of inappropriately accounting for such discount outlets can be substantial. Another area in which indexes are frequently used is the stock market. Several stock market indexes exist, including those produced by Dow Jones and Company, Standard and Poor's Corporation, Frank Russell and Company, among others. These indexes differ in two fundamental respects: their composition and their method of computation—with important implications for their usage and interpretation. Chapter 3 introduces the concept of a stock index by asking what, in fact a stock market index is—this is tantamount to considering the purpose for which the index is intended, since stock indexes should be constructed according to their usage. Because stock indexes are most commonly used as measures of returns on portfolios, the main considerations in constructing such return indexes are examined. Chapter 4 uses the Dow Jones Industrial Average (DJIA) as a case study to examine its properties as a return index. It is shown that the DJIA is not the return on a market portfolio consisting of its thirty component stocks: in fact the DJIA measures the return performance on a very particular (and unusual) investment strategy, a fact that is not well understood by institutional investors. An examination of some other popular stock indexes shows that they all differ in their computational formula and that each is consistent with a particular investment strategy. Numerical calculations reveal that the return performance of the DJIA can vary considerably with the choice of basic index number formula, particularly over shorter time horizons. Given the numerous ways of constructing stock market return indexes, the user is left to determine which is 'best' in some sense. The choice of an appropriate (or 'best') formula for a stock market index is formally addressed in chapter 5. The test or axiomatic approach to standard bilateral index number theory as in Eichhorn & Voeller (1983), Diewert (1993a), and Balk (1995) is adapted here. A number of a priori desirable properties (or axioms) are proposed for a stock index whose purpose is to measure the gross return on a portfolio of stocks. It is shown that satisfaction of a certain subset of axioms implies a definite functional form for a stock market return index. Chapter 6 evaluates the various stock indexes is use today in terms of their usefulness as measures of gross returns on portfolios. To this end the axioms developed in chapter 5 are used to provide a common evaluative framework, in the sense that some of the indexes satisfy certain axioms while others do not. It is shown that the shortcomings of the DJIA as a measure of return arise from its failure to satisfy a number of the basic axioms proposed. Notwithstanding this, each index corresponds to a different investment strategy. Thus, when choosing an index for benchmarking purposes an investor should select one which closely matches his/her investment strategy—a choice that cannot be made by appealing to axioms alone.

This thesis examines the theoretical underpinnings and practical construction of select economic and financial indexes. Such indexes are used for a variety of purposes, including the measurement of inflation, portfolio return performance, and firm productivity. Chapter 1 motivates interest in economic and financial indexes and introduces the principal ideas in the thesis. Chapter 2 focuses on one potential source of bias in the Canadian consumer price index (CPI) that arises from the emergence of large discount/warehouse stores—the so-called outlet substitution bias. Such outlets have gained market share in Canada in recent years, but current CPI procedures fail to capture the declines in average prices that consumers enjoy when they switch to such outlets. Unrepresentative sampling, and the fact that discount stores often deliver lower rates of price increase can further bias the CPI. Bias estimates for some elementary indexes are computed using data from Statistics Canada's CPI production files for the province of Ontario. It is shown that the effect on the Canadian CPI of inappropriately accounting for such discount outlets can be substantial. Another area in which indexes are frequently used is the stock market. Several stock market indexes exist, including those produced by Dow Jones and Company, Standard and Poor's Corporation, Frank Russell and Company, among others. These indexes differ in two fundamental respects: their composition and their method of computation—with important implications for their usage and interpretation. Chapter 3 introduces the concept of a stock index by asking what, in fact a stock market index is—this is tantamount to considering the purpose for which the index is intended, since stock indexes should be constructed according to their usage. Because stock indexes are most commonly used as measures of returns on portfolios, the main considerations in constructing such return indexes are examined. Chapter 4 uses the Dow Jones Industrial Average (DJIA) as a case study to examine its properties as a return index. It is shown that the DJIA is not the return on a market portfolio consisting of its thirty component stocks: in fact the DJIA measures the return performance on a very particular (and unusual) investment strategy, a fact that is not well understood by institutional investors. An examination of some other popular stock indexes shows that they all differ in their computational formula and that each is consistent with a particular investment strategy. Numerical calculations reveal that the return performance of the DJIA can vary considerably with the choice of basic index number formula, particularly over shorter time horizons. Given the numerous ways of constructing stock market return indexes, the user is left to determine which is 'best' in some sense. The choice of an appropriate (or 'best') formula for a stock market index is formally addressed in chapter 5. The test or axiomatic approach to standard bilateral index number theory as in Eichhorn & Voeller (1983), Diewert (1993a), and Balk (1995) is adapted here. A number of a priori desirable properties (or axioms) are proposed for a stock index whose purpose is to measure the gross return on a portfolio of stocks. It is shown that satisfaction of a certain subset of axioms implies a definite functional form for a stock market return index. Chapter 6 evaluates the various stock indexes is use today in terms of their usefulness as measures of gross returns on portfolios. To this end the axioms developed in chapter 5 are used to provide a common evaluative framework, in the sense that some of the indexes satisfy certain axioms while others do not. It is shown that the shortcomings of the DJIA as a measure of return arise from its failure to satisfy a number of the basic axioms proposed. Notwithstanding this, each index corresponds to a different investment strategy. Thus, when choosing an index for benchmarking purposes an investor should select one which closely matches his/her investment strategy—a choice that cannot be made by appealing to axioms alone. / Arts, Faculty of / Vancouver School of Economics / Graduate

Then, we consider the patterns between news stream and time series indices stream. We first transform the news stream into a set of bursty feature (keywords) time series streams and propose three technique to study their relationship to time series index. First, we explore a Non-homogeneous Hidden Markov Model (NHMM) to predict the stock market process which takes both stock prices and news articles into consideration. Second, we propose a risk analytical model to predict the volatility of price indices by integrating news information. Finally, we devise an algorithm to detect the priming event from text and a time series index. The evaluation on real world dataset suggests the significant correlation exists between news stream and time series stream and our pattern discover algorithm can detect promising patterns from this relationship to support real world applications effectively. / We start from investigating the co-movement relationship of multiple time series. We propose techniques to study two aspects of this problem. First, we propose a co-movement model for constructing financial portfolio by analyzing and mining the co-movement patterns among two time series. Second, we presents an efficient streaming algorithm to discover leaders from multiple time series stream. Both of the algorithms are evaluated using real time series indices data and the result proves that co-movement patterns and detected leaders are promising and can support various applications including portfolio management, high frequency trading and risk management. / With the increasing amount of data in financial market, there are two types of data streams attracting a lot of research and studies, time series index stream and related news stream. In this thesis, we focus on discovering patterns from these data streams and try to answer the following challenging questions, (I) given two co-evolving time series indices, what is the co-movement dependency between them. (II) given a set of evolving time series, could we detect some leaders from them whose rise or fall impacts the behavior of many other time series? (III) could we integrate the news stream information into stock price prediction? (IV) could we integrate the news stream information into stock risk analysis? and (V) could we detect what are those events that trigger time series index movement. For each of the question, we design algorithms and address three technique issues (I) how to detect promising patterns from the noisy financial data; (II) how to update the old patterns when new data arrives in high frequency; (III) how to use the pattern to support the financial applications. / Wu, Di. / Adviser: Jeffrey Xu Pu. / Source: Dissertation Abstracts International, Volume: 73-01, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 124-131). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest dissertations and theses, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

This thesis explores whether scanner data can be used to inform Consumer Price Index (CPI) construction, with particular reference to the issues of substitution bias and choice of aggregation dimensions. The potential costs and benefits of using scanner data are reviewed. Existing estimates of substitution bias are found to show considerable variation. An Australian scanner data set is used to estimate substitution bias for six different aggregation methods and for fixed base and superlative indexes. Direct and chained indexes are also calculated. Estimates of substitution bias are found to be highly sensitive to both the method of aggregation used and whether direct or chained indexes were used. The ILO (2004) recommends the use of dissimilarity indexes to determine the issue of when to chain. This thesis provides the first empirical study of dissimilarity indexes in this context. The results indicate that dissimilarity indexes may not be sufficient to resolve the issue. A Constant Elasticity of Substitution (CES) index provides an approximate estimate of substitution-bias-free price change, without the need for current period expenditure weights. However, an elasticity parameter is needed. Two methods, referred to as the algebraic and econometric methods, were used to estimate the elasticity parameter. The econometric approach involved the estimation of a system of equations proposed by Diewert (2002a). This system has not been estimated previously. The results show a relatively high level of substitution at the elementary aggregate level, which supports the use a Jevons index, rather than Carli or Dutot indexes, at this level. Elasticity parameter estimates were found to vary considerably across time, and statistical testing showed that elasticity parameter estimates were significantly different across estimation methods. Aggregation is an extremely important issue in the compilation of the CPI. However, little information exists about 'appropriate' aggregation methods. Aggregation is typically recommended over 'homogenous' units. An hedonic framework is used to test for item homogeneity across four supermarket chains and across all stores within each chain. This is a novel approach. The results show that treating the same good as homogenous across stores which belong to the same chain may be recommended.

This thesis explores whether scanner data can be used to inform Consumer Price Index (CPI) construction, with particular reference to the issues of substitution bias and choice of aggregation dimensions. The potential costs and benefits of using scanner data are reviewed. Existing estimates of substitution bias are found to show considerable variation. An Australian scanner data set is used to estimate substitution bias for six different aggregation methods and for fixed base and superlative indexes. Direct and chained indexes are also calculated. Estimates of substitution bias are found to be highly sensitive to both the method of aggregation used and whether direct or chained indexes were used. The ILO (2004) recommends the use of dissimilarity indexes to determine the issue of when to chain. This thesis provides the first empirical study of dissimilarity indexes in this context. The results indicate that dissimilarity indexes may not be sufficient to resolve the issue. A Constant Elasticity of Substitution (CES) index provides an approximate estimate of substitution-bias-free price change, without the need for current period expenditure weights. However, an elasticity parameter is needed. Two methods, referred to as the algebraic and econometric methods, were used to estimate the elasticity parameter. The econometric approach involved the estimation of a system of equations proposed by Diewert (2002a). This system has not been estimated previously. The results show a relatively high level of substitution at the elementary aggregate level, which supports the use a Jevons index, rather than Carli or Dutot indexes, at this level. Elasticity parameter estimates were found to vary considerably across time, and statistical testing showed that elasticity parameter estimates were significantly different across estimation methods. Aggregation is an extremely important issue in the compilation of the CPI. However, little information exists about 'appropriate' aggregation methods. Aggregation is typically recommended over 'homogenous' units. An hedonic framework is used to test for item homogeneity across four supermarket chains and across all stores within each chain. This is a novel approach. The results show that treating the same good as homogenous across stores which belong to the same chain may be recommended.

Thesis (Ph. D.)--University of California, San Diego, 1999. / Vita. Includes bibliographical references.

This study evaluates existing methods for developing price indices for defense products, proposes an alternative method based on hedonic analysis, and develops price indices for U.S . Army vehicles using the proposed method. Prices indices are estimated for combat vehicles, and trucks and trailers. The period covered is 1981 through 1985. The estimated hedonic price indices show that for trucks and trailers existing historical price indices significantly understate inflation. The estimated hedonic index is 4 to 6 times higher than comparable indices in all years except 1985. In 1985, the index reflected significant deflation which placed it well below comparable indices. The deflation experienced during this period may have, in part, been due to the enactment of the Competition in Contracting Act in 1984. This Act dramatically increased competition for Government contracts. It was not possible to estimate price indices for combat vehicles due to the paucity of data. However, should additional price and attribute data become available it is believed that price indices can be developed using the hedonic approach. Based on the results of this study it is obvious that existing methods for developing price indices are not optimum and hedonic analysis is a viable method for constructing price indices for selected applications. / M.A.