This thesis examines the relationship between stock market returns and systematic risk factors in twelve industrial countries. Using the APT framework, the thesis investigates the notion of international stock market integration versus segmentation in terms of pricing risk, international stock market efficiency in terms of eliminating arbitrage opportunities across domestic markets, and the validity of the international version of the APT according to a model that specifies purely domestic factors. Starting with ordinary least squares estimation the thesis investigates the responses of investors in their national stock markets to systematic shocks. By employing iterative non-linear multivariate seemingly unrelated regression estimation, this work avoids the statistical problems encountered in the second-pass test of the two-stage procedure. This study found that the international stock market was neither integrated nor efficient and that the IAPT was not supported by the results during the period investigated. It was demonstrated that partial and regional integration, regional efficiency, and regional IAPT validity cannot be ruled out. Moreover, the alternative model proved to be practically valid. / United Arab Emirates University

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Many portfolios diversify by including mutual funds and exchange traded funds counting equities linked to various world country market indices, e.g. the S&P 500 of the United States and the Nikkei 225 of Japan. However a necessary condition for an international portfolio to be beneficial is that the correlation of returns between markets be low or at least non unity. My thesis will explore through extensive correlation analyses how advanced and emerging country indices are interrelated. The inspiration for my thesis came from the dissertation of Yale Ph.D. Graduate Charles H. Yang's research published in 1999, Essays on International Market Correlations. Yang tested correlation market data from 1972-1997 and found in 16 advanced country indices that the markets were becoming steadily and increasingly correlated over the 26 years studied. My thesis will expand on Yang's research with 32 total indices from advanced and emerging markets such as the Jakarta index of Indonesia, the Merval index of Argentina, and All-Ordinaries of Australia to assess if the world's financial markets are continuing integration, with the strongest correlations increasing between advanced markets. One of the objectives of my correlation research is to equip novice investors in advanced markets such as the U.S. with up-to-date information to enable them to be cautious but more open to investing in emerging economies, which have typically been classified as too risky. My thesis will shed light on how correlation analysis can be used to improve investment strategies and thereby permit investors to exploit the current wave of globalization to earn superior returns.

The Purchasing Managers’ Index (PMI) has been shown to provide useful indications on where the economy is heading (Afshar et al., 2007; Koenig, 2002; Harris, 1991). We examine the predictive abilities of PMI on stocks that are sensitive to business cycle movements by testing if the index can contribute to forecasting a group of Swedish industrial machinery stocks during 2012-2023. We approach this by employing pairwise Granger Causality tests, using PMI data from five countries, and stock performance data for 11 industrial machinery stocks included in the OMXS30. The results indicate that PMI cannot contribute to forecasting the stock performance. Instead, we find empirical evidence of a predictive relationship in the opposite direction, suggesting that the stock performance can forecast the PMI.

Doctor of Philosophy / Department of Economics / Lance J. Bachmeier / This dissertation investigates the long run and short run relationships between Saudi stock market returns and eight macroeconomic variables. We investigate the ability of these variables to predict the level and volatility of Saudi stock market returns. A wide range of Vector autoregression (VAR) and generalized autoregressive conditional heteroskedasticity (GARCH) models estimated and interpreted. A Johansen-Juselius cointegration test indicates a positive long run relationship between the Saudi stock price index and the M2 money supply, bank credit, and the price of oil, and a negative long run relationship with the M1 money supply, the short term interest rate, inflation, and the U.S. stock market. An estimated vector error correction model (VECM) suggests significant unidirectional short run causal relationships between Saudi stock market returns and the money supply and inflation. The VECM also finds a significant long run causal relationship among the macroeconomic variables in the system. The estimated speed of adjustment indicates that the Saudi stock market converges to the equilibrium within half a year. Granger causality tests show no causal relationship between Saudi stock market returns and the exchange rate. Impulse response function analysis shows no significant relationship between Saudi stock market returns and the macroeconomic variables. Forecast error variance decompositions suggest that 89% of the variation in Saudi stock market returns is attributable to its own shock, which implies that Saudi stock market returns are largely independent of the macroeconomic variables in the system. Finally, a GARCH-X model indicates a significant relationship between volatility of Saudi stock returns and short run movements of macroeconomic variables. Implications of this study include the following. (i) Prediction of stock market returns becomes more difficult as the volatility of the macroeconomic variables increases in the short run. (ii) Investors should look at the systematic risks revealed by these macroeconomic variables when structuring their portfolios and diversification strategies. (iii) Policymakers should seek to minimize macroeconomic fluctuations considering the effect of macroeconomic variables changes on the stock market when formulating economic policy.

Financial markets, particularly capital and stock markets, play an important role in mobilizing and canalising the idle savings of individuals and institutions to the investment options where they are really required for productive purposes. The prediction of stock prices and returns is carried out in order to enhance the quality of investment decisions in stock markets, but it is considered to be tricky and complicates tasks as these prices behave in a random fashion and vary with time. Owing to the potential of returns and inherent risk factors in stock market returns. Various stock market prediction models and decision support systems such as Capital asset pricing model, the arbitrage pricing theory of Ross, the inter-temporal capital asset pricing model of Merton ,Fama and French five-factor model, and zero beta model to provide investors with an optimal forecast of stock prices and returns. In this research thesis, a stock market prediction model consisting of two parts is presented and discussed. The first is the three factors of the Fama and French model (FF) at the micro level to forecast the return of the portfolios on the Saudi Arabian Stock Exchange (SASE) and the second is a Value Based Management (VBM) model of decision-making. The latter is based on the expectations of shareholders and portfolio investors about taking investment decisions, and on the behaviour of stock prices using an accurate modern nonlinear technique in forecasting, known as Artificial Neural Networks (ANN). This study examined monthly data relating to common stocks from the listed companies of the Saudi Arabian Stock Exchange from January 2007 to December 2011. The stock returns were predicted using the linear form of asset pricing models (capital asset pricing model as well as Fama and French three factor model). In addition, non-linear models were also estimated by using various artificial neural network techniques, and adaptive neural fuzzy inference systems. Six portfolios of stock predictors are combined using: average, weighted average, and genetic algorithm optimized weighted average. Moreover, value-based management models were applied to the investment decision-making process in combination with stock prediction model results for both the shareholders’ perspective and the share prices’ perspective. The results from this study indicate that the ANN technique can be used to predict stock portfolio returns; the investment decisions and the behaviour of stock prices, optimized by the genetic algorithm weighted average, provided better results in terms of error and prediction accuracy compared to the simple linear form of stock price prediction models. The Fama and French model of stock prediction is better suited to Saudi Arabian Stock Exchange investment activities in comparison to the conventional capital assets pricing model. Moreover, the multi-stage type1 model, which is a combination of Fama and French predicted stock returns and a value-based management model, gives more accurate results for the stock market decision-making process for investment or divestment decisions, as well as for observing variation in and the behaviour of stock prices on the Saudi stock market. Furthermore, the study also designed a graphic user interface in order to simplify the decision-making process based upon Fama and French and value-based management, which might help Saudi investors to make investment decisions quickly and with greater precision. Finally, the study also gives some practical implications for investors and regulators, along with proposing future research in this area.

Four research projects have been carried out with the objective of providing insights into some of the popular Asian investment myths and beliefs. The studies also throw some light on the efficiency of one Asian stock market. At the same time, the results reported in these research papers provide pragmatic investment guidelines for Asian emerging stock market investors. These research efforts add depth and breath (sic) to the existing emerging stock market investment literature, especially on Asian emerging stock markets. The Four Research Papers were : Research Paper I : Stock Selection Criteria During the Bull Run in the Malaysian Stock Market; Research Paper II : How Important Were Political Factors for Asian Stock Market Investors Throughout the Recent Financial Crisis?; Research Paper III : Active Equity Management versus Passive Equity Management - The Case of Malaysia from the Perspective of Foreign Investors; Research Paper IV : Stock Selection Criteria during the Bear Phase of the Malaysian Stock Market. Four popular myths/beliefs (myliefs) were selected for in-depth study with the conviction that the findings from these four studies could provide an insight into the emerging Malaysia stock market. The selection of the myliefs is mainly based on the popularity of the mylief as well as the applicability of the research results in the view of a foreigner investor / Doctor of Business Administration

We study some aspects of liquidity of stocks traded through the National Stock Exchange (NSE) of India. Initially we examine the multi-dimensional nature of liquidity by conducting day-wise factor analysis of eleven liquidity proxies across a cross-section of stocks, using data from two periods reflecting different market conditions. Five factors emerge consistently, interpretable as depth, spread, volume, price elasticity and relative activity. Subsequently, we study execution of limit orders in the NSE from three angles. First we consider order execution probability, using 106 stock-specific logistic models. Important predictors of order execution probability are price premium followed by volatility, relative activity, bid ask spread and order imbalance. Some differences are noted when comparing companies of different sizes and between buy and sell orders. Second, we study order execution times using survival analysis. Several diagnostic tests indicate that parametric Accelerated Failure Time models using the log-logistic distribution for the survival time S(t) are suitable for current data. 100 stock-specific models are built; results are consistent with the logistic models. Additionally depth is also found to be important. Finally we build 4 combined models across stocks for both execution probabilities as well as times. These models perform well on out of sample data, suggesting their predictive utility.

Prior studies have shown that investment knowledge and motivation increases when students in a school setting have access to a stock trading learning platform.  This thesis aims to further investigate if a stand-alone online stock trading learning platform, on its own, can help non stock investors understand financial literacy concepts.It further attempts to identify what type of system functionality that is most beneficial for the beginner when it comes to understanding and applying these concepts.  To explore this, an MVP stock trading learning platform1 was initially developed so that new features could be implemented and modified freely, without being bound by existing software. The development was done using the lean UX method and Jobs To Be Done interviews. From this, it was found that merely enabling the users to trade stocks (without risk) did not significantly help them to understand investing concepts and draw new conclusions.  New functionality was then added to the learning platform, in the form of a historical propagation feature. It lets the user assemble a stock portfolio and see what the portfolio would be worth today if bought earlier. This enabled the user to quickly and interactively see the effects of diversification and return of investment over time. Pre/post interviews showed that the platform, with historical propagation functionality, altered the users perception of both diversification and return, which indicates that it also has the potential to affect financial literacy. / Tidigare studier har visat att investerings-kunskap och motivation ökar när elever i en skolmiljö har tillgång till en inlärningsplattform för aktiehandel.  Detta examensarbete syftar till att ytterligare undersöka om en fristående online- aktie-inlärningsplattform, i sig, kan hjälpa icke-aktieinvesterare att förstå begrepp rörande finansiell kompetens. Arbetet försöker vidare identifiera vilken typ av systemfunktionalitet som är mest fördelaktig för nybörjaren när det gäller att förstå och tillämpa dessa begrepp.  För att utforska detta utvecklades inledningsvis en MVP (minimum viable product) lärplattform för aktiehandel så att nya funktioner kunde implementeras och modifieras fritt utan att begränsas av befintlig programvara. Utvecklingen skedde med hjälp av lean UX-metoden och Jobs To Be Done intervjuer. Av arbetet kunde man konstatera att funktionaliteten med att bara göra det möjligt för användarna att handla aktier (utan risk) inte hjälpte dem nämnvärt att förstå investerings-koncept och dra nya slutsatser.  Ny funktionalitet lades sedan till på inlärnings-plattformen i form av en historiepropagagerings-funktion. Funktionen låter användaren skapa en aktieportfölj och se vad portföljen skulle vara värd idag om den köptes tidigare. Detta gjorde det möjligt för användaren att snabbt och interaktivt se effekterna av diversifiering och resultatet av investeringar över tid. Pre / post intervjuer visade att plattformen, med historiepropagerings-funktionalitet, förändrade användarnas uppfattning om både diversifiering och avkastning, vilket indikerar att den också har potential att påverka finansiell kompetens.

Wang, Xiaolei. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2008. / Includes bibliographical references (leaves 34-39). / Abstracts in English and Chinese. / Chapter Chapter 1. --- Introduction --- p.1 / Chapter Chapter 2. --- Identification of Stock Market Crashes --- p.5 / Chapter 2.1 --- Identification Criteria --- p.7 / Chapter 2.2 --- Identification Results --- p.8 / Chapter Chapter 3. --- Data --- p.10 / Chapter 3.1 --- Data Issue for Chapter 4 --- p.10 / Chapter 3.2 --- Data Issue for Chapter 5 --- p.12 / Chapter 3.3 --- Data Issue for Chapter 6 --- p.12 / Chapter Chapter 4. --- Examination of AFE --- p.13 / Chapter 4.1 --- Definition of AFE and MAAFE --- p.13 / Chapter 4.2 --- Examination of MAAFE --- p.14 / Chapter 4.3 --- Examination of AFE by Grouping Duration --- p.15 / Chapter Chapter 5. --- Examination of AFD --- p.18 / Chapter Chapter 6. --- Examination of the Relationship between AFD and ESR --- p.22 / Chapter 6.1 --- Portfolio Strategy - Sorting by Size and Dispersion --- p.23 / Chapter 6.2 --- Portfolio Strategy - Sorting by Size and Book to Market Ratio --- p.26 / Chapter 6.3 --- Fama-French Time Series Regression Test (Three-Factor Model) --- p.28 / Chapter 6.4 --- Fama-French Time Series Regression Test (Three-Factor Model with Dispersion on the Right Hand Side) --- p.30 / Chapter 6.5 --- Introduction of a Nonlinear Form of AFD to the Fama-French Model --- p.31 / Chapter Chapter 7. --- Conclusions --- p.32 / References --- p.34 / Appendix Table I to Table XVI --- p.40-55 / Figure I to Figure VI --- p.56-61