M.Ing. (Engineering Management) / Driving sustainability, optimising return on investments and cultivating a competitive market advantage, are imperative for organisational success and growth. In order to achieve the business objectives and value proposition, effective management strategies must be efficiently implemented, monitored and controlled. Failure to do so ultimately result in; financial loss due to increased capital and operational expenditure, schedule slippages, substandard delivery on quality and depreciation of market share. This research paper investigates and discusses management strategies with the focus on integration of effective portfolio management, efficient system development life cycles and optimal project control to ultimately drive organisational sustainability and growth. With the aid of this research, optimal decisions on project/organisational venture selection can be made. Furthermore, integrating portfolio management strategies with system development life cycles and optimal project control strategies, will optimise an organisational portfolio and enhance the probability of project and organisational success.

Investors and financial analysts spend an inordinate amount of time, resources and effort in an attempt to perfect the science of maximising the level of financial returns. To this end, the field of distribution modelling and analysis of firm size effect is important as an investment analysis and appraisal tool. Numerous studies have been conducted to determine which distribution best fits stock returns (Mandelbrot, 1963; Fama, 1965 and Akgiray and Booth, 1988). Analysis and review of earlier research has revealed that researchers claim that the returns follow a normal distribution. However, the findings have not been without their own limitations in terms of the empirical results in that many also say that the research done does not account for the fat tails and skewness of the data. Some research studies dealing with the anomaly of firm size effect have led to the conclusion that smaller firms tend to command higher returns relative to their larger counterparts with a similar risk profile (Banz, 1981). Recently, Janse van Rensburg et al. (2009a) conducted a study in which both non- normality of stock returns and firm size effect were addressed simultaneously. They used a scale mixture of two normal distributions to compare the stock returns of large capitalisation and small capitalisation shares portfolios. The study concluded that in periods of high volatility, the small capitalisation portfolio is far more risky than the large capitalisation portfolio. In periods of low volatility they are equally risky. Janse van Rensburg et al. (2009a) identified a number of limitations to the study. These included data problems, survivorship bias, exclusion of dividends, and the use of standard statistical tests in the presence of non-normality. They concluded that it was difficult to generalise findings because of the use of only two (limited) portfolios. In the extension of the research, Janse van Rensburg (2009b) concluded that a scale mixture of two normal distributions provided a more superior fit than any other mixture. The scope of this research is an extension of the work by Janse van Rensburg et al. (2009a) and Janse van Rensburg (2009b), with a view to addressing several of the limitations and findings of the earlier studies. The Janse van rensburg (2009b) study was based on data from the Johannesburg Stock Exchange (JSE); this study seeks to compare their research by looking at the New York Stock Exchange (NYSE) to determine if similar results occur in developed markets. For analysis purposes, this study used the statistical software package R (R Development Core Team 2008) and its package mixtools (Young, Benaglia, Chauveau, Elmore, Hettmansperg, Hunter, Thomas, Xuan 2008). Some computation was also done using Microsoft Excel. This dissertation is arranged as follows: Chapter 2 is a literature review of some of the baseline studies and research that supports the conclusion that earlier research finding had serious limitations. Chapter 3 describes the data used in the study and gives a breakdown of portfolio formation and the methodology used in the study. Chapter 4 provides the statistical background of the methods used in this study. Chapter 5 presents the statistical analysis and distribution fitting of the data. Finally, Chapter 6 gives conclusions drawn from the results obtained in the analysis of data as well as recommendations for future work.

This thesis is focused on IT Project Portfolio Management and the creation of tools for teaching it. The objectives are first to summarize the evolution of IT Project Portfolio Management, then to extend the current process of project selection with other elements and points of view, and also to create a software tool for teaching IT Project Portfolio Management. The thesis deals with the emergence and subsequent development of IT Project Portfolio Management and its benefits, problems, and concepts, which are necessary for deeper understanding of the issue. Furthermore, the thesis describes the cycle of IT Project Portfolio Management and highlights the important moments and trends. In addition, it focuses on the processes used in the context of portfolio management and its impact on the company and its employees. It also lists some options how to limit its and how to improve the quality of project plans. The focus of the thesis is also on the process of criteria selection and ways of obtaining appropriate weights of criteria and on other methods of selecting projects. The last chapter contains a manual how to work with the attached MS Excel file. The file provides a tool for the assessment of projects.

This thesis generalizes stochastic portfolio theory in two different aspects. The first part demonstrates the functional generation of portfolios in a pathwise way. This notion of functional generation of portfolios was first introduced by E.R. Fernholz, to construct a variety of portfolios solely in the terms of the individual companies' market weights. I. Karatzas and J. Ruf developed recently another approach to the functional construction of portfolios, which leads to very simple conditions for strong relative arbitrage with respect to the market. Both of these notions of functional portfolio generation are generalized in a pathwise, probability-free setting; portfolio generating functions, possibly less smooth than twice-differentiable, involve the current market weights, as well as additional bounded-variation functionals of past and present market weights. This generalization leads to a wider class of functionally-generated portfolios than was heretofore possible to analyze, and to improved conditions for outperforming the market portfolio over suitable time-horizons. The second part develops portfolio theory in open markets. An open market is a subset of the entire equity market, composed of a certain fixed number of top-capitalization stocks. Though the number of stocks in open market is fixed, the constituents of the market change over time as each company's rank by its market capitalization fluctuates. When one is allowed to invest also in money market, an open market resembles the entire 'closed' equity market in the sense that most of the results that are valid for the entire market, continue to hold when investment is restricted to the open market. One of these results is the equivalence of market viability (lack of arbitrage) and the existence of num\'eraire portfolio (portfolio which cannot be outperformed). When access to the money market is prohibited, the class of portfolios shrinks significantly in open markets. In such a case, we discuss the Capital Asset Pricing Model, how to construct functionally-generated portfolios, and the concept of universal portfolio in open market setting.

Diese englischsprachige Dissertation behandelt ausgewählte Fragen zum Thema Portfoliomanagement in Energiemärkten. Im Kontext der modernen Portfoliotheorie werden theoretische Verteilungsannahmen untersucht, die einen optimalen Mittelwert-Varianz-Ansatz implizieren. Der Bereich zu Energiemärkten befasst sich einerseits mit Kurzfristprognosen von Day-Ahead-Preisen auf dem Strommarkt. Andererseits werden auf dem Erdgasmarkt die von komplexen Energiederivaten impliziten Volatilitäten analysiert. Einige interessante Beiträge, die diese Dissertation liefert, sind beispielsweise (i) die Erkenntnis, dass sich der Mittelwert-Varianz-Ansatz zur Bestimmung eines optimalen Portfolios von Vermögensgegenständen auch im Falle einer schiefen Renditeverteilung theoretisch rechtfertigen lässt, (ii) eine umfangreiche Vergleichsstudie mit verschiedenen Ansätzen zur Reduktion der Komplexität von multivariaten Strompreisprognosen und (iii) die Entwicklung eines theoretischen Rahmens und effizienten Algorithmus zur Übersetzung von Preisen für Swing-Optionen in implizite Volatilitäten.

No description available.

Wang, Yu. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 33-35). / Abstracts in English and Chinese. / Abstract --- p.ii / 摘要 --- p.iii / Chapter I. --- Introduction and Overview --- p.1 / Chapter II. --- Literature Review --- p.6 / Chapter 1. --- Price Impact Literatures --- p.6 / Chapter 2. --- Cost Measurement Literatures --- p.9 / Chapter 3. --- Trading Friction Literatures --- p.11 / Chapter III. --- Sample Description --- p.13 / Chapter 1. --- Data Source --- p.13 / Chapter 2. --- Selection Criteria for Sample Stocks --- p.14 / Chapter 3. --- Summary of Statistics --- p.15 / Chapter i. --- General Description --- p.15 / Chapter ii. --- Shanghai Stock Exchange versus Shenzhen Stock Exchange --- p.16 / Chapter iii. --- Normality Test --- p.17 / Chapter IV. --- Regression Analysis --- p.19 / Chapter 1. --- Sales Premium Estimation --- p.19 / Chapter 2. --- Statistics of the Estimated Sales Premium --- p.20 / Chapter 3. --- Factors that Impact the Sales Premium --- p.22 / Chapter i. --- Panel Data Regression --- p.22 / Chapter ii. --- Results and Interpretations --- p.23 / Chapter iii. --- Sales Premium versus Economic Events --- p.25 / Chapter IV. --- Robustness Tests. --- p.27 / Chapter 1. --- Common Robustness Tests --- p.27 / Chapter i. --- Validity of Fixed-Effect Model --- p.27 / Chapter ii. --- Autocorrelation Problem: Durbin-Watson tests --- p.27 / Chapter iii. --- Heteroskedasticity --- p.28 / Chapter iv. --- Consistency of Estimators --- p.28 / Chapter 2. --- Additional Variable for Sales Premium Estimation in Shenzhen Stock Exchange --- p.29 / Chapter V. --- Conclusion --- p.30 / Bibliography --- p.33 / Chapter Appendix A. --- Graphs --- p.36 / Chapter Appendix B. --- Tables --- p.41

Decidir entre as melhores alternativas de produtos para compor o portfólio de uma empresa é um problema complexo e que envolve múltiplos critérios. Este trabalho tem como foco, a adaptação de um modelo de Gestão de Portfólio de Produtos, que possua um caráter quantitativo, flexível, de fácil aplicação e que contemple requisitos importantes para avaliação da carteira de projetos e produtos das indústrias farmacêuticas. O propósito é que este modelo auxilie os gestores das empresas deste setor na tomada de decisão estratégica em relação ao portfólio atual e futuro dos seus produtos, de maneira mais assertiva e reduzindo as subjetividades das escolhas. A abordagem metodológica utilizada foi a pesquisa-ação, cuja pesquisa de campo foi realizada em uma organização do setor farmacêutico nacional de pequeno porte, que buscava otimizar o seu processo de seleção e priorização de produtos / projetos. Desta forma, a partir de uma revisão sistemática simplificada do tema; do acesso a documentos que descrevem o processo de desenvolvimento de produtos e seleção de projetos da referida indústria; bem como de entrevistas em profundidade com os diretores da empresa, foi possível levantar os principais critérios para a tomada de decisão gerencial estratégica da carteira de produtos. Estes critérios foram alocados em uma estrutura de Gestão de Portfólio de Produtos, desenvolvida por Danilevicz e Ribeiro (2013), intitulada Decisões Estratégicas de INovação (DEIN), a qual deu origem ao modelo de Decisões Estratégicas de INovação para o setor Farmacêutico (DEIN-FARMA). Este modelo ajustado foi aplicado utilizando-se os produtos e projetos reais desta empresa gerando, ao final, um portfólio de produtos definido para o próximo período e com um ganho de inovação de 50%. Logo, o DEIN-FARMA permitiu o alinhamento dos produtos às estratégias da empresa, a otimização dos recursos, a redução dos riscos inerentes aos lançamentos, o balanceamento do portfólio e a maximização do seu valor. / Decision making in product portfolio of a company is a complex problem that involves multiple criteria. The aim of this study is the adaptation of a Product Portfolio Management Model. This model must to be quantitative, flexible, easy to be applied, and including important requirements for evaluating the pharmaceutical projects and products. The purpose of this model is to serve as a tool to help managers of the sector to make a strategic decision about the current and future portfolio of their products, being more assertive and decreasing the subjectivity of choices. The methodological approach used was the action research, whose fieldwork was carried out in a Brazilian pharmaceutical industry, seeking to optimize their process of selection and prioritization of their products / projects. Thus, from a simplified systematic review of the subject; access to the documents that describe the process of product development and selection of projects, as well as, in-depth interviews with the directors of the company , it was possible to raise the main criteria for making strategic management decision of the product portfolio. These criteria were allocated on a structure of Product Portfolio Management, previously developed, called Strategic Decisions of Innovation (DEIN), which gave rise to the Strategic Decisions of Innovation model for the Pharmaceutical Industry (DEIN-FARMA). This adjusted model was applied using the real products and projects of this company generating, in the end, a product portfolio set for the next period with a gain of 50% in innovation. Soon the DEIN-FARMA allowed the alignment of the products to the strategies of company, optimize resources, reduce inherent risks, balancing the portfolio and hence maximization of its value.

Decidir entre as melhores alternativas de produtos para compor o portfólio de uma empresa é um problema complexo e que envolve múltiplos critérios. Este trabalho tem como foco, a adaptação de um modelo de Gestão de Portfólio de Produtos, que possua um caráter quantitativo, flexível, de fácil aplicação e que contemple requisitos importantes para avaliação da carteira de projetos e produtos das indústrias farmacêuticas. O propósito é que este modelo auxilie os gestores das empresas deste setor na tomada de decisão estratégica em relação ao portfólio atual e futuro dos seus produtos, de maneira mais assertiva e reduzindo as subjetividades das escolhas. A abordagem metodológica utilizada foi a pesquisa-ação, cuja pesquisa de campo foi realizada em uma organização do setor farmacêutico nacional de pequeno porte, que buscava otimizar o seu processo de seleção e priorização de produtos / projetos. Desta forma, a partir de uma revisão sistemática simplificada do tema; do acesso a documentos que descrevem o processo de desenvolvimento de produtos e seleção de projetos da referida indústria; bem como de entrevistas em profundidade com os diretores da empresa, foi possível levantar os principais critérios para a tomada de decisão gerencial estratégica da carteira de produtos. Estes critérios foram alocados em uma estrutura de Gestão de Portfólio de Produtos, desenvolvida por Danilevicz e Ribeiro (2013), intitulada Decisões Estratégicas de INovação (DEIN), a qual deu origem ao modelo de Decisões Estratégicas de INovação para o setor Farmacêutico (DEIN-FARMA). Este modelo ajustado foi aplicado utilizando-se os produtos e projetos reais desta empresa gerando, ao final, um portfólio de produtos definido para o próximo período e com um ganho de inovação de 50%. Logo, o DEIN-FARMA permitiu o alinhamento dos produtos às estratégias da empresa, a otimização dos recursos, a redução dos riscos inerentes aos lançamentos, o balanceamento do portfólio e a maximização do seu valor. / Decision making in product portfolio of a company is a complex problem that involves multiple criteria. The aim of this study is the adaptation of a Product Portfolio Management Model. This model must to be quantitative, flexible, easy to be applied, and including important requirements for evaluating the pharmaceutical projects and products. The purpose of this model is to serve as a tool to help managers of the sector to make a strategic decision about the current and future portfolio of their products, being more assertive and decreasing the subjectivity of choices. The methodological approach used was the action research, whose fieldwork was carried out in a Brazilian pharmaceutical industry, seeking to optimize their process of selection and prioritization of their products / projects. Thus, from a simplified systematic review of the subject; access to the documents that describe the process of product development and selection of projects, as well as, in-depth interviews with the directors of the company , it was possible to raise the main criteria for making strategic management decision of the product portfolio. These criteria were allocated on a structure of Product Portfolio Management, previously developed, called Strategic Decisions of Innovation (DEIN), which gave rise to the Strategic Decisions of Innovation model for the Pharmaceutical Industry (DEIN-FARMA). This adjusted model was applied using the real products and projects of this company generating, in the end, a product portfolio set for the next period with a gain of 50% in innovation. Soon the DEIN-FARMA allowed the alignment of the products to the strategies of company, optimize resources, reduce inherent risks, balancing the portfolio and hence maximization of its value.

Decidir entre as melhores alternativas de produtos para compor o portfólio de uma empresa é um problema complexo e que envolve múltiplos critérios. Este trabalho tem como foco, a adaptação de um modelo de Gestão de Portfólio de Produtos, que possua um caráter quantitativo, flexível, de fácil aplicação e que contemple requisitos importantes para avaliação da carteira de projetos e produtos das indústrias farmacêuticas. O propósito é que este modelo auxilie os gestores das empresas deste setor na tomada de decisão estratégica em relação ao portfólio atual e futuro dos seus produtos, de maneira mais assertiva e reduzindo as subjetividades das escolhas. A abordagem metodológica utilizada foi a pesquisa-ação, cuja pesquisa de campo foi realizada em uma organização do setor farmacêutico nacional de pequeno porte, que buscava otimizar o seu processo de seleção e priorização de produtos / projetos. Desta forma, a partir de uma revisão sistemática simplificada do tema; do acesso a documentos que descrevem o processo de desenvolvimento de produtos e seleção de projetos da referida indústria; bem como de entrevistas em profundidade com os diretores da empresa, foi possível levantar os principais critérios para a tomada de decisão gerencial estratégica da carteira de produtos. Estes critérios foram alocados em uma estrutura de Gestão de Portfólio de Produtos, desenvolvida por Danilevicz e Ribeiro (2013), intitulada Decisões Estratégicas de INovação (DEIN), a qual deu origem ao modelo de Decisões Estratégicas de INovação para o setor Farmacêutico (DEIN-FARMA). Este modelo ajustado foi aplicado utilizando-se os produtos e projetos reais desta empresa gerando, ao final, um portfólio de produtos definido para o próximo período e com um ganho de inovação de 50%. Logo, o DEIN-FARMA permitiu o alinhamento dos produtos às estratégias da empresa, a otimização dos recursos, a redução dos riscos inerentes aos lançamentos, o balanceamento do portfólio e a maximização do seu valor. / Decision making in product portfolio of a company is a complex problem that involves multiple criteria. The aim of this study is the adaptation of a Product Portfolio Management Model. This model must to be quantitative, flexible, easy to be applied, and including important requirements for evaluating the pharmaceutical projects and products. The purpose of this model is to serve as a tool to help managers of the sector to make a strategic decision about the current and future portfolio of their products, being more assertive and decreasing the subjectivity of choices. The methodological approach used was the action research, whose fieldwork was carried out in a Brazilian pharmaceutical industry, seeking to optimize their process of selection and prioritization of their products / projects. Thus, from a simplified systematic review of the subject; access to the documents that describe the process of product development and selection of projects, as well as, in-depth interviews with the directors of the company , it was possible to raise the main criteria for making strategic management decision of the product portfolio. These criteria were allocated on a structure of Product Portfolio Management, previously developed, called Strategic Decisions of Innovation (DEIN), which gave rise to the Strategic Decisions of Innovation model for the Pharmaceutical Industry (DEIN-FARMA). This adjusted model was applied using the real products and projects of this company generating, in the end, a product portfolio set for the next period with a gain of 50% in innovation. Soon the DEIN-FARMA allowed the alignment of the products to the strategies of company, optimize resources, reduce inherent risks, balancing the portfolio and hence maximization of its value.