The proposition of this dissertation is that superior capital budgeting solutions can be attained by not only analyzing projects individually but rather as part of a portfolio of projects that has the objective of maximizing the company’s range of multiple objectives, not only the economic benefit. The dissertation starts with a detailed study of current techniques and an assessment of flaws and shortcomings. This study concludes with the requirements that any new approach or model must address in order to improve on the current practices. Based on these requirements, a new model is developed based on the portfolio approach that integrates all the assumptions, constraints, project and variable interrelationships. An important feature of the model is that it selects its portfolio of capital projects in such a way that it optimizes support for the company’s multiple objectives, not only the economic objective. The dissertation concludes with the application of this model to a hypothetical case. It is concluded that, by developing and using this model, a company can improve the analysis required before capital budgets are finalized. / Dissertation (MEng (Industrial Engineering))--University of Pretoria, 2006. / Industrial and Systems Engineering / unrestricted

The recent global financial crisis, regulatory and compliance requirements placed on organisations, and the need for scientific research in the project portfolio management discipline were factors that motivated this research. The interest and contribution to the body of knowledge in project portfolio management has been growing significantly in recent years, however, there still appears to be a misalignment between literature and practice. A particular area of concern is the decision-making, during the management of the portfolio, regarding which projects to accelerate, suspend, or terminate. A lack of determining the individual and cumulative contribution of projects to strategic objectives leads to poorly informed decisions that negate the positive effect that project portfolio management could have in an organisation. The focus of this research is, therefore, aimed at providing a mechanism to determine the individual and cumulative contribution of projects to strategic objectives so that the right decisions can be made regarding those projects. This thesis begins with providing a context for project portfolio management by confirming a definition and providing a theoretical background through related theories. An investigation into the practice of project portfolio management then provides insight into the alignment between literature and practice and confirms the problem that needed to be addressed. A conceptual model provides a solution to the problem of determining the individual and cumulative contribution of projects to strategic objectives. The researcher illustrates how the model can be extended before verifying and validating the conceptual model. Having the ability to determine the contributions of projects to strategic objectives affords decision makers the opportunity to conduct what-if scenarios, enabled through the use of dashboards as a visualization technique, in order to test the impact of their decisions before committing them. This ensures that the right decisions regarding the project portfolio are made and that the maximum benefit regarding the strategic objectives is achieved. This research provides the mechanism to enable better-informed decision- making regarding the project portfolio. / Computing / D. Phil. (Computer science)

L'objectif de cette thèse est d’étudier à côté du risque défaut, le rôle spécifique des risques de volatilité et de co-volatilité dans la formation des taux longs dans la zone euro. On propose en particulier un modèle théorique de choix de portefeuille à deux pays permettant d’évaluer la contribution des primes de risque de volatilité aux processus de contagion et de fuite vers la qualité dans différents épisodes de la crise de la dette souveraine. Ce modèle permet également d’analyser le rôle des achats d’actifs (QE) de la BCE sur l’équilibre des marchés obligataires. Nos tests empiriques suggèrent que les programmes QE de la BCE à partir de mars 2015 n’ont fait qu’accélérer « une défragmentation » des marchés obligataires de la zone euro, apparue plus tôt dans la crise, dès la mise en place de l’OMT. / This thesis examines the specific role of volatility risks and co-volatility in the formation of long-term interest rates in the euro area. In particular, a two-country theoretical portfolio choice model is proposed to evaluate the volatility risk premia and their contribution to the contagion and flight to quality processes. This model also provides an opportunity to analyze the ECB's role of asset purchases (QE) on the equilibrium of bond markets. Our empirical tests suggest that the ECB's QE programs from March 2015 have accelerated the "defragmentation" of the euro zone bond markets.

This thesis explores the application of Markowitz' Modern Portfolio Theory onto 220 years of financial returns for 13 metals and 21 poly-metallic ore types. The interdisciplinary research shows that poly-metallic ores can be described as naturally occurring portfolios that were diversified by natural geological processes. Safest and optimal portfolios for metals and ores can be computed for different time horizons using portfolio optimization algorithms. Results for optimized ore portfolios are thereby subject to geological constraints. The study revealed that commodity cycles last between six and twenty years and exhibit clockwise and counterclockwise motions in the risk-return framework. The cycle length differences for clockwise cycles are statistically significant and thus specific to all investigated metals and ores. By incorporating novel cycle parameters into decision making tools it is suggested that current industry decisions for resource development can be improved. Insights into the performance of metals and ores through the industrial cycles, as well as into the frequency of profitable super cycles can assist Metals & Mining executives in strategic planning and investment.:Introduction 1 Data 3 Metals & ore types studied 5 2.1 Metals.......................................... 5 2.2 Ore types ........................................ 5 2.3 Prices .......................................... 10 2.4 Summary ........................................ 12 II Analysis 13 3 Modern Portfolio Theory 15 3.1 Overview ........................................ 15 3.2 Definitions........................................ 15 3.3 Assumptions ...................................... 17 3.4 Discussion & Conclusion................................ 18 4 Poly-metallic ores as natural portfolios 19 4.1 Objectives........................................ 19 4.2 Results.......................................... 19 4.3 Summary & Discussion................................. 24 4.4 Conclusion ....................................... 25 5 Static portfolio optimization 27 5.1 Objectives........................................ 27 5.2 Assumptions ...................................... 27 5.3 Results.......................................... 27 5.4 Summary & Discussion................................. 31 5.5 Conclusion ....................................... 32 6 Dynamic portfolio optimization 33 6.1 Assumptions ...................................... 33 6.2 Results.......................................... 34 6.3 Summary & Discussion................................. 44 6.4 Conclusion ....................................... 45 7 Commodity cycles & metal assets 47 7.1 Commodity cycles ................................... 47 7.2 Commodity cycle observations ............................ 54 7.3 Summary ........................................ 76 7.4 Discussion........................................ 77 7.5 Conclusion ....................................... 78 III Application 81 8 Commodity cycles & resource development strategies 83 8.1 The timing of mine development and mining start-up................ 83 8.2 Lead times from discovery to operation........................ 88 8.3 Exploration....................................... 89 8.4 Project valuation considerations............................ 91 8.5 Summary & Discussion................................. 92 8.6 Conclusion ....................................... 93 9 Industrial cycles & modern history 95 9.1 The Metal Markets Indicator-MMI ......................... 95 9.2 The Metal Markets Indicator & the economy .................... 97 9.3 The MMI & military conflict ............................. 105 9.4 MMI cyclicality..................................... 115 9.5 Summary & Discussion................................. 122 9.6 Conclusion ....................................... 123 10 Industrial cycles & metal performance 125 10.1 Methodology ...................................... 125 10.2 Metal performance during technological epochs ................ 126 10.3 Discussion........................................ 133 10.4 Conclusion ....................................... 137 11 Industrial cycles & ore type preferences 139 11.1 Coal Age ........................................ 139 11.2 Oil Age ......................................... 142 11.3 Atomic Age....................................... 144 11.4 Discussion........................................ 146 11.5 Conclusion ....................................... 150 12 Industrial cycles & ore provinces 151 12.1 Ore genetic models and industrial cycles....................... 151 12.2 Ore geology and geography .............................. 154 12.3 Ore provenances and mining technology ....................... 156 12.4 Discussion........................................ 157 12.5 Conclusion ....................................... 157 13 The state and future of the M&M Industry 159 13.1 The current state.................................... 159 13.2 The dawn of a new Industrial Age .......................... 163 13.3 The future........................................ 164 13.4 Summary & Discussion................................. 167 13.5 Conclusion ....................................... 168 14 Summary 169 15 Conclusion 171 IV Appendix 173 Bibliography 233 Index 245

In this thesis the relationship between regional composition and risk-adjusted performance is evaluated concerning Swedish issued green mutual equity funds. By using three different indices; Sharpe, Jensen and Treynor, a relationship has been able to establish. The study finds no strong relationship between geographic composition and performance concerning any of the indices and thus the impact of diversifying one's portfolio has little impact. By using the Modern Portfolio Theory, Stewardship Theory, Home Bias Theory and Behavioral Finance Theory a theoretical discussion has been established in order to further examine and analyze the fundamental dynamics of this relationship. Lastly, model risk and other variables impact on performance has been investigated. Our study finds a potential model risk since our three indices results disparate. Further, ESG related factors and Morningstar ratings seem to impact performance greater than regional composition.

In 2005 Attilio Meucci presented his article Beyond Black-Litterman: Views on Non-Normal Markets which introduces the copula opinion pooling approach using generic non-normal market assumptions. Copulas and opinion pooling are used to express views on the market which provides a posterior market distribution that smoothly blends an arbitrarily distributed market prior distribution with arbitrarily chosen views. This thesis explains how to use this method in practice and investigates its performance in different investment situations. The method is tested on three portfolios, each showing some different feature. The conclusions that can be drawn are e.g. that the method can be used in many different investment situations in many different ways, implementation and calculations can be made within a few seconds for a large data set and the method could be useful for portfolio managers using mathematical methods. The presented examples together with the method generate reasonable results.

The financial markets have a complex structure and the modelling techniques have recently been more and more complicated. So for a portfolio manager it is very important to find better and more sophisticated modelling techniques especially after the 2007-2008 banking crisis. The idea in this thesis is to find the connection between the components in macroeconomic environment and portfolios consisting of assets from OMX Stockholm 30 and use these relationships to perform Tactical Asset Allocation (TAA). The more specific aim of the project is to prove that dynamic modelling techniques outperform static models in portfolio theory. / Den finansiella marknaden är av en väldigt komplex struktur och modelleringsteknikerna har under senare tid blivit allt mer komplicerade. För en portföljförvaltare är det av yttersta vikt att finna mer sofistikerade modelleringstekniker, speciellt efter finanskrisen 2007-2008. Idéen i den här uppsatsen är att finna ett samband mellan makroekonomiska faktorer och aktieportföljer innehållande tillgångar från OMX Stockholm 30 och använda dessa för att utföra Tactial Asset Allocation (TAA). Mer specifikt är målsättningen att visa att dynamiska modelleringstekniker har ett bättre utfall än mer statiska modeller i portföljteori.

Capital Asset Pricing Model (CAPM) is an equilibrium model to test relationship between expected return and market risk (Sharpe, 1964). The model research on pricing and return when the securities market reaches equilibrium and investors are rational and investing by diversification based on Markovitz portfolio theory (Markovitz, 1952). Fama and MacBeth (1973) proposed a cross-sectional testing methodology on CAPM and this regression method has been widely used in testing CAPM in developed markets since then. While CAPM is hard to explain more and more market anomalies (excessive return in smaller market value company) in cross section regression, Fama and French (1992) added two more factors (SMB and HML) and proposed three factor model. The empirical results show that three factor model is superior to CAPM in developed markets. Relevant studies have been conducted by Manjuunatha (2006) and Trimech et al. (2015) but show different results. This dissertation will use Fama-MacBeth cross section approach to test CAPM and Fama-French's three factor model in Chinese and Polish stock market respectively. Following Fama and MacBeth (1972) and Shweta and Anil (2015), three sub periods of Polish and Chinese stock market returns ranging from 2007 to 2018 are examined. The empirical results in this thesis...

Indiana University-Purdue University Indianapolis (IUPUI) / This dissertation consists of two essays on nonprofit finance. Nonprofit finance concerns obtaining and managing financial resources to support the social purposes of nonprofit organizations. A unique feature of nonprofit finance is that nonprofits derive revenue from a variety of sources. Nonprofit finance thus involves answering two fundamental questions: What is the optimal combination of revenue sources that supports a nonprofit to achieve its mission? Where and how to obtain the revenue sources? The two dissertation essays address these two questions respectively. The first essay, titled “Modern Portfolio Theory and the Optimization of Nonprofit Revenue Mix,” is among the first to properly apply modern portfolio theory (MPT) from corporate finance to nonprofit finance. By analyzing nonprofit tax return data, I estimate the expected return and risk characteristics for five nonprofit revenue sources as well as the correlations among these returns. I use the estimates to identify the efficient frontiers for nonprofits in different industries, based on which nonprofit managers can select an optimal portfolio that can minimize the risk given a preferred level of service provision or maximize the return given a level of risk. The findings also pose a challenge to the predominant approach used in previous nonprofit finance studies (Herfindahl-Hirschman Index) and suggest that MPT is theoretically and practically more helpful in guiding nonprofit revenue management. The second essay, titled “Charitable Giving in Nonprofit Service Associations: Identities, Incentives, and Gender Differences,” concerns nonprofit resource attainment, specifically, how do decisionmaking contexts and framing affect donations. Membership in a service club is characterized by two essential elements: members’ shared interest in the club’s charitable mission; and private benefits that often come as a result of social interactions with other members, such as networking, fellowship, and fun. A laboratory experiment was designed to examine 1) whether membership in a service club makes a person more generous and 2) the effect of service club membership—stressing either the service or socializing aspects—on individual support for collective goods. The study finds that female individuals are the least generous when they are reminded of the socializing aspect of service-club membership.

[pt] A teoria moderna de carteiras estabelece que a alocação ótima de ativos é uma função da média-variância da distribuição dos retornos. Na prática, estes retornos são modelados por distribuições Gaussianas e seus parâmetros são estimados a partir dos dados históricos do mercado, utilizando técnicas descritivas da estatística Frequentista. A dinâmica atual dos mercados globalizados gera períodos aleatórios de alta e baixa volatilidade e/ou saltos nos retornos dos ativos, provocando mudanças de regime ou quebras estruturais na série temporal dos retornos, tornando-os não Gaussianos. Consequentemente, a teoria moderna de carteiras precisa ser adaptada para atender a estas novas condições do mercado. Para contornar o problema das mudanças de regime, propõe-se a substituição do mecanismo de otimização baseada no índice de Sharpe pela otimização baseada na medida Ômega. Isto porque a medida Ômega tem a vantagem de quantificar o risco-retorno de qualquer distribuição de probabilidade e não somente distribuições Gaussianas como acontece com o índice de Sharpe, ou seja, as distribuições de retornos não Gaussianos provocadas pelas mudanças de regime são tratadas naturalmente pela medida Ômega. Para contornar o problema das quebras estruturais, propõe-se a substituição do procedimento de estimação dos parâmetros da distribuição dos retornos, baseada em técnicas da estatística Frequentista por técnicas da estatística Bayesiana. Isto porque a estatística Bayesiana, tem a vantagem de combinar as informações públicas do mercado (dados históricos dos retornos) com informações privadas do investidor (visões prospectivas do mercado) permitindo corrigir a quebra estrutural e, na sequência, tratar o retorno não Gaussiano, utilizando o mecanismo de otimização baseada na medida Ômega. / [en] Modern portfolio theory states that the optimal asset allocation is a function of the mean-variance of the distribution of returns. In practice, these returns are modeled by Gaussian distributions and their parameters are estimated from historical market data, using descriptive techniques of Frequentist statistics. The current dynamics of globalized markets generate random periods of high and low volatility and/or jumps in asset returns, causing regime shifts or structural breaks in the time series of returns, making them non Gaussian. Consequently, modern portfolio theory needs to be adapted to meet these new market conditions. To circumvent the problem of regime shifts, it is proposed to replace the optimization mechanism based on the Sharpe index by the optimization based on the Omega measure. This is because the Omega measure has the advantage of quantifying the risk-return of any probability distribution and not only Gaussian distributions as with the Sharpe index, that is, non Gaussian returns distributions caused by regime shifts are treated naturally by the Omega measure. To circumvent the problem of structural breaks, it is proposed to replace the estimation procedure for the parameters of the distribution of returns, based on Frequentist statistics techniques, by Bayesian statistical techniques. This is because the Bayesian statistic has the advantage of combining public market information (historical return data) with private investor information (prospective market views) allowing to correct the structural break, and subsequently, treating the non Gaussian return using the optimization based on the Omega measure.