This dissertation consists of two essays dealing with two selected aspects of the investment decision process faced by individuals and corporations. In the first essay, I develop a model of a multiple-stage patent race between two rival firms to study the impact of technological competition on value and return dynamics of Research and Development (R&D) ventures. The model describes a firm's capital budgeting decision process in the presence of technical uncertainty, market uncertainty and preemption. I characterize the equilibrium of the race and derive optimal investment strategies. Analysis of the equilibrium firm value shows that the premium accruing to the technology "leader" is larger than the loss accruing to the technology "lagger" and that the marginal effect of success/failure is increasing in the uncertainty of cash flows. Risk premia demanded by an ownership claim to competing R&D ventures (i) increase when a rival pulls ahead in the race and (ii) are lower when rivals are "closer" to each other in the development process. Compared to the case where rival firms merge, R&D competition reduces the industry value and lowers the expected completion time for a project. The erosion in value, due to preemption, is higher when firms are "neck-and-neck" and in early stages of development. Numerical simulations show that, in later stages of development, risk premia demanded by the perfectly collusive market are generally lower than risk premia demanded by a portfolio of competing firms. The opposite is true in early stages of development, which suggests that R&D competition may actually lower the cost of early stage financing. In the second essay, I solve a portfolio allocation problem for an individual who can select between two risky assets and a riskless asset in the presence of capital gains taxes. I treat capital gains taxes as a form of endogenous transaction costs. Using this analogy, I characterize the trading strategy for the two assets, and study the effect of taxes on optimal portfolio diversification. The optimal strategy contains a "no trade" region and a dynamic tax-timing option. I find that the diversification costs due to capital gains taxes are substantial and the value of the tax deferral option is decreasing in the correlation among assets and in the volatility of the risky assets. By comparing the solution of the multiple asset portfolio problem to the one of an investor who can trade only in a mutual fund I am able to measure the value of the flexibility option of the multi-asset case as well as the cost of mutual fund turnover. Finally, I show that imposing a wash-sale constraint generates discontinuous portfolio rebalancing strategies. / Business, Sauder School of / Finance, Division of / Graduate

This doctoral dissertation focuses on the area of IT projects portfolio management and IT projects. Dissertation summarizes development of IT projects portfolio management, its benefits, problems, and integration of IT PPM philosophy into selected widely use methodologies and IT frameworks. Further work summarizes developments and main findings of social networks analysis and relevant findings from psychological and sociological field, team work and process of organization. Also presents results of two surveys, on their basis have been formulated conclusions and recommendations. The main part of the work focuses on design of additional processes for MMDIS ŘIP mainly by use of social networks analysis to support the selection of the appropriate staff to selected positions in an IT project. Furthermore, the proposal presents categorization of IT roles according to selected metrics of social network nodes.

Cílem práce je zařadit koncept IT Portfolio Management do kontextu strategického řízení firmy a dále navrhnout model IT Portfolio Managementu, který by byl universálně použitelný v malých a středních podnicích. Model zohledňuje odlišnosti malých a středních podniků a zestručňuje obecný postup implementace IT Portfolio Managementu popsaný v literatuře tak, aby byl lépe srozumitelný pro management takovýchto podniků. Přínos autora je zejména v syntéze teoretických poznatků s praktickými zkušenostmi nabytými během dlouholeté praxe v IT společnosti.

Branding dates back to centuries ago when traders were trying to distinguish their products from others in order to promise a higher quality to their consumers. Today, brands are considered as intangible resources that can have a significant contribution to the firm performance. Based on the Resource-Based Theory (RBT), valuable, rare, inimitable, and non-substitutable brands are strategic resources that create superior value and play a key role in achieving a sustainable competitive advantage over rivals. In the process of developing and maintaining strong brands, brand managers constantly need to make multiple decisions. Whether to add, delete or retail brands are among the routine decisions that brand managers face in managing their brand portfolios. Brand managers need to regularly assess their brand portfolios in order to make sure they are not selling redundant brands. Through brand portfolio assessment, brand managers can recognize weak brands and delete the unprofitable brands from the portfolio in order to free up resources and reinvest them in their stronger and more successful brands to gain competitive advantage in the market. This admonition is in line with the RBT of competitive advantage. This dissertation builds upon and extends previous literature on RBT in the context of brand deletion to achieve three main objectives. The first objective is to find the answer to why companies decide to delete brands from their portfolios. Thus, the focus of the first objective is to identify the organizational (i.e., firm, managerial, and brand) factors that drive the brand deletion strategy in a company. The second goal is to find the answer to the when question through identifying the environmental (i.e., market) factors associated with brand deletion decision making in a company. Finally, the third objective is to go deeper and investigate the different types of brand deletion strategy (i.e., merge, sell, milk, and kill). In other words, the third objective seeks to find the answer to the how question. Deleting brands from the portfolio of a company, being the most sensitive issue in strategic brand portfolio management, is yet understudied in the brand portfolio management literature. This study adds to the literature of strategic brand portfolio management by a) applying the Resource-based Theory (RBT) in the context of brand deletion decision making and b) empirically testing the relationships among the drivers of brand deletion strategies. The findings of this dissertation provide a better understanding on how each of these factors are associated with the brand deletion decision making process in companies. The current dissertation provides practitioners with several managerial insights as well. First, the study identifies and empirically tests several organizational-level factors that drive brand deletion decisions in companies. This will help brand managers be familiar with factors that they need to consider when evaluating their poor-performing brands. Breaking these factors into internal (brand and firm) and external (market) drivers provides practitioners with a better understanding of the brand deletion decision making process. In addition, the findings of this study help managers realize their own role (in terms of their attitude toward deletion and their commitment to the brand) in the brand deletion process. Finally, the identification and discussion of the four types of brand deletion strategy help companies have a clearer picture of how they can remove brands from their portfolios.

This thesis introduces three variable clustering methods designed in the context of diversified portfolio selection. The motivation is to cluster financial assets in order to identify a small set of assets to approximate the level of diversification of the whole universe of stocks. First, we develop a data-driven approach to variable clustering based on a correlation blockmodel, in which assets in the same cluster have the same correlations with all other assets. Under the correlation blockmodel, the assets in the same cluster are controlled by the same latent factor. In addition, each cluster forms an equivalent class among assets, in the sense that the portfolio consisting of one stock from each cluster will have the same correlation matrix, regardless of the specific stocks chosen. We devise an algorithm named ACC (Asset Clustering through Correlation) to detect the clusters, with theoretical analysis and practical guidance for tuning the parameter for the algorithm. Our second method studies a multi-factor block model, which is a generalization of the correlation blockmodel. Under this multi-factor block model, assets in the same cluster are governed by a set of multiple latent factors, instead of a single factor, as in the correlation blockmodel. Observations of the asset returns lie near a union of low-dimensional subspaces under this model. We propose a subspace clustering method that utilizes square-root LASSO nodewise regression to identify these subspaces and recover the corresponding clusters. Through theoretical analysis, we provide a practical and straightforward guidance for choosing the regularization parameters. Existing subspace clustering methods based on regularized nodewise regression often arbitrarily choose the form of the regularization. The parameter that controls the regularization is also often determined exogenously or by cross-validation.Our third method theoretically unifies the choices of the regularizer and its parameter by formulating a distributionally robust version of nodewise regression. In this new formulation, we optimize the worst-case square loss within a region of distributional uncertainty around the empirical distribution. We show that this formulation naturally leads to a spectral-norm regularized optimization problem. In addition, the parameter that controls the regularization is nothing but the radius of the uncertainty region and can be determined easily based on the degree of uncertainty in the data. We also propose an alternating direction method of multipliers (ADMM) algorithm for efficient implementation. Finally, we design and implement an empirical analysis framework to verify the performance of the three proposed clustering methods. This framework consists of four main steps: clustering, stock selection, asset allocation, and portfolio backtesting. The main idea is to select stocks from each cluster to construct a portfolio and then assess the clustering method by analyzing the portfolio's performance. Using this framework, we can easily compare new clustering methods with existing ones by creating portfolios with the same selection and allocation strategies. We apply this framework to the daily returns of the S&P 500 stock universe. Specifically, we compare portfolios constructed using different clustering methods and asset allocation strategies with the S&P 500 Index benchmark. Portfolios from our proposed clustering methods outperform the benchmark significantly. They also perform favorably compared to other existing clustering algorithms in terms of the risk-adjusted return.

The diploma thesis deals with the design and implementation of a transparent resource management system at the portfolio level. Its primary task is to present and implement this system, but also to describe the situations that occurred during its implementation at Garrett Motion. In order to better understand the issue, the theoretical foundations of project management and resource management are presented at the beginning of the thesis. These serve as the basis for the following analysis of the company's environment, design and subsequent implementation of the system.

Limitations of Capital Asset Pricing Model (CAPM) continue to present inconsistent empirical results despite its rm mathematical foundations provided in recent studies. In this thesis, we examine how estimation errors of the CAPM could be minimized using the cross-validation technique, a concept that is widely applied in machine learning (CV-CAPM). We apply our approach to test the assumption of CAPM as a well-diversified portfolio model with data from S&P500 and Dow Jones Industrial Average (DJIA). Our results from the CV-CAPM validate that both S&P500 and DJIA are well-diversified market indices with statistically insignificant variation in unsystematic risks during and after the 2007 financial crisis. Furthermore, the CV-CAPM provides the smallest root mean square errors and mean absolute deviations compared to the traditional CAPM.

Historic market volatility has made risk management decisions by firms in the agricultural supply chain more challenging. Market risk measurement methods, such as Value-at-Risk, were developed in the financial industry to objectively measure, and thus better comprehend, market risk's effect on positions. This thesis gives a thorough background of the issues involved with risk measurement. Different scenarios were then used to demonstrate how the risk measurement method can be applied to the agricultural processing margin. In this thesis, the flour milling margin was used to demonstrate how a firm can incorporate sophisticated risk analytics into its risk management decision making process. Multiple scenarios were developed to account for different situations faced by flour millers. Ocean freight, exchange rate risk, futures price risk, basis risk and flour price risk are all included to provide examples of how market risk measurement can be beneficial to industry participants.

In this dissertation, we adopt the viability approach to mathematical finance developed in the book of Karatzas and Kardaras (2020), and extend it to settings where portfolio choice is constrained. We introduce in Chapter 2 the notions of supermartingale numeraire, supermartingale deflator, and viability. After that, we characterize all supermartingale deflators under conic constraints on portfolio choice. Most importantly, we prove a fundamental theorem for equity market structure and arbitrage theory under such conic constraints, to the effect that the existence of the supermartingale numeraire is equivalent to market viability. Further, and always under the assumption of viability, we establish some additional optimality properties of the supermartingale numeraire. In the end of Chapter 2, we pose and solve a problem of robust maximization of asymptotic growth, under some realistic assumptions. In Chapter 3, we state and prove the Optional Decomposition Theorem under conic constraints. Using this version of the Optional Decomposition Theorem, we deal with the problem, of superhedging contingent claims. In Chapter 4, we consider yet another portfolio optimization problem. Under simultaneous conic constraints on portfolio choice, and drawdown constraints on their generated wealth, we try to maximize the long-term growth rate from investment. Application of the Azema-Yor transform allows us to show that the optimal portfolio for this optimization problem is a simple path transformation of a supermartingale numeraire portfolio. Some asymptotic properties of this portfolio are also discussed in Chapter 4.

El presente trabajo es una propuesta de implementación de mejora al proceso de Gestión de Portafolio de TI en una entidad del Sector Público. Se trata de un conjunto de mejoras orientadas a hacer del portafolio de TI una herramienta útil para orientar, planificar y evaluar las iniciativas del negocio que por su naturaleza, requieren o hacen uso intensivo de recursos tecnológicos; a fin de asegurar su contribución al cumplimiento de los objetivos institucionales. El documento se divide en cuatro capítulos. En el primer capítulo se describe el marco teórico consultado para justificar y desarrollar una propuesta fundada en definiciones y lineamientos conceptuales que permiten asegurar su fiabilidad. También se incluyen aspectos sobre el desarrollo de esfuerzos similares en instituciones públicas y una breve revisión general sobre la entidad. En el segundo capítulo se describe el foco de atención de la problemática y qué argumentos justifican el desarrollo de la propuesta. En el tercer capítulo se desarrolla la propuesta de solución a dos niveles: en un primer nivel se formulan los lineamientos para la implementación y en un segundo se describe el modelo de gestión y la caracterización de procesos, finalizando con la realización de su aplicación práctica al inventario de componentes incluidos en el preliminar de Plan Operativo Tecnológico, tomando en cuenta que actualmente se está trabajando con el inventario de componentes del próximo año. En el cuarto capítulo se incluyen conclusiones y recomendaciones de la propuesta, útiles para las siguientes etapas de implementación. / The present project is a proposal of implementation of improvement to the process of IT Portfolio Management in an entity of the Public Sector. It is a set of improvements aimed at making the IT portfolio a useful tool to guide, plan and evaluate business initiatives that, by their nature, require or make intensive use of technological resources; in order to ensure its contribution to the fulfillment of the institutional objectives. The document is divided into four chapters. The first chapter describes the theoretical framework consulted to justify and develop a proposal based on definitions and conceptual guidelines that ensure its reliability. Aspects about the development of similar efforts in public institutions and a brief general review of the entity are also included. The second chapter describes the focus of the problem and what arguments justify the development of the proposal. In the third chapter the proposal for a two-level solution is developed: in a first level the guidelines for the implementation are formulated and in a second one the management model and the characterization of processes are described, ending with the realization of its practical application to the inventory of components included in the preliminary IT Operational Plan, considering that the component inventory of next year is currently being worked on. The fourth chapter includes conclusions and recommendations of the proposal, useful for the following stages of implementation. / Trabajo de investigación