<p>Even though today´s world unwinds on the increasing way of the globalisation, investors are aware of the possibilities the international markets offer and distance is not an issue any more, they are still governed by the “home bias factor“. This phenomenon implies that investors tend to prefer investing in domestic securities rather than entering the global market. Swedish investors are not the exception and the issue of the attraction of foreign fixed income securities is highlighted even more when we have found out there is lack of academic research about the topic from the perspective of Swedish investors. To narrow down the research subject and provide a reader with an interesting approach, we decided to examine the attraction of foreign government bonds from the perspective of Swedish investors.</p><p>At the beginning of the paper we raised three research questions and defined the objective of the paper in questioning the existence of reasons to invest in foreign government bonds. Another research question was defined as identifying our local investor, who is entering the global market and last, but not least, what investing strategy do we recommend him to follow.</p><p>Along the paper we proposed to apply a decent level of informative as well as a scientific approach to provide a reader with a valuable study concerning pre-defined topic. To reach more concrete outcomes of the study we have accepted couple of assumtions which we have identified ourselves with and we have stressed them especially during the theoretical part of the paper.</p><p>After conducting the comprehensive analysis of the Swedish market for government bonds we have identified a huge gap between the demand and supply for such bonds and based on the discussion concerning the opportunities and risks connected with such investments we have defined our investor. Under given assumptions, as the most probable case of occurance we consider a rational investor, who is offsetting the balance of interest rate sensitive assets and liabilities simultaneously looking for the best possible yield, the lowest possible risk and sound level of diversification.</p><p>During the empirical analysis, namely examination of the national yield curves we set first, however very limited investment strategy. After the incorporation of the portfolio theory, currency rate risk and the existence of instruments covering the foreign currency exposure we have come into a conclusion that our investor does not have to necessarily prefer a security from the depicted efficient frontier, but he can employ other securities as well. As a consequence, when using 100% hedging he can use whichever security on the global market.</p><p>At the conclusion, stated findings imply another investigation, since our research was based on very strong assumptions presented during the study. Thus it by far does not provide the reader with a comprehensive investment analysis, which some readers might be interested in. However, even from the beginning we claimed that we do not have such an ambitious goal.</p>

Even though today´s world unwinds on the increasing way of the globalisation, investors are aware of the possibilities the international markets offer and distance is not an issue any more, they are still governed by the “home bias factor“. This phenomenon implies that investors tend to prefer investing in domestic securities rather than entering the global market. Swedish investors are not the exception and the issue of the attraction of foreign fixed income securities is highlighted even more when we have found out there is lack of academic research about the topic from the perspective of Swedish investors. To narrow down the research subject and provide a reader with an interesting approach, we decided to examine the attraction of foreign government bonds from the perspective of Swedish investors. At the beginning of the paper we raised three research questions and defined the objective of the paper in questioning the existence of reasons to invest in foreign government bonds. Another research question was defined as identifying our local investor, who is entering the global market and last, but not least, what investing strategy do we recommend him to follow. Along the paper we proposed to apply a decent level of informative as well as a scientific approach to provide a reader with a valuable study concerning pre-defined topic. To reach more concrete outcomes of the study we have accepted couple of assumtions which we have identified ourselves with and we have stressed them especially during the theoretical part of the paper. After conducting the comprehensive analysis of the Swedish market for government bonds we have identified a huge gap between the demand and supply for such bonds and based on the discussion concerning the opportunities and risks connected with such investments we have defined our investor. Under given assumptions, as the most probable case of occurance we consider a rational investor, who is offsetting the balance of interest rate sensitive assets and liabilities simultaneously looking for the best possible yield, the lowest possible risk and sound level of diversification. During the empirical analysis, namely examination of the national yield curves we set first, however very limited investment strategy. After the incorporation of the portfolio theory, currency rate risk and the existence of instruments covering the foreign currency exposure we have come into a conclusion that our investor does not have to necessarily prefer a security from the depicted efficient frontier, but he can employ other securities as well. As a consequence, when using 100% hedging he can use whichever security on the global market. At the conclusion, stated findings imply another investigation, since our research was based on very strong assumptions presented during the study. Thus it by far does not provide the reader with a comprehensive investment analysis, which some readers might be interested in. However, even from the beginning we claimed that we do not have such an ambitious goal.

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Within the scope of this thesis, the Black-Litterman Asset Allocation Model (as presented in He &amp; Litterman, 1999) is compared to the classical mean-variance framework by simulating past performance of portfolios constructed by both models using identical input data. A quantitative investment strategy which favours stocks with high dividend yield rates is used to generate private views about the expected excess returns for a fraction of the stocks included in the sample. By comparing the ex-post risk-return characteristics of the portfolios and performing ample sensitivity analysis with respect to the numerical values assigned to the input variables, we evaluate the two models’ suitability for different categories of portfolio managers. As a neutral benchmark towards which both portfolios can be measured, a third market-capitalization-weighted portfolio is constructed from the same investment universe. The empirical data used for the purpose of our simulations consists of total return indices for 23 of the 30 stocks included in the OMXS30 index as of the 21st of February 2014 and stretches between January of 2003 and December of 2013.   The results of our simulations show that the Black-Litterman portfolio has delivered risk-adjusted return which is superior not only to that of its market-capitalization-weighted counterpart but also to that of the classical mean-variance portfolio. This result holds true for four out of five simulated strengths of the investment strategy under the assumption of zero transaction costs, a rebalancing frequency of 20 trading days, an estimated risk aversion parameter of 2.5 and a five per cent uncertainty associated with the CAPM prior. Sensitivity analysis performed by examining how the results are affected by variations in these input variables has also shown notable differences in the sensitivity of the results obtained from the two models. While the performance of the Black-Litterman portfolio does undergo material changes as the inputs are varied, these changes are nowhere near as profound as those exhibited by the classical mean-variance portfolio.   In the light of our empirical results, we also conclude that there are mainly two aspects which the portfolio manager ought to consider before committing to one model rather than the other. Firstly, the nature behind the views generated by the investment strategy needs to be taken into account. For the implementation of views which are of an α-driven character, the dynamics of the Black-Litterman model may not be as appropriate as for views which are believed to also influence the expected return on other securities. Secondly, the soundness of using market-capitalization weights as a benchmark towards which the final solution will gravitate needs to be assessed. Managers who strive to achieve performance which is fundamentally uncorrelated to that of the market index may want to either reconsider the benchmark weights or opt for an alternative model.

In this thesis modelling and solution methods for portfolio optimisation are presented. The investigations reported in this thesis extend the Markowitz mean-variance model to the domain of quadratic mixed integer programming (QMIP) models which are 'NP-hard' discrete optimisation problems. In addition to the modelling extensions a number of challenging aspects of solution algorithms are considered. The relative performances of sparse simplex (SSX) as well as the interior point method (IPM) are studied in detail. In particular, the roles of 'warmstart' and dual simplex are highlighted as applied to the construction of the efficient frontier which requires processing a family of problems; that is, the portfolio planning model stated in a parametric form. The method of solving QMIP models using the branch and bound algorithm is first developed; this is followed up by heuristics which improve the performance of the (discrete) solution algorithm. Some properties of the efficient frontier with discrete constraints are considered and a method of computing the discrete efficient frontier (DEF) efficiently is proposed. The computational investigation considers the efficiency and effectiveness in respect of the scale up properties of the proposed algorithm. The extensions of the real world models and the proposed solution algorithms make contribution as new knowledge.

>Magister Scientiae - MSc / Bank asset management mainly involves profit maximization through invest- ment in loans giving high returns on loans, investment in securities for reducing risk and providing liquidity needs. In particular, commercial banks grant loans to creditors who pay high interest rates and are not likely to default on their loans. Furthermore, the banks purchase securities with high returns and low risk. In addition, the banks attempt to lower risk by diversifying their asset portfolio. The main categories of assets held by banks are loans, treasuries (bonds issued by the national treasury), reserves and intangible assets. In this mini-thesis, we solve an optimal asset allocation problem in banking under the mean-variance frame work. The dynamics of the different assets are modelled as geometric Brownian motions, and our optimization problem is of the mean- variance type. We assume the Basel II regulations on banking supervision. In this contribution, the bank funds are invested into loans and treasuries with the main objective being to obtain an optimal return on the bank asset port- folio given a certain risk level. There are two main approaches to portfolio optimization, which are the so called martingale method and Hamilton Jacobi Bellman method. We shall follow the latter. As is common in portfolio op- timization problems, we obtain an explicit solution for the value function in the Hamilton Jacobi Bellman equation. Our approach to the portfolio prob- lem is similar to the presentation in the paper [Hojgaard, B., Vigna, E., 2007. Mean-variance portfolio selection and efficient frontier for defined contribution pension schemes. ISSN 1399-2503. On-line version ISSN 1601-7811]. We pro- vide much more detail and we make the application to banking. We illustrate our findings by way of numerical simulations.

abstract: Project portfolio selection (PPS) is a significant problem faced by most organizations. How to best select the many innovative ideas that a company has developed to deploy in a proper and sustained manner with a balanced allocation of its resources over multiple time periods is one of vital importance to a company's goals. This dissertation details the steps involved in deploying a more intuitive portfolio selection framework that facilitates bringing analysts and management to a consensus on ongoing company efforts and buy into final decisions. A binary integer programming selection model that constructs an efficient frontier allows the evaluation of portfolios on many different criteria and allows decision makers (DM) to bring their experience and insight to the table when making a decision is discussed. A binary fractional integer program provides additional choices by optimizing portfolios on cost-benefit ratios over multiple time periods is also presented. By combining this framework with an `elimination by aspects' model of decision making, DMs evaluate portfolios on various objectives and ensure the selection of a portfolio most in line with their goals. By presenting a modeling framework to easily model a large number of project inter-dependencies and an evolutionary algorithm that is intelligently guided in the search for attractive portfolios by a beam search heuristic, practitioners are given a ready recipe to solve big problem instances to generate attractive project portfolios for their organizations. Finally, this dissertation attempts to address the problem of risk and uncertainty in project portfolio selection. After exploring the selection of portfolios based on trade-offs between a primary benefit and a primary cost, the third important dimension of uncertainty of outcome and the risk a decision maker is willing to take on in their quest to select the best portfolio for their organization is examined. / Dissertation/Thesis / Doctoral Dissertation Industrial Engineering 2018

Orientadores: Antonio Carlos Moretti, Roberto Andreani / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica / Made available in DSpace on 2018-08-13T15:55:52Z (GMT). No. of bitstreams: 1 Silva_DanielTressida_M.pdf: 563016 bytes, checksum: 89e68063d06bd89084d7d6a15fdb7403 (MD5) Previous issue date: 2009 / Resumo: Nesta dissertação, estudamos algoritmos genéticos para resolver o problema de corte unidimensional multiobjetivo, onde minimizamos o desperdício dos objetos processados e o número de padrões distintos denominado custo de setup. Primeiro, realizamos uma codificação baseada em grupos desenvolvida por Falkenauer e, em seguida, aplicamos o algoritmo genético multiobjetivo SPEA2 para obter a Fronteira de Eficiente do problema. / Abstract: In this dissertation we studied genetic algorithms to solve the unidimensional multiobjective cutting stock problem, where we minimize the wastage of processed objects and the distinct number of patterns used, called setup cost. First, we make a group based codification derived by Falkenauer and, after that, we apply the multiobjective genetic algorithm SPEA2 to obtain problem's Efficient Frontier. / Mestrado / Otimização e Pesquisa Operacional / Mestre em Matemática Aplicada

This thesis presents two Models of portfolio optimization, namely the Markowitz Mean Variance Optimization Model and the Rockefeller and Uryasev CVaR Optimization Model. It then presents an application of these models to a portfolio of clean energy assets for optimal allocation of financial resources in terms of maximum returns and low risk. This is done by writing GAMS programs for these optimization problems. An in-depth analysis of the results is conducted, and we see that the difference between both models is not very significant even though these results are data-specific.

In this thesis we investigate the application of two heuristic methods, genetic algorithms and tabu/scatter search, to the optimisation of realistic portfolios. The model is based on the classical mean-variance approach, but enhanced with floor and ceiling constraints, cardinality constraints and nonlinear transaction costs which include a substantial illiquidity premium, and is then applied to a large I 00-stock portfolio. It is shown that genetic algorithms can optimise such portfolios effectively and within reasonable times, without extensive tailoring or fine-tuning of the algorithm. This approach is also flexible in not relying on any assumed or restrictive properties of the model and can easily cope with extensive modifications such as the addition of complex new constraints, discontinuous variables and changes in the objective function. The results indicate that that both floor and ceiling constraints have a substantial negative impact on portfolio performance and their necessity should be examined critically relative to their associated administration and monitoring costs. Another insight is that nonlinear transaction costs which are comparable in magnitude to forecast returns will tend to diversify portfolios; the effect of these costs on portfolio risk is, however, ambiguous, depending on the degree of diversification required for cost reduction. Generally, the number of assets in a portfolio invariably increases as a result of constraints, costs and their combination. The implementation of cardinality constraints is essential for finding the bestperforming portfolio. The ability of the heuristic method to deal with cardinality constraints is one of its most powerful features. / Decision Sciences / M. Sc. (Operations Research)