>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.

Este estudo considera o problema de controle ótimo multi-período de média-variância para sistemas em tempo discreto com saltos markovianos e ruídos multiplicativos. Inicialmente considera-se um critério de desempenho formado por uma combinação linear da variância nal e valor esperado da saída do sistema. É apresentada uma solução analítica na obtenção da estratégia ótima para este problema. Em seguida são considerados os casos onde os critérios de desempenho são minimizar a variância nal sujeito a uma restrição no valor esperado ou maximizar o valor esperado nal sujeito a uma restrição na variância nal da saída do sistema. As estratégias ótimas de controle são obtidas de um conjunto de equações de diferenças acopladas de Riccati. Os resultados obtidos neste estudo generalizam resultados anteriores da literatura para o problema de controle ótimo com saldos markovianos e ruídos multiplicativos, apresentando condições explícitas e sucientes para a otimalidade da estratégia de controle. São apresentados modelos e simulações numéricas em otimização de carteiras de investimento e estratégias de gestão de ALM (asset liabilities management). / This thesis focuses on the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noise under three kinds of performance criterions related to the nal value of the expectation and variance of the output. In the first problem it is desired to minimize the nal variance of the output subject to a restriction on its nal expectation, in the second one it is desired to maximize the nal expectation of the output subject to a restriction on its nal variance, and in the third one it is considered a performance criterion composed by a linear combination of the nal variance and expectation of the output of the system. The optimal control strategies are obtained from a set of interconnected Riccati dierence equations and explicit sufficient conditions are presented for the existence of an optimal control strategy for these problems, generalizing previous results in the literature. Numerical simulations of investment portfolios and asset liabilities management models for pension funds with regime switching are presented.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2016-09-02T14:39:05Z No. of bitstreams: 1 gabrielfiliperodriguesvasconcelos.pdf: 1140696 bytes, checksum: e6bf5056f506b71583057bdeb7231773 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2016-09-06T14:17:29Z (GMT) No. of bitstreams: 1 gabrielfiliperodriguesvasconcelos.pdf: 1140696 bytes, checksum: e6bf5056f506b71583057bdeb7231773 (MD5) / Made available in DSpace on 2016-09-06T14:17:29Z (GMT). No. of bitstreams: 1 gabrielfiliperodriguesvasconcelos.pdf: 1140696 bytes, checksum: e6bf5056f506b71583057bdeb7231773 (MD5) Previous issue date: 2013-11-25 / CAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Esta dissertação propõe uma nova versão para o CAPM, denominada Ômega CAPM. Este novo modelo trabalha com uma condição suficiente mais simples do que a eficiência do mercado em termos de média e variância. Consequentemente, restrições na utilidade e nas distribuições de retornos não são necessárias, podendo os ativos ter distribuições diferentes entre si. Além disso, todos os momentos das distribuições de retornos são considerados de forma indireta, ou seja, não precisam ser calculados e observados pelos investidores. O OCAPM mantem a forma simples de um único fator do CAPM, bem como seu rigor teórico. Empiricamente o OCAPM mostrou-se superior ao CAPM, não sendo rejeitado em um número maior de vezes, além de obter coeficientes mais coerentes com a teoria. Além disso, foi mostrado que o OCAPM adiciona novas informações sobre os retornos esperados não consideradas pelo CAPM. Entretanto, este trabalho não rejeita nenhum dos dois modelos, ele apenas aponta a superioridade do OCAPM. / This dissertation proposes a new version for the well-known CAPM, the Omega CAPM. This new model has a simpler sufficient condition than the mean-variance efficiency required on the CAPM. Thus, restriction regarding utility functions and returns distributions are not required. Besides that, our model allows assets to have different distribution amongst themselves. The OCAPM considers all superior moments indirectly, i.e. they do not have to be calculated or observed by investors and it maintains the single factor simplicity and the theoretical rigor of the original model. On an empirical point of view, the OCAPM was superior to the CAPM, the model obtained coefficients which ware more consistent with the theory. Moreover, we showed that the OCAPM adds information of the expected returns that are not considered by the CAPM. Nevertheless, we do not reject any of the models, we just show that the OCAPM is superior.

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.

Many important tasks in finance often rely on complex and time-consuming computations. The rapid development of quantum technology has raised the question of whether quantum computing can be used to solve these tasks more efficiently than classical computing. This thesis studies the potential use of quantum computing in finance by solving differently-sized problem instances of the mean-variance portfolio selection model using commercially available quantum resources. The experiments employ gate-based quantum computers and quantum annealing, the two main technologies for realizing a quantum computer. To solve the mean-variance optimization problem on gate-based quantum computers, the model was formulated as a quadratic unconstrained binary optimization (QUBO) problem, which was then used as input to quantum resources available on the largest quantum computing as a service (QCaaS) platforms, IBM Quantum Lab, Microsoft Azure Quantum and Amazon Braket. To solve the problem using quantum annealing, a hybrid quantum-classical solver available on the service D-Wave Leap was employed, which takes as input the mean-variance model’s constrained quadratic form. The problem instances were also solved classically on the model’s QUBO form, where the results acted as benchmarks for the performances of the quantum resources. The results were evaluated based on three performance metrics: time-to-solve, solution quality, and cost-to-solve. The findings indicate that gate-based quantum computers are not yet mature enough to consistently find optimal solutions, with the computation times being long and costly as well. Moreover, the use of gate-based quantum computers was not trouble-free, with the majority of quantum computers failing to even complete the jobs. Quantum annealing, on the other hand, demonstrated greater maturity, with the hybrid solver being capable of fast and accurate optimization, even for very large problem instances. The results from using the hybrid solver justify further research into quantum annealing, to better understand the capabilities and limitations of the technology. The results also indicate that quantum annealing has reached a level of maturity where it has the potential to make a significant impact on financial institutions, creating value that cannot be obtained by using classical computing.

貨幣需求理論中，長期利率與短期利率常被用來作為貨幣持有之機會成本的變數。然 究竟那一種利率較為適用？在學理上，這個問題帶來很多爭論。近幾年來，一些經濟 學家主張貨幣需求函數只考慮長期利率或考慮短期利率均不恰當，貨幣需求函數應該 針對整個利率結構考慮。這種貨幣需求─利率結構理論，在文獻上又有兩種分析方式 ：一種為：INVENTORY APPROACH，另一種為MEAN- VARIANCE APPROACH 。 本文第一章探討貨幣持有與機會成本間的關係。第二、三章分別就上述兩種APPROACH 作一探討；並就台灣資料作實證分析。篛四章討論採用多利率變數時在計量上所遭遇 的問題及其解決方式。第五章為結語。

Este estudo considera o modelo de controle ótimo estocástico sob um critério de média-variância para sistemas lineares a tempo discreto sujeitos a saltos Markovianos e ruídos multiplicativos sob dois critérios. Inicialmente, consideramos como critério de desempenho a minimização multiperíodo de uma combinação entre a média e a variância da saída do sistema sem restrições. Em seguida, consideramos o critério de minimização multiperíodo da variância da saída do sistema ao longo do tempo com restrições sobre o valor esperado mínimo. Condições necessárias e suficientes explícitas para a existência de um controle ótimo são determinadas generalizando resultados anteriores existentes na literatura. O controle ótimo é escrito como uma realimentação de estado adicionado de um termo constante. Esta solução é obtida através de um conjunto de equações generalizadas a diferenças de Riccati interconectadas com um conjunto de equações lineares recursivas. Como aplicação, apresentamos alguns exemplos numéricos práticos para um problema de seleção de portfólio multiperíodo com mudança de regime, incluindo uma estratégia de ALM (Asset and Liability Management). Neste problema, deseja-se obter a melhor alocação de portfólio de forma a otimizar seu desempenho entre risco e retorno em cada passo de tempo até o nal do horizonte de investimento e sob um dos dois critérios citados acima. / In this work we consider the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noise under two criterions. First, we consider an unconstrained multiperiod mean-variance trade-off performance criterion. In the sequence, we consider a multiperiod minimum variance criterion subject to constraints on the minimum expected output along the time. We present explicit necessary and sufficient conditions for the existence of an optimal control strategy for the problems, generalizing previous results in the literature. The optimal control law is written as a state feedback added with a deterministic sequence. This solution is derived from a set of coupled generalized Riccati difference equations interconnected with a set of coupled linear recursive equations. As an application, we present some practical numerical examples on a multiperiod portfolio selection problem with regime switching, including an Asset and Liability Management strategy. In this problem it is desired to nd the best portfolio allocation in order to optimize its risk-return performance in every time step along the investment horizon, under one of the two criterions stated above.In this work we consider the stochastic optimal control problem of discrete-time linear systems subject to Markov jumps and multiplicative noise under two criterions. First, we consider an unconstrained multiperiod mean-variance trade-off performance criterion. In the sequence, we consider a multiperiod minimum variance criterion subject to constraints on the minimum expected output along the time. We present explicit necessary and sufficient conditions for the existence of an optimal control strategy for the problems, generalizing previous results in the literature. The optimal control law is written as a state feedback added with a deterministic sequence. This solution is derived from a set of coupled generalized Riccati difference equations interconnected with a set of coupled linear recursive equations. As an application, we present some practical numerical examples on a multiperiod portfolio selection problem with regime switching, including an Asset and Liability Management strategy. In this problem it is desired to nd the best portfolio allocation in order to optimize its risk-return performance in every time step along the investment horizon, under one of the two criterions stated above.

Com a crescente desregulamentação dos mercados de energia, os diferentes participantes dos mercados se deparam com a necessidade de gerenciar de maneira eficiente seus investimentos em energia elétrica. Nesse cenário, a otimização das Carteiras de Contratos mostra-se uma técnica interessante no planejamento estratégico dos agentes de mercados de energia. Os mercados estão frequentemente expostos a riscos de diversas fontes, assim, a mitigação dos mesmos é fundamental. A Teoria do Portfólio, proposta por Harry Markowitz, tem sido utilizada em análises envolvendo diversos mercados. Este trabalho analisa um problema de Gestão de Carteiras de Contratos de energia elétrica, com Gestão de Risco. A relação contratual entre a ANDE (Administración Nacional de Electricidad Paraguai) e Itaipu Binacional é utilizada como estudo de caso. A metodologia proposta para tratar o problema extende a teoria de Markowitz em um contexto de tomada de decisão multiobjetivo, no qual se busca minimizar os gastos da ANDE em contratação de energia (via programação não-linear) e também o risco do portfólio, avaliado por meio da variância do mesmo. Por meio do modelo proposto é possível obter a decisão contratual ótima de ANDE, que minimiza o custo de seu portfólio para cada nível de risco. Os resultados obtidos indicam que o modelo é eficiente em termos de redução de custos e risco. / Due to the increasing deregulation of electricity markets, different market participants were faced with the necessity to effectively manage their investment in electricity. In this scenario, portfolio optimization is a relevant technique that can be investigated for strategic planning by agents on energy markets. In general, markets are exposed to risks from multiple sources, the mitigation of such risks, thus, is important. The portfolio theory proposed by Harry Markowitz has been used in analyses involving several markets. This work analyzes the problem of electricity Portfolio Management, with Risk Management. The contractual relationship between ANDE and Itaipu Binacional is used as a study case. The methodology proposed for addressing the problem extends Markowitz´s theory (applying non-linear programming) for a context of multi-objective decision making, searching for the minimization of ANDEs power contract costs, as well the portfolio risk, evaluated by its variance. With the proposed model, it is possible to obtain the optimal contract decision, which minimizes the portfolio cost for each risk level. Results indicate that the model proposed is efficient in cost and risk minimization.

Com a crescente desregulamentação dos mercados de energia, os diferentes participantes dos mercados se deparam com a necessidade de gerenciar de maneira eficiente seus investimentos em energia elétrica. Nesse cenário, a otimização das Carteiras de Contratos mostra-se uma técnica interessante no planejamento estratégico dos agentes de mercados de energia. Os mercados estão frequentemente expostos a riscos de diversas fontes, assim, a mitigação dos mesmos é fundamental. A Teoria do Portfólio, proposta por Harry Markowitz, tem sido utilizada em análises envolvendo diversos mercados. Este trabalho analisa um problema de Gestão de Carteiras de Contratos de energia elétrica, com Gestão de Risco. A relação contratual entre a ANDE (Administración Nacional de Electricidad Paraguai) e Itaipu Binacional é utilizada como estudo de caso. A metodologia proposta para tratar o problema extende a teoria de Markowitz em um contexto de tomada de decisão multiobjetivo, no qual se busca minimizar os gastos da ANDE em contratação de energia (via programação não-linear) e também o risco do portfólio, avaliado por meio da variância do mesmo. Por meio do modelo proposto é possível obter a decisão contratual ótima de ANDE, que minimiza o custo de seu portfólio para cada nível de risco. Os resultados obtidos indicam que o modelo é eficiente em termos de redução de custos e risco. / Due to the increasing deregulation of electricity markets, different market participants were faced with the necessity to effectively manage their investment in electricity. In this scenario, portfolio optimization is a relevant technique that can be investigated for strategic planning by agents on energy markets. In general, markets are exposed to risks from multiple sources, the mitigation of such risks, thus, is important. The portfolio theory proposed by Harry Markowitz has been used in analyses involving several markets. This work analyzes the problem of electricity Portfolio Management, with Risk Management. The contractual relationship between ANDE and Itaipu Binacional is used as a study case. The methodology proposed for addressing the problem extends Markowitz´s theory (applying non-linear programming) for a context of multi-objective decision making, searching for the minimization of ANDEs power contract costs, as well the portfolio risk, evaluated by its variance. With the proposed model, it is possible to obtain the optimal contract decision, which minimizes the portfolio cost for each risk level. Results indicate that the model proposed is efficient in cost and risk minimization.

Derivative pricing, and in particular the pricing of options, is an important area of current research in financial mathematics. Experts debate on the best method of pricing and the most appropriate model of a price process to use. In this thesis, a ``Switching Black-Scholes'' model of a price process is proposed. This model is based on the standard geometric Brownian motion (or Black-Scholes) model of a price process. However, the drift and volatility parameters are permitted to vary between a finite number of possible values at known times, according to the state of a hidden Markov chain. This type of model has been found to replicate the Black-Scholes implied volatility smiles observed in the market, and produce option prices which are closer to market values than those obtained from the traditional Black-Scholes formula. As the Markov chain incorporates a second source of uncertainty into the Black-Scholes model, the Switching Black-Scholes market is incomplete, and no unique option pricing methodology exists. In this thesis, we apply the methods of mean-variance hedging, Esscher transforms and minimum entropy in order to price options on assets which evolve according to the Switching Black-Scholes model. C programs to compute these prices are given, and some particular numerical examples are examined. Finally, filtering techniques and reference probability methods are applied to find estimates of the model parameters and state of the hidden Markov chain. / Thesis (Ph.D.)--Applied Mathematics, 2003.