This thesis represents the first comprehensive attempt at providing conceptual and scholarly coherence to the topic of stranded assets and the environment. Over the last five years the topic has risen up the agenda and has become of significant interest to scholars and practitioners alike, as it has influenced a number of pressing issues facing investors, companies, policymakers, regulators, and civil society in relation to global environmental change. The thesis reveals how the topic developed and emerged, notably through a unique first-person account based on autoethnography and close dialogue. Four self- contained papers demonstrate the wide applicability of stranded assets, and further existing, relatively well-developed literatures (namely carbon budgets and stranded costs) and also two much less developed literatures (namely the calibration of climate policy to minimise stranded assets and policy mechanisms to quickly and efficiently strand assets). Though a significant amount has been written on stranded assets over a short period, there remain significant gaps in the literature. The thesis identifies substantial research opportunities, particularly to better connect our understanding of physical and societal environment-related risks; to improve our knowledge of perception and behaviour in relation to the creation and management of stranded assets; to expand the scope of work into new sectors and geographies; and to place stranded assets in an appropriate historical perspective. Stranded assets is, if anything, a geographical concept. The thesis makes the case for economic geography as the disciplinary home for stranded assets. The sub-discipline can both contribute to the development of stranded assets as a scholarly endeavour and itself benefit from interacting with a topic that intersects with some of the most pressing contemporary issues related to environmental sustainability.

One of the classical problems in finance is that of an economic unit who aims at maximizing his expected life-time utility from consumption and/or terminal wealth by an effective asset-liability management. The purpose of this thesis is to determine the optimal investment strategies , from the point of view of their economic utility, for individual and institutional investors such pension funds.

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Aktyvų ir pasyvų valdymo (APV) klausimas aktualus dar nuo tada, kai susikūrė pirmieji bankai, kadangi tai iš pačios bankininkystės specifikos kylant problema. Spartėjantys globalizacijos procesai šią problemą dar labiau aštrina ir tai skatina bankus ieškoti efektyvesnių būdų jų aktyvų ir pasyvų portfelių valdymui. Šio magistrinio darbo tikslas yra išanalizuoti APV problemą komerciniame banke ir įvertinti APV efektyvumo vertinimą trijuose Lietuvos bankuose. Siekiant išanalizuoti APV problemą, pirmiausia buvo apžvelgtos įvairių autorių siūlomos APV koncepcijos, buvo pabrėžta APV svarba, žvelgiant tiek iš centrinio, tiek iš komercinio banko pozicijų, taip pat apžvelgta APV koncepcijos istorinė raida. Buvo išnagrinėti trys populiariausi APV modeliai: GAP analizė, trukmės analizė, VaR bei Monte Carlo metodikos. Tuomet buvo įvertintas APV efektyvumo vertinimas trijuose Lietuvos bankuose, palyginimui pasirenkant didelį, vidutinį ir mažą bankus. Siekiant įvertinti APV efektyvumo vertinimą pasirinktuose bankuose buvo atlikta GAP analizė, įvertintas privalomųjų centrinio banko normatyvų vykdymas ir apskaičiuoti pelningumo ir likvidumo rodikliai. Atlikta analizė parodė, jog yra akivaizdus ryšis tarp banko dydžio ir APV efektyvumo. Tendencijos tokios, jog mažesni bankai laiko didesnes likvidžių aktyvų atsargas, kadangi jie turi menkesnes skolinimosi galimybes, mažesni tokių bankų paskolų portfeliai, taigi jų efektyvumas transformuojant priimtus depozitus į paskolas yra mažesnis. Visi šie... [toliau žr. visą tekstą] / The problem of asset – liability management (ALM) has been topical since the origin of banking. The processes of globalization and internationalization in financial markets in the twenty first century made this problem sharper than ever before, that make banks search more efficient ways of management of their asset and liabilities portfolios. The aim of this master work is to analyse the problem of ALM in commercial bank and evaluate the performance ALM in three Lithuanian banks. In order to analyse ALM problem different scientists approaches to ALM were analysed in this research in order to define the ALM conception. Also the importance of ALM was underlined from the point of view both of central bank and commercial bank and the development of ALM was viewed. The most popular models of ALM were analysed – GAP analysis, Duration GAP, VaR and Monte Carlo. Then the effectiveness of performance of ALM was evaluated in three Lithuanian banks, choosing the big one, the medium one and the small one. In order to analyse the effectiveness of performance of ALM in the chosen banks the GAP analysis was made, the execution of central bank’s compulsory normative rates was evaluated and the rates of liquidity and profitability were counted and analysed. The analysis pointed out, that there is an obvious relation between the size of the bank and the way it’s ALM is performed. The tendencies are these: smaller banks keep bigger amounts of liquid assets, because that they have lower... [to full text]

The primary objective of this dissertation is to assess the impact of regulation on the asset management industry. The secondary aims of the study are to investigate whether the South African asset management industry regulation is aligned towards creating an enabling economic environment, analyse the regulatory regime affecting the asset management industry and provide recommendations regarding the strategies that may be adopted by asset managers, in order to effectively and efficiently comply with existing and new regulations. A quantitative research methodology was adopted. A survey was conducted by means of questionnaire design. The questionnaire was administered to a sample of asset management companies registered with the Financial Services Board. Through empirical research the researcher gained in-depth knowledge regarding the impact of regulation on the asset management industry. There is an appreciation of the economic importance of the asset management industry, as a creator of employment and its effect on the growth and development of the South African economy in general. The regulation of the asset management industry contributes towards an enabling economic environment and development of the industry. The rationale and objectives of regulation of the asset management industry, as it pertains to systematic issues associated with externalities, market imperfections and failures, economies of scale in monitoring, consumer confidence and the consumer demand for regulation, would seem to justify the existence and development of compliance requirements. Regulation must however balance the goals of competition and efficiency versus safety and soundness. The current regulatory universe applicable to the asset management industry is justifiable, beneficial and is achieving the intended objectives. The rapid changes in regulation and costs of regulation of the asset management industry, which entails utilisation of resources such as personnel, time and systems required and limitation on investment freedom and creativity, remain the cause for concern. However based on the outcomes of the research, there is adequate evidence to suggest that the benefits of regulation of the asset management industry outweigh the costs thereof. The outcomes of the research suggest that under the new paradigm, success will be determined by how asset managers can solve several key challenges such as enhancing operational efficiency, complying with the complex and rapidly changing regulatory environment and meeting the changing customer expectations. The new era of compliance will force asset managers to focus on an enterprise-wide integration of business strategy and not simply short-term tactical solutions. For asset managers that effectively meet the challenge of the changing regulatory environment, substantial investments in infrastructure or data architecture and implementation of an enhanced operating model will provide opportunities to enhance profitability and ensure growth. / Economics / M. Com.

A incerteza é um elemento fundamental da realidade. Então, torna-se natural a busca por métodos que nos permitam representar o desconhecido em termos matemáticos. Esses problemas originam uma grande classe de programas probabilísticos reconhecidos como modelos de programação estocástica. Eles são mais realísticos que os modelos determinísticos, e tem por objetivo incorporar a incerteza em suas definições. Essa tese aborda os problemas probabilísticos da classe de problemas de multi-estágio com incerteza e com restrições probabilísticas e com restrições probabilísticas conjuntas. Inicialmente, nós propomos um modelo de administração de ativos e passivos multi-estágio estocástico para a indústria de fundos de pensão brasileira. Nosso modelo é formalizado em conformidade com a leis e políticas brasileiras. A seguir, dada a relevância dos dados de entrada para esses modelos de otimização, tornamos nossa atenção às diferentes técnicas de amostragem. Elas compõem o processo de discretização desses modelos estocásticos Nós verificamos como as diferentes metodologias de amostragem impactam a solução final e a alocação do portfólio, destacando boas opções para modelos de administração de ativos e passivos. Finalmente, nós propomos um “framework” para a geração de árvores de cenário e otimização de modelos com incerteza multi-estágio. Baseados na tranformação de Knuth, nós geramos a árvore de cenários considerando a representação filho-esqueda, irmão-direita o que torna a simulação mais eficiente em termos de tempo e de número de cenários. Nós também formalizamos uma reformulação do modelo de administração de ativos e passivos baseada na abordagem extensiva implícita para o modelo de otimização. Essa técnica é projetada pela definição de um processo de filtragem com “bundles”; e codifciada com o auxílio de uma linguagem de modelagem algébrica. A eficiência dessa metodologia é testada em um modelo de administração de ativos e passivos com incerteza com restrições probabilísticas conjuntas. Nosso framework torna possível encontrar a solução ótima para árvores com um número razoável de cenários. / Uncertainty is a key element of reality. Thus, it becomes natural that the search for methods allows us to represent the unknown in mathematical terms. These problems originate a large class of probabilistic programs recognized as stochastic programming models. They are more realistic than deterministic ones, and their aim is to incorporate uncertainty into their definitions. This dissertation approaches the probabilistic problem class of multistage stochastic problems with chance constraints and joint-chance constraints. Initially, we propose a multistage stochastic asset liability management (ALM) model for a Brazilian pension fund industry. Our model is formalized in compliance with the Brazilian laws and policies. Next, given the relevance of the input parameters for these optimization models, we turn our attention to different sampling models, which compose the discretization process of these stochastic models. We check how these different sampling methodologies impact on the final solution and the portfolio allocation, outlining good options for ALM models. Finally, we propose a framework for the scenario-tree generation and optimization of multistage stochastic programming problems. Relying on the Knuth transform, we generate the scenario trees, taking advantage of the left-child, right-sibling representation, which makes the simulation more efficient in terms of time and the number of scenarios. We also formalize an ALM model reformulation based on implicit extensive form for the optimization model. This technique is designed by the definition of a filtration process with bundles, and coded with the support of an algebraic modeling language. The efficiency of this methodology is tested in a multistage stochastic ALM model with joint-chance constraints. Our framework makes it possible to reach the optimal solution for trees with a reasonable number of scenarios.

A incerteza é um elemento fundamental da realidade. Então, torna-se natural a busca por métodos que nos permitam representar o desconhecido em termos matemáticos. Esses problemas originam uma grande classe de programas probabilísticos reconhecidos como modelos de programação estocástica. Eles são mais realísticos que os modelos determinísticos, e tem por objetivo incorporar a incerteza em suas definições. Essa tese aborda os problemas probabilísticos da classe de problemas de multi-estágio com incerteza e com restrições probabilísticas e com restrições probabilísticas conjuntas. Inicialmente, nós propomos um modelo de administração de ativos e passivos multi-estágio estocástico para a indústria de fundos de pensão brasileira. Nosso modelo é formalizado em conformidade com a leis e políticas brasileiras. A seguir, dada a relevância dos dados de entrada para esses modelos de otimização, tornamos nossa atenção às diferentes técnicas de amostragem. Elas compõem o processo de discretização desses modelos estocásticos Nós verificamos como as diferentes metodologias de amostragem impactam a solução final e a alocação do portfólio, destacando boas opções para modelos de administração de ativos e passivos. Finalmente, nós propomos um “framework” para a geração de árvores de cenário e otimização de modelos com incerteza multi-estágio. Baseados na tranformação de Knuth, nós geramos a árvore de cenários considerando a representação filho-esqueda, irmão-direita o que torna a simulação mais eficiente em termos de tempo e de número de cenários. Nós também formalizamos uma reformulação do modelo de administração de ativos e passivos baseada na abordagem extensiva implícita para o modelo de otimização. Essa técnica é projetada pela definição de um processo de filtragem com “bundles”; e codifciada com o auxílio de uma linguagem de modelagem algébrica. A eficiência dessa metodologia é testada em um modelo de administração de ativos e passivos com incerteza com restrições probabilísticas conjuntas. Nosso framework torna possível encontrar a solução ótima para árvores com um número razoável de cenários. / Uncertainty is a key element of reality. Thus, it becomes natural that the search for methods allows us to represent the unknown in mathematical terms. These problems originate a large class of probabilistic programs recognized as stochastic programming models. They are more realistic than deterministic ones, and their aim is to incorporate uncertainty into their definitions. This dissertation approaches the probabilistic problem class of multistage stochastic problems with chance constraints and joint-chance constraints. Initially, we propose a multistage stochastic asset liability management (ALM) model for a Brazilian pension fund industry. Our model is formalized in compliance with the Brazilian laws and policies. Next, given the relevance of the input parameters for these optimization models, we turn our attention to different sampling models, which compose the discretization process of these stochastic models. We check how these different sampling methodologies impact on the final solution and the portfolio allocation, outlining good options for ALM models. Finally, we propose a framework for the scenario-tree generation and optimization of multistage stochastic programming problems. Relying on the Knuth transform, we generate the scenario trees, taking advantage of the left-child, right-sibling representation, which makes the simulation more efficient in terms of time and the number of scenarios. We also formalize an ALM model reformulation based on implicit extensive form for the optimization model. This technique is designed by the definition of a filtration process with bundles, and coded with the support of an algebraic modeling language. The efficiency of this methodology is tested in a multistage stochastic ALM model with joint-chance constraints. Our framework makes it possible to reach the optimal solution for trees with a reasonable number of scenarios.

In recent years, new regulations and stronger competition have further increased the importance of stochastic asset-liability management (ALM) models for life insurance firms. However, the often complex nature of life insurance contracts makes modeling to a challenging task, and insurance firms often struggle with models quickly becoming too complicated and inefficient. There is therefore an interest in investigating if, in fact, certain traits of financial ratios could be exposed through a more efficient model. In this thesis, a discrete time stochastic model framework, for the simulation of simplified balance sheets of life insurance products, is proposed. The model is based on a two-factor stochastic capital market model, supports the most important product characteristics, and incorporates a reserve-dependent bonus declaration. Furthermore, a first approach to endogenously model customer transitions is proposed, where realized policy returns are used for assigning transition probabilities. The model's sensitivity to different input parameters, and ability to capture the most important behaviour patterns, are demonstrated by the use of scenario and sensitivity analyses. Furthermore, based on the findings from these analyses, suggestions for improvements and further research are also presented. / Införandet av nya regelverk och ökad konkurrens har medfört att stokastiska ALM-modeller blivit allt viktigare för livförsäkringsbolag. Den ofta komplexa strukturen hos försäkringsprodukter försvårar dock modelleringen, vilket gör att många modeller anses vara för komplicerade samt ineffektiva, av försäkringsbolagen. Det finns därför ett intresse i att utreda om egenskaper hos viktiga finansiella nyckeltal kan studeras utifrån en mer effektiv och mindre komplicerad modell. I detta arbete föreslås ett ramverk för stokastisk modellering av en förenklad version av balansräkningen hos typiska livförsäkringsbolag. Modellen baseras på en stokastisk kapitalmarknadsmodell, med vilken såväl aktiepriser som räntenivåer simuleras. Vidare så stödjer modellen simulering av de mest väsentliga produktegenskaperna, samt modellerar kundåterbäring som en funktion av den kollektiva konsolideringsgraden. Modellens förmåga att fånga de viktigaste egenskaperna hos balansräkningens ingående komponenter undersöks med hjälp av scenario- och känslighetsanalyser. Ytterligare undersöks även huruvida modellen är känslig för förändringar i olika indata, där fokus främst tillägnas de parametrar som kräver mer avancerade skattningsmetoder.

This dissertation is a theoretical and empirical investigation of the actual changes in Federal S&L asset portfolios following the deregulation of the 1980's which loosened the restrictions on the amount of non-housing related lending that Federal S&L's could undertake. In particular the study focuses on the effects of deregulation and the forces promoting and constraining the individual S&L's expansion into non-housing related assets. The theoretical model provides a framework for the empirical examination of the deregulation in the DIDMCA of 1980 and Garn-St Germain Act of 1982. The theoretical model is an adaptation of the Mingo and Wolkowitz (1977) banking model. The peculiarities of the S&L industry are embodied through adaptations of the Mingo and Wolkowitz (1977) model which emphasize after-tax profit maximization (tax laws reward specialization in housing related assets), constrain diversification into non-housing related assets, and differentiate between mutual and stock associations. Using the method of Lagrange multipliers, an expression is obtained for the effect of a change in after-tax profits for a relaxation of the constraint on diversification which becomes the focus of the analysis. By integrating the Lagrange multiplier with economic and regulatory controls, systems of regressions are developed which examine the changes in asset portfolio composition for Federal associations using balance sheet and income statement data between 1979 and 1983. The findings and implications of the empirical analysis are summarized as follows: 1. The tax laws do not appear to have constrained the diversification. 2. Specialization effects with respect to housing related assets appear to have constrained the diversification into non-housing related assets. 3. Non-housing related assets and liquid assets appear to be substitutes. 4. Stock associations, on average, have expanded into non-housing related assets to a greater extent than mutual associations. 5. The changes in liability legislation appear to have restrained the diversification into non-housing related assets. 6. Large associations appear more able to acquire the expertise needed to diversify. 7. Profitability appears to be correlated with the expansion into "new products." / Ph. D.

Thesis (M.Com. (Finance))--University of the Witwatersrand, Faculty of Commerce, Law and Management, School of Economic and Business Sciences, 2017 / This dissertation investigates the inclusion of volatility into the asset allocation decision, first as an asset class, and second as a tool for dynamic equity allocation. An examination on whether volatility exposure as an asset class has the necessary characteristics to form part of the broader investment universe is conducted. This is accomplished by comparing the risk-return characteristics of three naked option-selling strategies, a bull put spread strategy and a VIX futures strategy with the S&P 500 Index. Each volatility strategy is also included as part of a 30/30/40 volatility/equity/bond portfolio and compared to a traditional 60/40 equity/bond portfolio. Historically, the results indicate that all individual volatility strategies generated superior Sharpe ratios and exhibited less severe drawdowns than the S&P 500 Index, particularly during the 2008 Global Financial Crisis. Additionally, all volatility blended portfolios experienced better tail-risk profiles than the 60/40 equity/bond portfolio, with the naked option-selling strategies also generating similar returns as the 60/40 portfolio both over the full sample period as well during the period of recovery following the 2008 Global Financial Crisis. The results suggest that the returns associated with option-selling strategies are consistent, and have resulted in strong long-run risk-adjusted performance, qualifying short volatility exposure attained through option-selling strategies as an asset class. It however remains unclear whether the VIX futures strategy qualifies as an asset class given that it aims to exploit a market anomaly in the form of potentially non-priced volatility clustering in the S&P 500 Index. While the strategy generated considerable outperformance from 2004 to 2009, it underperformed from 2009 to 2016 suggesting that much of the non-priced volatility clustering has since been traded away. Drawing on the evidence of volatility clustering in equity markets, a managed volatility trading rule that regulates portfolio exposure between cash and equity based on how high the prevailing volatility level was relative to historical volatility levels is developed. Although transaction costs were not accounted for, the results indicated that the managed volatility trading rule has historically generated considerably superior Sharpe ratios than equity in developed and developing markets. In conclusion, volatility exposure attained through option-selling strategies has proven to be an attractive asset class, and historical evidence suggests that its inclusion into a traditional 60/40 equity/bond portfolio is likely to reduce the risk of future risk-adjusted underperformance relative to what had been achieved in the past. Additionally, the managed volatility trading rule remains an attractive alternative to investors who are precluded from investing in volatility as an asset class. / GR2018