A most common question in finance, particularly in investment perspective, is how an investor should allocate his wealth. Robert C. Merton (1975) remarks that the quest for an answer to the problem of lifetime consumption and portfolio selection under uncertainty is the beginning point for the development of a theory of Finance. This research looks into the possibility of forming effective/profitable portfolio asset allocation during economic downturns which occurred in the period between year 1993 and 2008. We employ out-of-sample forecasting techniques using time-varying factors of constants (alpha) and asset sensitivities (beta) over the market and covariance/correlation in asset allocation. In addition, we also investigate if economic indicators have had any effect on forming asset allocation, particularly the stock markets. It is found that out of 24 portfolio asset allocation strategies investigated; two strategies provide superior return over risk results. The research also reveals that the incorporation of economic indicators has improved our model significantly. This research contributes to the present literature through recommendations for achieving better portfolio's return forecasts. It is intended that the findings will strengthen the practicability of Markowitz's Mean Variance theory and Sharpe's and Lintner's Capital Asset Pricing Model. We have proven that both models are feasible with some innovative adjustments made to them.

This thesis is concerned with the modelling and algorithmic development of a Stopping Rule Problem (SRP) in the area of Portfolio Management. More specifically, the objective is to provide an exit strategy for an invested portfolio containing one or more assets. The exit strategy aims to protect gains in addition to limiting losses. The thesis focuses on the investment/disinvestment in the portfolio and is not concerned with the composition of the portfolio. A new Finite Horizon SRP, referred to as the Portfolio Management Problem (PMP), has been proposed that allows future scenarios to be considered in the optimisation of the exit time. The PMP aims at maximizing the expected reward of a Portfolio Manager (PM) through an optimal policy. A Dynamic Programming approach is proposed and the DP algorithm developed is capable of solving real-life problems for short- and long-term trades. The applicability of the PMP is limited to cases where no constraints have been imposed by the PM. In view of adding more realism into the model, a Stop Loss and Target Return has been encapsulated in the formulation of the PMP model and thus, in the optimisation of the exit time. The impact of the model with enhanced managerial capabilities, is a better control of the maximum drawdown which restricts the risk of investment, influencing positively metrics of performance. An efficient tradeoff between computational time and size of problem solved has been developed. The final part of this thesis focuses on a PMP which takes into consideration in a dynamic way the new market information for the determination of the optimal policy for assets exhibiting Mean-reversion (MR). This has been achieved through the insertion of a MR Rule specifically developed for the PMP which quantifies future tendencies of the asset prices based on its varying average. An algorithm dealing with the further additional memory requirements has been developed, capable of solving problems of size identical to the original PMP.

No description available.

No description available.

There are different theoretical approaches to the construction of a portfolio which offer maximum expected returns for a given level of risk tolerance and where the goal is to find the optimal investment rule. Each investor has a certain utility for money which is reflected by the choice of a utility function. In this work, two different types of risk averse utility functions (the power utility function and an exponential one) are studied in discrete time without making any assumptions about the underlying probability distribution of the returns of the asset prices. Each investor chooses, at the beginning of an investment period, the feasible portfolio allocation which maximises the expected value of the utility function for terminal wealth. Effects of both large and small proportional transaction costs on the choice of an optimal portfolio are taken into account. The transaction regions are approximated by using asymptotic methods, when the proportional transaction costs are small, and by using expansions about critical points for large transaction costs. At first the one-risky asset case is looked at then a multi-asset case is studied. A method for computing the distribution of the total wealth of the portfolio is then developed using a chosen distribution for the returns: the lognormal and then a distribution derived from the maximum entropy. The Value at Risk is then defined and used to constrain the portfolio optimisation problem with a different utility: the utility of consumption.

This thesis examines three different, but related problems in the broad area of portfolio management for long-term institutional investors, and focuses mainly on the case of pension funds. The first idea (Chapter 3) is the application of a novel numerical technique – robust optimization – to a real-world pension scheme (the Universities Superannuation Scheme, USS) for first time. The corresponding empirical results are supported by many robustness checks and several benchmarks such as the Bayes-Stein and Black-Litterman models that are also applied for first time in a pension ALM framework, the Sharpe and Tint model and the actual USS asset allocations. The second idea presented in Chapter 4 is the investigation of whether the selection of the portfolio construction strategy matters in the SRI industry, an issue of great importance for long term investors. This study applies a variety of optimal and naïve portfolio diversification techniques to the same SRI-screened universe, and gives some answers to the question of which portfolio strategies tend to create superior SRI portfolios. Finally, the third idea (Chapter 5) compares the performance of a real-world pension scheme (USS) before and after the recent major changes in the pension rules under different dynamic asset allocation strategies and the fixed-mix portfolio approach and quantifies the redistributive effects between various stakeholders. Although this study deals with a specific pension scheme, the methodology can be applied by other major pension schemes in countries such as the UK and USA that have changed their rules.

Purpose: The problem the allocator of financial capital has to deal with is that asset selection decisions need to be made today based on uncertain future expectations derived from accounting measurements and estimations produced in the past which are vulnerable to error and creative accounting. The research looks at how this problem has been dealt with in the academic and professional literature and develops a new tool leveraging both quantitative methods and the reflective practitioner’s experiential intuition. Methodology design: A qualitative methodology based on real-world case study (Flyvbjerg 2011) and microanalysis (Strauss and Corbin 1998) is used to develop customised reflexive research tools to assess management success in allocating capital, and audit metrics to illuminate techniques used to conceal poor returns. Findings: Returns which failed to reach market indices or inflation were observed in the UK investment trust sector over the past ten years suggesting their customers’ capital lost value in real terms. Although Modern Portfolio Theory has useful insights, strong form Efficient Market Hypothesis is rejected as is the over-reliance on mathematical models most of which have been developed under non-realistic assumptions. Monte Carlo simulation was examined and used alongside experiential intuition (Burke and Miller 1999, Dane and Pratt 2007) to generate insights into future risk management priorities and also as a way of optimising portfolio weighting options. The use of Monte Carlo for risk analysis, while not new in the financial services industry, is less common in industry, which in turn served to generate client work and publication of findings during the research. In carrying out the research, data inquiry limitations and in some cases data, design and formulaic errors were found in the publicly available research databases. Therefore a customised accounting database was designed with which to carry out the real-world case studies, which in turn exposed usage of modified accounting bases, creative accounting (Griffiths 1992) and concealment of earnings fluctuations in the statement of comprehensive income (Athanasakou et al 2011). Conclusions: A customised accounting research database (CARD) is developed to provide a basis for conducting structured quantitative analysis based on DuPont (Brealey et al 2006), Graham (1976) and my own experientially derived metrics. This quantitative analysis is further supported with experiential intuitive unstructured inquiries in such areas as the likelihood of future returns, debt structuring risks, management orientation and so forth. Monte Carlo is used for estimating probable future outcome distributions and in optimising portfolio weighting. To further reduce the risk of incorrect decisions, a capital allocation policy is developed drawing from both the literature review (mainly Hertz 1964, Modigliani and Miller 1958, Buffett 1977 – 2012, Stiglitz 2010) and my own experiences. At each step in the analysis the practitioner has the opportunity to reflect on the data gathered and to formulate questions needed to address the knowledge gaps arising. The findings expose the care needed when analysing corporate financial data due to the vulnerabilities of financial databases to error as well as the vulnerabilities of published financial data to earnings management (Nelson et al 2002). The tools developed in the project place particular emphasis on data integrity through the use of both existing and new analytical and triangulation formulae.

No description available.

This thesis provides two general equilibrium models to analyse the macroeconomic effect of risk on wealth-enhancing investment decisions. In chapter 1, we present an overlapping generations model in which aspirational agents face uncertainty about the returns to human capital. Investment in human capital requires external funding, implying a probability of bankruptcy that is greater the lower the human capital endowment of an agent. We show that agents with sufficiently low human capital endowments may experience such a strong influence of loss aversion that they abstain from human capital investment. We further show how this behaviour may be transmitted through successive generations to cause initial inequalities to persist. These results do not rely on any credit market imperfections. In chapter 2 we note that most working-age Americans obtain health insurance coverage through the workplace. U.S. law requires employers that offer health plans to use a price common to all in the group. However, the value of health insurance to risk-averse agents varies with their idiosyncratic health risk. Hence, linking employment and health insurance creates a wedge between the marginal cost and benefit of insurance. Since health risk can be sizable and health insurance is part of total employee compensation, the wedge can affect firm and employee decisions. We study the impact of this wedge on occupational choice, productivity and welfare in a general equilibrium model with agents who are endowed with idiosyncratic health risk and heterogeneous managerial ability. Agents choose whether to be a worker or an entrepreneur. We find that the wedge distorts occupational choice by causing two types of misallocations. Some highly skilled individuals with adverse health shocks leave entrepreneurship while individuals with intermediate skills but favourable health shocks opt to manage firms. Four policies are analysed: expansion of employer-based health insurance; private insurance; health insurance exchanges; and universal health coverage. Factor prices are determined endogenously and programs are financed by lump sum taxes. We assess the quantitative effects of the policies on firm size, productivity, GDP, and earnings. Welfare effects may be positive or negative, vary significantly with an individual's position in the asset and ability distributions, and are sensitive to changes in risk aversion.

The purpose of this thesis is to conduct a detailed study of optimism in financial decision making. I contribute to the literature by clarifying the relationship between financial optimism and individual investors’ portfolio choice. I also investigate whether optimism benefits an investor’s objective and subjective well-being within the same study by using large-scale survey data. I then explore how feedback, framing, and personality, contribute to financial optimism using controlled user experiments. Both survey-based and experimental approaches are applied in this thesis to study various aspects of optimism in a financial decision making domain. In this thesis I propose a theoretical framing work for measuring financial optimism and use these measures to analyse investor profiles. My survey-based studies show that optimistic investors prefer to invest in risky portfolios to risk-free portfolios, and borrow higher debt and larger mortgages. Optimists are significantly younger with lower accumulated financial wealth compared to non-optimists. Financial optimism is found to be beneficial in improving objective well-being by increasing future financial wealth, but this positive effect is very limited in terms of increasing future total wealth. Optimism is associated with current happiness and satisfaction which means optimism might help to improve current subjective well-being, but the long-term effect of optimism on happiness might be less desirable if the investor’s realised financial situation is lower than expected. By conducting experiments on subjects given investment tasks in a controlled environment, I find that positive feedback on previous portfolio returns decreases optimism when forecasts on future portfolio returns are made in absolute values, while positive feedback increases optimism when participants forecast in relative terms. I also show that framing influences financial optimism - optimism is higher when forecasting in absolute values than in percentages. I discovered that certain personality traits, such as extraversion and modesty, correlate with financial optimism. Optimism is also strongly positively associated with an attitude for risk tolerance. The overall implications of this thesis is that when making a financial decision, individual investors should not neglect the effect of optimism on their choice of portfolio. Optimism is beneficial towards both objective and subjective well-being, however such positive influence of optimism is fairly limited and should not be magnified. Optimism might not be subject to the control of an individual because optimism could derive from environmental factors, such as feedback and framing, as well as from internal factors to the investor, such as personality and innate risk attitude.