This thesis focuses on understanding the impact of different factors on affecting the tax rate in a democracy. The first model traces the influence of ideology on determining the tax rate in the presence of political competition. The main outcome is that when the salience of the ideology increases, the cohort of voters with the median ideological view become the swing voters and the equilibrium tax rate is then designed to benefit that cohort of voters. The second model focuses on the impact of inner group altruism on taxation. It establishes that, in a democracy, a minority elite, where altruism is present among its members, will be more influential and the equilibrium policy may reflect more the preferences of those elite. There are two main analytical results. First, the social group that exhibits higher inner altruism prefers a lower tax rate. Then the higher the inner altruism the rich exhibit, the lower is the tax rate they enjoy. Second, if both social groups increase their inner altruism by the same amount, then the equilibrium tax rate reduces. The third model makes precise the relationship between inequality of income and a social security tax rate. The model proposes a stationary overlapping- generations economy, in which all individuals currently alive vote every period on social security. There is ideology diversity. The main analytical result is that, in equilibrium, the generation that is less ideological benefits from lower inequality of income. We find that the less ideological generation enjoys a larger allocation of consumption and pushes the size of social security to be in its own favour.

A frequently asked questions in the hedge fund literature is 'What are the systematic risk factors in hedge fund returns?". Existing efforts can be classified as 'bottom-up' or 'top-down', i.e. analysing specific styles of funds or taking a portfolio approach, respectively. In my first essay, I take a 'bottom-up' approach and analyse convertible arbitrage (CA) returns. The magnitudes of their reported returns suggest that there are severe inefficiencies in the pricing of convertible bonds. Alternatively, CA excess returns may be compensation for exposure to extraordinary events, i.e. market crashes, and may be related to systematic risk in a nonlinear way. To overcome database biases, statistical issues, the dynamic use of leverage, etc., I replicate three core CA strategies and show that these adequately represent real investor experiences. Panel regressions show that the replicated strategies have risk exposures that can be related to their construction. To overcome the limitations of a linear framework, I show that once crash risk is hedged with options while maintaining the same ex-ante exposure to crashes, excess returns are statistically indistinguishable from zero. CA therefore partly or fully represents compensation for systematic risk. In the second essay we take a 'top-down' approach and analyse whether accounting for nonlinear relationships between hedge funds and the market in the construction of a portfolio is beneficial for a myopic investor. We expand the classic mean-variance framework and dynamically optimise a portfolio based on time varying moments. Nonlinear relationships enter by allowing for different correlations conditional on market movement. We show that an investor is indeed better off in terms of risk and return if he accounts for correlation asymmetries. His portfolio returns are less negatively skewed, less kurtosed and have a lower turnover. The driving factor appears to be that less capital is allocated to non-directional, arbitrage-style hedge funds.

This thesis addresses three optimisation problems. The first problem concerns static portfolio optimization. Empirical evidence suggests that asset dynamics can be characterised by a multifactor representation of asset returns. In this context, investors can capture the premium or hedge the risk associated with a particular factor through factor-mimicking portfolios. We examine different methods for constructing optimal factor-mimicking portfolios. We provide analytical considerations in the construction of factor-mimicking portfolios, along with empirical evidence. Also, we illustrate potential practical applications of factor-mimicking portfolios in the institutional investment process. The second problem addresses continuous time optimal consumption and investment for an agent investing in a complete arbitrage-free market consisting of several risky assets and a bank account. In particular, we consider a general model in which the agent's preferences exhibit a linear habit formation pattern that captures the effect of past consumption on current utility. Using duality methods, we establish the existence of an optimal consumption and investment strategy. We also prove that the optimal portfolio consumption pair can be expressed in terms of the solution to the Hamilton-Jacobi-Bellman equation that the problem's value function satisfies. The third problem concerns a general one-dimensional lro diffusion which must be maintained within an externally specified bounded interval by means of an impulse control process. We minimise a long-term average criterion that penalises deviations of the state process from a given nominal point within this region as well as the use of impulsive control effort. We solve the resulting optimisation problem and we provide an explicit optimal control strategy under general assumptions. The model that we study is motivated by several applications, including the problem of determining an optimal central bank intervention strategy aiming at the control of an exchange rate or an inflation rate, as well as the problem of designing optimal contribution policies in defined benefit pension plans.

The first two chapters of the thesis are a comparative study of several methods for correlation estimation from high-frequency data. These range from the well established Pearson correlation coefficient and Spearman's rho to the more recently proposed realised correlation and Fourier method estimators. Measuring correlation from high-frequency data is impeded by two main problems. One problem stems from the asynchronous and non-homogeneous nature of the time series and the other is caused by a market microstructure effect called the "Epps effect". The performance of each correlation method in dealing with both problems is first assessed with simulated data and then with real time series spanning 14 years of trades in S&P1 00 stocks. The correlation matrices thus obtained are analysed with the aid of Random Matrix Theory and network analysis tools such as Minimum Spanning Trees. In the third chapter, network analysis tools are applied to the Italian interbank payments system. The objective is to analyse the network topology of the system in order to ascertain the differences in the activities of banks of different sizes and the evolution of their connectivity structure over time. This helps in assessing the stability of the banking system and the efficiency of the interbank market. The fourth chapter introduces a new class of stochastic processes called Ito semi-diffusions as an alternative modelling framework for asset price dynamics. These models provide a better fit for the distributional properties of asset prices whilst maintaining analytical tractability. Numerous examples are given together with an illustration of a pricing method for the valuation of contingent claims. In the final chapter a stochastic control problem that arises in the context of commodity storage valuation is considered. The model's operational characteristics can be associated with different types of inventories such as hydro-electric reservoirs or gas storage facilities. Under suitable assumptions, it is shown that the optimal storage strategy depends only on the planning horizon and on the amount of stored commodity but not on the actual commodity price.

Infrastructure enhances economic competitiveness and represents an important source of economic empowerment and revenue. At a global level there is increasing demand for infrastructure and as the demand and supply gap widens, the financing of infrastructure is becoming increasingly more complex. The desire to remain competitive in the global market has seen governments increasingly seeking to expand the role of the private sector in the financing and delivery of quality infrastructure resources. This study focuses on investors' attraction to infrastructure investment and the evolving role of the private sector in delivering infrastructure, bringing into perspective key vehicles in the financing of infrastructure resources across regions, countries and sectors. The uniqueness of the study stems from the timely assessment of the impact of the global financial crisis on infrastructure transactions and performance comparing infrastructure investment returns with other asset classes across global, European and UK markets. The study employs a quantitative research approach drawing time series data from two distinctive databases in order to fully explore infrastructure investments from both transaction based activities within the industry and the comparative performance of the asset class. Capital flows and trends in infrastructure transactions across geographical locations and sectors are examined and time series data used in the analysis of infrastructure returns over a ten year period (2001-2010). This facilitated the analyses of a broad range of listed infrastructure investment return characteristics. The data obtained were employed in the construction of efficient portfolio frontiers computed with the aid of an optimization tool. The study highlights the debt driven nature of greenfield projects offering investors a more attractive route into the infrastructure market. The oil & gas, power, transport and social infrastructure sectors attracted the highest investor funds within the infrastructure investment space. The role of the private sector within the infrastructure industry is evolving, as reflected in the growing acceptance of the PPP model and in the flexibility of options available across geographical markets. The impact of the global financial crisis (GFC) on infrastructure delivery from the transaction and performance perspectives was characterized by declining capital flows, resulting in a dwindling credit profile for the infrastructure markets. The resilience of infrastructure as a unique asset class was demonstrated during the GFC period by the superior performance shown by European generation utilities and UK infrastructure. The study shows that infrastructure plays a significant role within a mixed asset portfolio by enhancing diversification benefits; a unique investment strategy sought by investors to enhance investment performance.

This thesis explores links between aggregate investment and asset prices. Many popular theories that link investment and asset prices - such as rational bubbles and Tobin's q - do a poor job of describing the empirical reality. Examples include asset price booms that, in hindsight, may be described as bubbles leading to higher investment, contradicting the predictions from rational bubble models. Another example is the very low sensitivity of investment to Tobin's q in almost all empirical applications and evidence suggesting that q is not a sufficient statistic for investment. One relatively undeveloped area ofthe investment is that which considers a role for information asymmetries and social learning. Chapter II develops a partial equilibrium model based on Caplin and Leahy (1994) in which firms make investment decisions regarding a risky project each period after learning new infonnation about likely returns. This information is from private sources and the asset market. The key results of this model are that: asset prices affect the length and amplitude ofthe investment cycle; a small number of noisy market signals may dominate a very large number of accurate firm signals, due to frict~onal costs faced by the fum; there exist feedback channels from investment back to asset prices; and informational asymmetries impose ex-ante welfare costs on the economy. Chapter III extends this model by describing in detail the process of asset price formation. Chapter IV empirically tests some hypotheses from these theoretical models using aggregate U.S. data and a V AR model. The key result is that q is not a sufficient statistic for aggregate investment; indeed, investment Granger causes some important components of q. This suggests that market prices are not infonnationally efficient; fums hoard information which is then released through their publicly observable actions.

While the debate on gains from International Portfolio Diversification (IPD) points to the attractiveness of emerging intemational financial markets to industrial markets investors primarily due to low correlations, no evidence exists on gains from IPD in the six Gulf Cooperation Council (GCC) financial markets. This PhD dissertation aims at understandmg the behaviour, dynamics, and the potential for gains from IPD in the GCC financial markets from a USA investor's perspective over low and high oil prices periods.

This thesis is an analysis of sovereign default using option pricing models. The first part of the thesis applies the structural credit risk models of Gapen, Gray, Lim and Xiao, (GGLX) and Karmann and Maltritz (KM) to 25 countries accounting for about 75% of global GDP. The GGLX model underestimates sovereign spread and hence the probability of default. This confirms one of the main criticisms of structural credit risk models when applied to corporate default. By contrast, the estimates produced by the KM are far too high; the estimated probability of default is almost one in some cases. The second part of the thesis estimates the default risk indicators using the GGLX model in conjunction a number of different assumptions about the value of sovereign assets. It also uses market values of sovereign spread, which thus becomes an input to the model rather than an output. These approaches have not been reported in the literature before. In addition, Ito's lemma is used derive the corresponding geometric Brownian motion for sovereign spread. Using the new approach, the implied probabilities of default are larger than those obtained using standard GGLX. The model also gives revised values for domestic currency liability and its volatility. These are larger than the values reported by national agencies, thus contributing to the explanation of why structural credit risk models underestimate real-world credit spreads and the risk of default. The outputs from the model also lead to the construction of balance sheet ratios, which contribute to information about the likelihood of sovereign default. Overall, the new model results in default rankings and associated measures which are significantly more realistic than those produced by the standard GGLX model.

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