The first essay examines the problem of adverse selection when borrowers have private information about uncertain investment opportunities and are afforded the protection of limited liability. In particular, it considers how screening devices such as leverage ratios and interest rates can be used to assist in the transfer of information from borrowers to lenders. Both the supply and demand for credit is modelled. In a partial equilibrium setting, an increase in leverage ratios can enhance investment quality in a closed economy. If a country chooses to liberalise its capital account, an inflow of foreign capital can lead to a fall in GNP unless leverage ratios increase. In the second essay, the model is extended to include the risk of leverage into the investment decision. Again, multiple equilibria arise. In a close economy, the leverage ratio that maximises interest rates is higher than the leverage ratio that maximises output. In addition, the economy tends towards a Rothschild Stiglitz equilibrium that maximises nether interest rates nor output. This provides a justification for government intervention. In an open economy, the interests of government, savers and borrowers are aligned. However, liberalising the capital account does not ensure an increase in GNP. Opening the capital account gives the domestic economy access to foreign capital, but it loses control over the risk free interest rate. If capital flows are small, the costs of the latter may exceed the benefits of the former. In the third essay, empirical support for the theoretical insights of the first two essays is obtained. An hypotheses gleaned from the first two papers is that foreign capital should be less effectively allocated by the domestic banking sector, and consequently capital inflows should be associated with a fall in total factor productivity growth. Using a variety of methods, evidence is found to support this claim.

This doctoral dissertation consists of five essays related to two fields in financial economics which have been receiving a considerable interest from the academic community: stock market anomalies and option pricing. The first three essays deal with return seasonalities and systematic risk estimation. All three are empirical studies, and the data they use come from the equity markets of the Brussels Stock Exchange. The first essay is devoted to the study of the daily seasonalities in the rates of return. This reveals both a persistent lower return on Tuesday explained neither by various adjustments for the measurement errors nor by a relationship with other seasonal anomalies, and a seasonal pattern in the returns related to the settlement process of the forward market. The second essay examines some properties of market index returns and how their specification affects the security measure of systematic risk. It also demonstrates that the estimate of the systematic risk depends on both the choice of an index and the length of the differencing interval used to measure the returns. Finally, the third essay which tests adjustment procedures for this 'lq intervalling effect on the systematic risk reveals that the inferred asymptotic beta procedure is useful for a one day differencing interval and for a value weighted market index only. The last two essays are theoretical essays on the subject of option pricing. The first one presents simple models in both discrete and continuous time for valuing options on assets whose returns follow an additive process rather than a multiplicative process, as it is assumed, for example, in Cox, Ross and Rubinstein's model. As to the second essay, it demonstrates that a two-state option process can be the starting point of the derivation of any option pricing model. To derive an option pricing model, one needs to define the distribution function of the underlying asset price, and then to represent it with a binomial process with the same mean and variance.

This thesis examines various aspects of the modelling and prediction of Commercial Property Performance Indicators (CPPIs) with special reference to the modelling of office rents carried out by academics and practitioners. It considers the appropriate strategy for investment in commercial property, given that the efficiency of the market at reflecting available information into prices is largely unknown. It is argued and indeed accepted wisdom that it is, to some extent, inefficient and some investors appear consistently to 'beat the market'. Out of the uncertainty as to the efficiency of the market, CPPIs are modelled, predicted and forecast by academics and practitioners in an attempt to explain future price movements and thus provide knowledge which can be exploited to earn abnormal gains. Modelling and predicting commercial property markets (and so investment) is complicated by the nature of available CPPIs, being the results of valuations of properties rather than transactions. This means that CPPIs may not accurately reflect movements in the market but rather they may lag and underestimate actual changes - a phenomenon known as 'smoothing'. A model is presented which can be used to unsmooth CPPIs using a multiple regime approach and the characteristics of three office rent CPPIs are examined. Academics' and practitioners' 'consensus' models of office rent CPPIs are formed from a literature review and a survey, respectively. These models are compared in terms of their <I>ex post</I> predictive capability and it is found that generally, the better fitting models do not provide better predictions and in nearly 45% of cases choice of a model according to its fit will provide a worse model than a selection made at random. The academics' model generally predicts the Investment Property Databank (IPD) index better than the Jones Lang Wootton (JLW) and Investors' Chronicle Hillier Parker (HP) indices. It is generally the case that the one year ahead predictions are relatively poor.

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We derive a set of results of a statistical nature. We provide closed-form expressions to calculate the multivariate truncated moments of several distributions. The first major contribution of this research is a formula to calculate moments of an arbitrary order of the lower truncated multivariate standard normal (MVSN) distribution. This result is a generalisation of the previous research on truncated first- and second-order moments. The results on the MVSN are extended to the non-standard case for a lower truncated finite mixture of multivariate normal (FMVN) distributions. We derive the moments of the Student's t-distribution, and the lognormal (MVL) distribution. We also develop a toolbox software in MATLAB for the numerical calculations of these formulae. The applications of these results range from the financial area to general statistical theory. We derive a multi-asset option approximation for general stochastic processes, with a new methodology for valuing options of general continuous-time processes. We derive a general formula to value European options under general continuous-time processes, using an approximation of the risk-neutral density. This approximation is based on an extension to the multivariate case of the Jarrow and Rudd (1982) Univariate Generalised Edgeworth Expansion. Our expansion is called the Multivariate Generalised Edgeworth Expansion (MGEE). The general formula is an approximation using the calculated value of the options under a Wiener process, plus corrections of the value of the option based on the moments of second, third, and fourth order. Results show that a calibrated approximation provides a good fit when the differences between the moments of the risk-neutral density and the auxiliary density are small, and the uncalibrated approximation has immediate implications for risk management and hedging theory. Finally, Multivariate truncated closed-form moments are proposed to be used to price options. The set of options that can be priced with this new methodology includes new multivariate options, like multi-asset power, multi-strike forced rainbow and performance options. We use the multivariate riskneutral distribution and truncated moments theory of lognormal distributions for pricing, instead of the univariate distribution of the option contract. The results of the analytical approximations are provided.