The main objective of this thesis is to identify the reasons why firms choose to issue unit IPOs instead of share-only IPOs. Evidence is found that unit firms are smaller, riskier, with higher level of agency costs and higher levels of information asymmetry than share-only firms and unit IPOs are underwritten by less reputable underwriters. The initial return results provide strong support to the Agency Cost hypothesis that unit IPOs is significantly more underpriced than share-only IPOs. Unit firms have lower survival rate than that of share-only IPO firms; however, unit firms that do survive are more likely to issue seasoned equity offerings (SEOs) for further funding. A clear pattern of price run-up is observed before SEO announcements by unit firms and a significant negative price adjustment is found when the SEOs are announced. In the long-term, this thesis provides evidence that unit IPOs present significantly worse underperformance comparing to both the matching share-only IPOs and various market indices. Such results contradict both the Agency Cost and the Signalling hypotheses and imply that unit firms cannot significantly improve performance by simply attaching warrants, regardless as whether they are used to reduce agency costs or to signal firm value.

Mergers and acquisitions (M&As) are important corporate strategy actions that are vital for the companies in order to survive in this competitive global world. The popularity of those actions has increased over the years, especially in the international domain. In the UK, both the number and value of cross-border M&As has increased significantly over the years. Despite this increase, there haven’t been enough studies or clear evidence about whether venturing abroad to acquire foreign targets leads the companies to better performance compared to staying domestically. Therefore, the purpose of this thesis is to investigate the M&A phenomenon deeply and compare between cross-border and domestic M&As made by UK public acquirer firms. More specifically, the thesis concentrates on three main issues which are: (1) the difference between the returns to shareholders of acquirer firms involved in cross-border and domestic M&As; (2) the difference between the operating performance of acquirer firms involved in cross-border and domestic M&As; and (3) the difference between the impacts of cross-border and domestic M&As on the operating performance of acquirer and target firms combined. Market-based and accounting-based approaches are used to investigate a sample of UK acquirer firms engaged in cross-border and domestic M&As both in the short-term and in the long-term periods. In general, the results reveal insignificant differences between the shareholders’ returns and operating performances of acquirer firms involved in cross-border and domestic M&As over the short- and long-term periods. On the other hand, the results for acquirer and target combined firms show that cross-border M&As have lower operating performances than domestic M&As. Recommendations are provided in order to help the decision and policy makers in the companies to decide whether cross-border M&As should be actively encouraged or discouraged in comparison with domestic M&As.

This dissertation consists of a set of four sole-authored, reviewed and published papers which develop the theme that company accounting policies, particularly those relating to asset valuation, depreciation and dividend policy, developed in response to a change in the general perception of the nature of the property rights of the original owners. The original owners of commercial and industrial concerns in the early nineteenth century were the partners. After incorporation they and others became the shareholders of the company. The origin of commercial and industrial companies as partnerships influenced the British government and legal thinking for nearly a century from 1856 to 1945, the date of the Cohen Committee. It was the age of laissez-faire and has been much discussed: Parliament was less keen to intervene in connection with the generality of companies, where the view expressed in 1856 by Robert Lowe, then President of the Board of Trade, that `having given [companies] a pattern the State leaves then to manage their own affairs ... (quoted in Hein, 1978, p. 149) provided a rationalization of the widespread belief that it was no business of the state to interfere in what were seen as private contracts between shareholders (Sugarman and-Rubin, 1984, p. 12). Moreover, a laissez-faire approach on the part of the courts, where `formalist' views were at their height (Atiyah, 1979, pp. 388-97), seems also to have affected the attitude to accounts on the part of the courts. This may be observed in the series of `dividend' cases in the nineteenth century (French, 1977) where judges on the whole were loath to go beyond the companies' Articles of Association and the latter of the Companies' Acts (unless they could adduce fraudulent or improper behaviour on the part of directors) in assessing matters of valuation, income measurement and profit determination. (Napier and Noke, 1992, p. 38, emphasis added). These issues `matters of valuation, income measurement and profit determination' form the basis for much of this dissertation. There is one further paper extending the work of Jefferys (1938) and Cottrell (1980) on the format of share issues from 1914 (Pitts 2000).

The thesis explores applications of optimisation in investment management and risk measurement. In investment management the information issues are largely concerned with generating optimal forecasts. It is difficult to get inputs that have the properties they are supposed to have. Thus optimisation is prone to 'Garbage In, Garbage Out', that leads to substantial biases in portfolio selection, unless forecasts are adjusted suitably for estimation error. We consider three case studies where we investigate the impact of forecast error on portfolio performance and examine ways of adjusting for resulting bias. Treynor and Black (1973) first tried to make the best possible use of the information provided by security analysis based on Markovitz (1952) portfolio selection. They established a relationship between the correlation of forecasts, the number of independent securities available and the Sharpe ratio which can be obtained. Their analysis was based on the assumption that the correlation between the forecasts and outcomes is known precisely. In practice, given the low levels of correlation possible, an investor may believe himself to have a different degree of correlation from what he actually has. Using two different metrics we explore how the portfolio performance depends on both the anticipated and realised correlation when these differ. One measure, the Sharpe ratio, captures the efficiency loss, attributed to the change in reward for risk. The other measure, the Generalised Sharpe Ratio (GSR), introduced by Hodges (1997), quantifies the reduction in the welfare of a particular investor due to adopting an inappropriate risk profile. We show that these two metrics, the Sharpe ratio and GSR, complement each other and in combination provide a fair ranking of existing investment opportunities. Using Bayesian adjustment is a popular way of dealing with estimation error in portfolio selection. In a Bayesian implementation, we study how to use non-sample information to infer optimal scaling of unknown forecasts of asset returns in the presence of uncertainty about the quality of our information, and how the efficient use of information affects portfolio decision. Optimal portfolios, derived under full use of information, differ strikingly from those derived from the sample information only; the latter, unlike the former, are highly affected by estimation error and favour several (up to ten) times larger holdings. The impact of estimation error in a dynamic setting is particularly severe because of the complexity of the setting in which it is necessary to have time varying forecasts. We take Brennan, Schwartz and Lagnado's structure (1997) as a specific illustration of a generic problem and investigate the bias in long-term portfolio selection models that comes from optimisation with (unadjusted) parameters estimated from historical data. Using a Monte Carlo simulation analysis, we quantify the degree of bias in the optimisation approach of Brennan, Schwartz and Lagnado. We find that estimated parameters make an investor believe in investment opportunities five times larger than they actually are. Also a mild real time-variation in opportunities inflates wildly when measured with estimated parameters. In the latter part of the thesis we look at slightly less straightforward optimisation applications in risk measurement, which arise in reporting risk. We ask, what is the most efficient way of complying with the rules? In other words, we investigate how to report the smallest exposure within a rule. For this purpose we develop two optimal efficient algorithms that calculate the minimal amount of the position risk required, to cover a firm's open positions and obligations, as required by respective rules in the FSA (Financial Securities Association) Handbook. Both algorithms lead to interesting generalisations.

The U.K. capital market has observed a remarkable growth in the use of lease financing as a tool of financial management. It must be recognised, however, that its profitable use by Industry is dependent upon an easily applicable and theoretically acceptable method of evaluation within corporate capital budgeting procedures. Increasingly, analysts have come to acknowledge the need to integrate corporate investment and financing decisions insofar as concerns the acquisition of industrial plant and equipment. However, traditional methods of lease evaluation fail to examine its integrative nature, and in consequence, they neglect the critical interdependencies which encompass the simultaneous decision process. Extant lease evaluation models also fail to consider the consequences of the earnings generated by the "Residual Capital Balances". That is, the working capital freed when leasing is strategically used to relax what otherwise would be an unacceptable shortage of funds. Such earnings are a fundamental part of an integrated lease cash-flow profile under certain circumstances: namely, the use of leasing as part of a "Planned Financing Mix", as opposed to its use as an emergency or "spill-over" financing when no residual capital occurs. On the basis of extensive empirical study into the circumstances under which U.K. financial management had recourse to leasing, a hypothesis was developed to explain the role of leasing in corporate financial planning and debt management. The research proceeds to establish models for the evaluation of leasing under "spill-over" conditions (where all otherwise available sources of finance are, or appear to be, exhausted) and "Planned Financing" conditions (when the use of leasing in quantitative terns is formally envisaged as part of the corporate financing policy). In this way it is possible to determine the risks implicit in the haphazard use of leasing together with the benefits available to its planned use.

This thesis analyses interactions between firms and governments in climate change and international trade. First, a theory of international agreements on climate change is presented in which governments negotiate targets and firms bear the cost of emission reductions. It analyses the effect on negotiations of investment, on R&D for instance. The public good nature of the problem implies that investment improves the government’s bargaining position. Anticipating this effect on the Nash-bargained outcome will induce firms, surprisingly, to over-invest with respect to the second best. The second chapter explores a different area in which firms and governments interact: trade policy. This chapter analyses the incentives for trade protection in an electoral college setting by constructing a new multi jurisdictional political agency model. The introduction of a spatial factor shows how the distribution of swing voters across decisive, swing states affects trade policy incentives. The empirical analysis introduces a measure of how industries specialise geographically in swing and decisive states by augmenting a benchmark test of the "Protection for Sale" mechanism. The evidence provides support for the theory. A newly-available firm-level panel dataset for Belgium is described in the third chapter, in a bid to understand the patterns in the trade transaction data. The final chapter considers the determinants of firm exporting behaviour, in particular liquidity constraints. A heterogeneous �firms trade model shows how exporters in general, firms exporting to more destinations and to smaller markets, weighted by distance, are less likely to be credit-constrained. Finally, in the presence of liquidity constraints, the impact of exchange rates on trade flows is decomposed. These equilibrium relations hold in the Belgian data, measuring credit constraints with firm-year-level credit scores. This highlights the potential role of governments in determining, through their policies on credit constraints, the patterns of trade and hence productivity levels and overall welfare.

While there have been a number of studies of foreign exchange risk management in UK Multinational Companies (MNCs), the management of economic exposure has received very little attention. The aim of this study was to describe the management of economic exposure (and its relationship to transaction exposure) in UK MNCs. A random sample of twenty MNCs was selected, and archival data relevant to foreign exchange risk management were gathered. Finance personnel in both the HQ and the Irish subsidiaries of the twenty companies were interviewed. The results of the study with respect to transaction exposure were similar to previous studies. However, data collected at a subsidiary level revealed that the degree of centralisation may be underestimated by HQ treasurers, since divisional personnel may influence the practices in foreign subsidiaries. The degree of centralisation was explained by the presence of transaction costs in foreign exchange markets, and a relationship between centralisation and netting opportunities was detected. The in-house bank was highlighted as a mechanism for realising transaction cost savings without decreasing operating unit autonomy. An examination of the economic exposures of the sample companies revealed that economic exposure might be classified into four subsets: 1) Sticky Price Exposure (of which transaction exposure is a subset) 2) Traded Good Exposure (which arises from the tradeability of the MNC's products and factors of production) 3) Parallel Import Exposure 4) The Macroeconomic and Sectoral Consequences of Exchange Rate Changes The managerial response to economic exposure was also examined. The majority of corporate treasurers were only involved in transaction exposures and, with a few exceptions, the response to economic exposure was operational rather than financial. Political and promotional tactics were used extensively to manage economic exposure in the short-run. The creation of barriers to entry (and the resultant decrease in the tradeability of the firm's products) was a popular medium-run strategy. The author also found that only some of the sample MNCs had significant economic exposures. Finally, a decision support model was developed in order to operationalise the measurement of economic exposure, and the evaluation of exposure management alternatives.

Over the last 250 years, insurance law has become insurer biased to the detriment of consumers and modern business. Codification of judicial precedents and business practices resulted in the Marine Insurance Act 1906. There have been two attempts since the late 1950s to recommend changes, with reviews made by the English Law Reform Committee and the Law Commission in 1980. In the late 1970s, the insurance industry bought itself out of the Unfair Contract Terms Act 1977. In 1981, non-legal changes came gradually with the introduction of the Insurance Ombudsman Bureau, which took account of the law but followed best practice. With each decade that has passed, changes in practice have deviated away from the strict legal position. The insurer no longer has an agent to arrange policies, collect premiums and complete claims forms. The late 1980s and early to mid-1990s saw the introduction of distance selling via the telephone. The late 1990s, and early into 2000, saw the massive boom in Internet sales, with search engines focused on finding the best competitively priced quotes from insurers; however, the reforms that were needed still did not occur. The Marine Insurance Act 1906 still applied and formed the basis of insurance law for many common law countries which copied the statue verbatim. As a result, these countries also had similar problems as those suffered by the insured in the UK; however, some have undergone bold reforms, as in the case of Australia, unlike the UK, which has lagged behind significantly. The Scottish Law Commission and the Law Commission instigated a joint root-andbranch review of insurance law in 2006, as a result of a British Insurance Law Association paper (Insurance Contract Law Reform and Recommendations to the Law Commission (2002)) that highlighted the discrepancies in the law towards the insured. Unfortunately, however, the Commissions chose to focus on only certain areas. This thesis does not cover these aspects. It is concerned, however, with what could broadly be termed 'good faith', the corresponding duties vis-à-vis the insured and the insurer pre- and post-contract where the insured suffers disproportionately due to the way the law has developed pro-insurer biased. This body of work supporting the award of a PhD examines these corresponding duties where the articles form a basis of a contemporary, critical examination of these duties, and develops suggestions as to how the joint Law Commissions of England and Scotland should have approached changes.

The purpose of this thesis is to determine and to better inform industry practitioners to the most appropriate classification and regression techniques for modelling the three key credit risk components of the Basel II minimum capital requirement; probability of default (PD), loss given default (LGD), and exposure at default (EAD). The Basel II accord regulates risk and capital management requirements to ensure that a bank holds enough capital proportional to the exposed risk of its lending practices. Under the advanced internal ratings based (IRB) approach Basel II allows banks to develop their own empirical models based on historical data for each of PD, LGD and EAD. In this thesis, first the issue of imbalanced credit scoring data sets, a special case of PD modelling where the number of defaulting observations in a data set is much lower than the number of observations that do not default, is identified, and the suitability of various classification techniques are analysed and presented. As well as using traditional classification techniques this thesis also explores the suitability of gradient boosting, least square support vector machines and random forests as a form of classification. The second part of this thesis focuses on the prediction of LGD, which measures the economic loss, expressed as a percentage of the exposure, in case of default. In this thesis, various state-of-the-art regression techniques to model LGD are considered. In the final part of this thesis we investigate models for predicting the exposure at default (EAD). For off-balance-sheet items (for example credit cards) to calculate the EAD one requires the committed but unused loan amount times a credit conversion factor (CCF). Ordinary least squares (OLS), logistic and cumulative logistic regression models are analysed, as well as an OLS with Beta transformation model, with the main aim of finding the most robust and comprehensible model for the prediction of the CCF. Also a direct estimation of EAD, using an OLS model, will be analysed. All the models built and presented in this thesis have been applied to real-life data sets from major global banking institutions.

The three papers in this thesis comprise the development of three types of Basel models – a Probability of Default (PD), Loss Given Default (LGD) and Exposure at Default (EAD) model for consumer credit risk, using mixture model methods. Mixture models consider the underlying population as being composed of different sub-populations that are modelled separately. In the first paper (Chapter 2), mixture cure models are introduced to the area of PD/credit scoring. A large proportion of the dataset may not experience the event of interest during the loan term, i.e. default. A mixture cure model predicting (time to) default on a UK personal loan portfolio was developed and its performance compared to industry standard models. The mixture cure model's ability to distinguish between two subpopulations can offer additional insights by estimating the parameters that determine susceptibility to default in addition to parameters that influence time to default of a borrower. The second paper (Chapter 3) considers LGD modelling. One of the key problems in building regression models to estimate loan-level LGD in retail portfolios such as mortgage loans relates to the difficulty in modelling its distribution, which typically contains an extensive amount of zeroes. An alternative approach is proposed in which a mixed discrete-continuous model for the total loss amount incurred on a defaulted loan is developed. The model simultaneously accommodates the probability of zero loss and the loss amount given that loss occurs. This zero-adjusted gamma model is shown to present an alternative and competitive approach to LGD modelling. The third paper (Chapter 4) considers EAD models for revolving credit facilities with variable exposure. The credit conversion factor (CCF), the proportion of the current undrawn amount that will be drawn down at time of default, is used to calculate the EAD and poses modelling challenges with challenging bimodal distributions. We explore alternative EAD models which ignore the CCF formulation and target the EAD distribution directly. We propose a mixture model with the zero-adjusted gamma distribution and compare performance with CCF based models. We find the mixture model to be more accurate in calibration than the CCF models and that segmented approaches offer further performance improvements.