Insurance and reinsurance are important tools of risk management. A well-designed (re)insurance strategy can help individuals and institutions to effectively adjust its risk position to match its risk appetite while meeting other targets such as profitability. Thus, optimal (re)insurance design has been a popular research area during the last fifty years. The first contribution investigates the optimal reinsurance contract from the perspective of an insurer who would like to minimise its risk exposure under Solvency II. Under this regulatory framework, the insurer is exposed to the retained risk, reinsurance premium and change in the risk margin requirement as a result of reinsurance. Depending on how the risk margin corresponding to the reserve risk is calculated, two optimal reinsurance problems are formulated. We show that the optimal reinsurance policy can be in the form of two layers. Further, numerical examples illustrate that the optimal two-layer reinsurance contracts are only slightly different under these two methodologies. In the second contribution, numerical optimisation methods that are practically implementable and solvable are discussed with actuarial applications. The efficiency of these methods is extremely good for some well-behaved convex problems, such as the Second-Order Conic Problems. Specific numerical solutions are provided in order to better explain the advantages of appropriate numerical optimisation methods chosen to solve various risk transfer problems. The stability issues are also investigated together with a case study performed for an insurance group that aims capital effciency across the entire organisation. The next two contributions aim to identify a robust optimal insurance contract that is not sensitive to the chosen risk distribution. The first of the two contributions focuses on the classical robust optimisation models, namely the worst-case and the worst-regret model, which have been already investigated in literature relating to optimal investment portfolio problems, while Bayesian type robust optimisation models are discussed in the second contribution. A caveat of robust optimisation is that the optimal solution may not be unique, and therefore, it may not be economically acceptable, i.e. not Pareto optimal. This issue is numerically addressed and simple numerical methods are found for constructing insurance contracts that are both Pareto and robust optimal.

This thesis introduces a general framework for model-free discretisation-invariant swaps. In the first main chapter a novel design for swap contracts is developed where the realised leg is modified such that the fair value is independent of the monitoring partition. An exact swap rate can then be derived from the price aportfolio of vanilla out-of-the-money options without any discrete-monitoring or jump errors. In the second main chapter the P&Ls on discretisation-invariant swaps associated with the variance, skewness and kurtosis of the log return distribution are used as estimators for the corresponding higher-moment risk premia. An empirical study on the S&P 500 investigates the factors determining these risk premia for different sampling frequencies and contract maturities. In the third main chapter the dynamics of conventional and discretisation-invariant variance swaps and variance risk premia are compared in an affine jump-diffusion setting. The ideas presented in this thesis set the ground for many interesting and practically relevant applications.

We know that managers may use their discretion by structuring transactions that can alter financial reports in order to persuade stockholders in their interpretation of the underlying economic performance of the company. The study reported in this thesis examines such earnings discretion in the six monthly interim reports issued by listed firms in the UK, and investigates the relationship between estimates of earnings manipulation and the market pricing of the firm's shares. This is tested by examining whether managers use their discretion to sustain earnings trends in the case of ‘winner' firms, i.e. those that are in the upper range of prior returns, and likewise to keep a negative trend in ‘loser' firms, those in the lower range of prior returns. Specifically, momentum portfolios are formed based on past six-month returns and tested for differences in future six-month earnings management, as measured by discretionary current accruals in six month interim reporting periods. The results suggest that discretionary current accruals are significantly associated with past returns for winner more than loser firms, and hence that past returns may contribute to the explanation of future earnings management, the behaviour being consistent with appearing either to persist as winners or to turn losers around

This thesis analyses the causes and consequences of access to credit by small- scale enterprises in developing countries and the design of optimal financial systems. The first essay explores the link between informality and access to external finance by Small and Microenterprises (MSEs). A probit model is estimated using data on MSEs from Ethiopia. The results show that informality plays an important role in a firm's access to credit. Specifically, informal firms are about sixteen percentage points more likely to be credit constrained than their formal counterparts. The second essay examines the consequence of credit constraints on a firm's innovation using the same data on MSEs from Ethiopia. We construct a measure of innovation exploiting a question in the survey that asks whether a firm has engaged in some form of innovation or not. Employing various estimation methods to deal with the possible endogeneity of access to credit, the results show that access to credit has a significant and positive effect on a firm's propensity to engage in innovative activi- ties. The third essay examines whether opening a stock exchange boosts per capita income growth in Sub-saharan Africa countries (SSA). Employing a semi-parametric Difference-in-Difference (DiD), i.e., a DiD on a set of matched countries, we show that opening a stock exchange does not appear to have a significant impact on eco- nomic growth in SSA as well as in other developing countries in other regions. The fourth essay studies whether the structure of the economy determines the evolution of the optimal structure of the financial system. Employing a measure of economic structure constructed based on a country's comparative advantage and using an in- novative instrumentation strategy to deal with the possible endogeneity of economic structure, the essay shows that the structure of the economy exerts a first-order causal effect on the evolution of the structure of a country's financial system

The purpose of this thesis is to analyse the interaction of currency intervention, speculation and sentiment, and their influence on the exchange rate dynamics across the developed and developing countries. This thesis tackles the three factors attributable to the unsolved issues in the field, i.e., the lack of proper data set or proxies, theoretical foundation, and structural models. After reviewing the related literature, microstructure frameworks are built with theoretical set-ups, e.g., the international parities, the forward rate bias and central bank credibility. Then the transmission channels of currency interventions, the reaction functions of central banks, and the impacts of the speculators activity and psychology are examined with cointegrated VAR methodology. In doing so, this thesis offers thorough structural and identified analyses of developed and developing country currencies in a joint theoretical framework. Therefore, this thesis fills some methodological, theoretical and empirical gaps in the field of international finance. Furthermore, it provides not only suggestions for future empirical and theoretical research but also policy implications for central banks across developed and developing countries.

The aim of this thesis is three-fold. First, in contrast to developed exporting countries such as Australia, New Zealand and Canada, Middle East oil exporting countries are years behind achieving the prerequisites for floating exchange rate and Inflation Targeting monetary regime. On the other hand, their performance under fixed exchange rate (to the US dollar) has brought them some painful experience such as the Dutch Disease and high inflation. For a sample of five of these countries -- Qatar, Oman, Kuwait, Saudi Arabia and the UAE -- we conduct a set of counterfactual experiments. We empirically simulate government consumption expenditure, under a hypothetical peg to a nominal anchor (oil price in either the radical or moderate version) or to a basket (containing the US Dollar, Yen and the Euro) and compare this simulation with whatever exchange rate regime each country actually followed. We find that lower volatility of real oil price in local currency causes lower volatility in government expenditure and fiscal balance as a share of GDP. Hence, we face a less volatile economy. Second, we determine the equilibrium exchange rate (using BEER) of these five oil exporting countries in the Persian Gulf which depend heavily on exports of oil, natural gas and oil products. We employ a new data set for the real effective exchange rate of these countries which is updated annually and covers the period from 1980 to 2011. Given the limited length of the sample (32 years) and low power of individual country by country tests for unit root and cointegration, estimating separate equations for each country (time series) does not provide us with precise results; therefore, to increase the efficiency of the estimators, we employ panel analysis. We apply the pooled mean-group (PMG) of Pesaran et al. (1999) and four more panel estimators for a robustness check. All estimators strongly support the positive effect of real oil price on the real effective exchange rate (i.e. higher real oil price leads to appreciation of the real effective exchange rate) which is consistent with theoretical predictions and with previous studies for commodity (oil) exporting countries. The productivity deferential elasticity is 0.10 which is consistent with the results of the related literature such as the studies of MacDonald and Ricci (2004) for South Africa, and of Lee et al. (2008) for 48 countries over 1980-2004. The BEERs of Qatar, Kuwait and (to some extent) the UAE follow their real effective exchange rates. From 2000, with the increase in oil price, the BEERs appreciate while the real exchange rate of Oman and Saudi Arabia decline; therefore, the Saudi Arabian and Omani currencies get undervalued. Third, employing a new data set of Canadian commodity price indices, we revisit the Canada Bank Equation and introduce a new version with more fundamentals. We present a similar equation for Australia as one of the other developed commodity exporting countries. Using cointegration and the first differences analysis between real exchange rate and fundamentals, we investigate the SVECM and SVAR frameworks to decompose the variance of real exchange rate of Canada and Australia. In the SVECM analysis, the productivity differential and commodity price are the main contributor to the variance of the real exchange rates of Australia and Canada. For the SVAR analysis, we confirm that, as in the literature, demand shock is the dominant force in explaining the variance of real exchange rates of both countries. This result does not change even by adding the commodity price shock to the SVAR framework.

In this dissertation, liquidity, price volatility and integration are investigated in European natural gas markets. Liquidity in the one-month-ahead forward market is examined using tick-by-tick data and measures from financial markets. A time-varying multivariate approach is adopted to assess correlations between trading activity, volatility and liquidity. Results support the extension of the financial market microstructure theory to physical markets and contribute towards understanding dynamics and driving forces of liquidity in energy markets. They confirm that order flow aspects asset prices and that a correlation exists between price volatility and liquidity. The main drivers of natural gas price volatility are identified using BEKK models, which are particularly suitable because they allow for volatility spillovers within markets. Asymmetries and changes in the fundamental drivers of demand, supply and inventory are considered, and expectations of the theory of storage are assessed. Results support fundamental values as main drivers of price volatility in natural gas markets and indicate greater integration between natural gas and electricity markets. Finally, the process towards the integration of European natural gas markets is investigated in the one-month-ahead and day-ahead forward markets. Cointegration procedures are adopted, which are robust to outliers, seasonalities, leptokurtosis and GARCH effects in the energy price time series. Results show that barriers to trade remain, which prevent full integration, mostly in day-ahead markets, and may impact competitiveness. Long-run relationships between crude oil and natural gas prices are also investigated and are not supported by data, thus highlighting increased reliance of hub pricing mechanisms to the fundamental drivers. In all, there are indications of greater exposure of hub prices to short-term dynamics in the natural gas and power sectors, which are affected by capacity allocation management and have implications for the overall efficiency of European energy sector.

In most developed economies, the insurance sector earns premiums that amount to around eight percent of their GNP. In order to protect both the financial market and the real economy, this results in strict regulations, such as the Solvency II Directive, which has monitored the EU insurance sector since early 2016. The largest item on general insurers’ balance sheets is often liabilities, which consist of future costs for reported claims that have not yet been settled, as well as incurred claims that have not yet been reported. The best estimate of these liabilities, the so-called reserve, is given attention to in Article 77 of the Solvency II Directive. However, the guidelines in this article are quite vague, so it is not surprising that modern statistics has not been used to a great extent in the reserving departments of insurance companies. This thesis aims to combine some theoretical results with the practical world of claims reserving. All results are motivated by the chain ladder method, and provide different reserving methods that will be introduced thoughout four separate papers. The first two papers show how claim estimates can be embedded into a full statistical reserving model based on the double chain ladder method. The new methods introduced incorporate available incurred data into the outstanding liability cash flow model. In the third paper a new Bornhuetter-Ferguson method is suggested, that enables the actuary to adjust the relative ultimates. Adjusted cash flow estimates are obtained as constrained maximum likelihood estimates. The last paper addresses how to consider reserving issues when there is excess-of loss reinsurance. It provides a practical example as well as an alternative approach using recent developments in stochastic claims reserving.

This thesis consists of four essays exploring quantitative methods for investment analysis. Chapter 1 is an introduction to the topic where the backgrounds, motivations and contributions of the thesis are discussed. This Chapter proposes an expert system paradigm which accommodates the methodology for all four empirical studies presented in Chapters 2 to 5. In Chapter 2 the profitability of technical analysis and Bayesian Statistics in trading the EUR/USD, GBP/USD, and USD/JPY exchange rates are examined. For this purpose, seven thousand eight hundred forty-six technical rules are generated, and their profitability is assessed through a novel data snooping procedure. Then, the most promising rules are combined with a Naïve Bayes (NB), a Relevance Vector Machine (RVM), a Dynamic Model Averaging (DMA), a Dynamic Model Selection (DMS) and a Bayesian regularised Neural Network (BNN) model. The findings show that technical analysis has value in Foreign eXchange (FX) trading, but the profit margins are small. On the other hand, Bayesian Statistics seems to increase the profitability of technical rules up to four times. Chapter 3 introduces the concept of Conditional Fuzzy (CF) inference. The proposed approach is able to deduct Fuzzy Rules (FRs) conditional to a set of restrictions. This conditional rule selection discards weak rules and the generated forecasts are based only on the most powerful ones. In order to achieve this, an RVM is used to extract the most relevant subset of predictors as the CF inputs. Through this process, it is capable of achieving higher forecasting performance and improving the interpretability of the underlying system. The CF concept is applied in a betting application on football games of three main European championships. CF’s performance in terms of accuracy and profitability over the In-Sample (IS) and Out-Of-Sample (OOS) are benchmarked against the single RVM and an Adaptive Neuro-Fuzzy Inference System (ANFIS) fed with the same CF inputs and an Ordered Probit (OP) fed with the full set of predictors. The results demonstrate that the CF is providing higher statistical accuracy than its benchmarks, while it is offering substantial profits in the designed betting simulation. Chapter 4 proposes the Discrete False Discovery Rate (DFDR+/-) as an approach to compare a large number of hypotheses at the same time. The presented method limits the probability of having lucky findings and accounts for the dependence between candidate models. The performance of this approach is assessed by backtesting the predictive power of technical analysis in stock markets. A pool of twenty-one thousand technical rules is tested for a positive Sharpe ratio. The surviving technical rules are used to construct dynamic portfolios. Twelve categorical and country-specific Morgan Stanley Capital International (MSCI) indexes are examined over ten years (2006-2015). There are three main findings. First, the proposed method has high power in detecting the profitable trading strategies and the time-related anomalies across the chosen financial markets. Second, the emerging and frontier markets are more profitable than the developed markets despite having higher transaction costs. Finally, for a successful portfolio management, it is vital to rebalance the portfolios on a monthly basis or more frequently. Chapter 5 undertakes an extensive investigation of volatility models for six securities in FX, stock index and commodity markets, using daily one-step-ahead forecasts over five years. A discrete false discovery controlling procedure is employed to study one thousand five hundred and twelve volatility models from twenty classes of Generalized AutoRegressive Conditional Heteroskedasticity (GARCH), Exponential Weighted Moving Average (EWMA), Stochastic Volatility (SV), and Heterogeneous AutoRegressive (HAR) families. The results indicate significant differences in forecasting conditional variance. The most accurate models vary across the three market categories and depend on the study period and measurement scale. Time-varying means, Integrated GARCH (IGARCH) and SV, as well as fat-tailed innovation distributions are the dominant specifications for the outperforming models compared to three benchmarks of ARCH (1), GARCH (1,1), and the volatility pool’s 90th percentile. Finally, Chapter 6 puts together the main findings from the four essays and presents the concluding marks.

This thesis attempts to investigate the cross-sectional predictive power of return asymmetry, skewness and tail risk. It mainly consists of three empirical chapters on the relation between predictive patterns of the return distribution and expected stock returns. In the first empirical chapter, I adopt a measure of asymmetry, originally proposed by Patil et al. (2012), which can be employed to characterise the shape of the entire distribution of asset returns instead of skewness. Empirical evidence on the relation between asset returns and the skewness of the return distribution is mixed. As skewness is primarily influenced by the tail behaviour of the return distribution, it is possible for two distributions with identical skewness to have quite different asymmetry. I will examine the relationship between this new measure and stock returns. My empirical analysis indicates that stocks with high return asymmetry exhibit low expected returns. The negative relation between return asymmetry and expected returns persists after I control for size, book-to-market, momentum, short-term return reversals, liquidity, idiosyncratic volatility and various skewness factors. My results are consistent with the findings from theoretical models such as those of Brunnermeier et al. (2007) and Barberis and Huang (2008). In the second empirical chapter, I examine the default risk and financial crisis explanations for the market skewness risk effect and find that the effect is stronger among stocks with large size, high growth, and low default risk. This suggests that the positive skewness preference theory only holds for safe stocks. Moreover, the effect of market skewness risk on stock returns interacts with default risk significantly. Market skewness risk has explanatory power for stock returns only during the periods of good economic conditions. Additionally, the market skewness risk effect is not persistent. After the financial crisis of 2007-2008, the strong effect disappears. In the last empirical chapter, I know that investors sometimes underweight the tail event. I then try to figure out this situation by examining the default risk and financial crisis explanations for the tail risk effect. I find that market size, book-to-market ratio, and default risk have large impact on the tail risk effect. Moreover, tail risk only has explanatory power for stock returns during the periods of good economic conditions. The results suggest that when investors hold stocks with small size, low growth, and high default risk, the tail risk tends to be ignored. The tail risk effect is not persistent. The significant tail risk effect also disappear after the financial crisis of 2007-2008.