This thesis is mainly divided into three chapters. Even though the three chapters have different aims, they all concern investment environment and process. With respect to the former aspect, we consider how stocks and bonds are traded in securities markets. The second and third chapter deal with markets where a single risky asset is sequentially traded in batch auctions. In the fourth chapter we consider bond markets where transaction costs create frictions. As for the investment process, we study how market participants should choose their investment, and when should it be made. We analyze trading strategies for market participants in the second and third chapter, while active bond portfolio management is dynamically characterized in the fourth chapter. Chapter 2 develops a dynamic trading game in which fundamental insiders coexist with non-fundamental speculators. We study inclusions in the S&P 500 as an example in which non-fundamental speculation arises due to preannouncing index replacements. Evidence on volume and liquidity is consistent with our theoretical analysis. Chapter 3 deals with asymmetrically informed traders engaging in information sharing about the asset's fundamental value. In the presence of information sharing, trading activity and price volatility both cluster at the end of the trading period, and price informativeness is reduced. Our model predicts a rich variety of patterns for liquidity, volume and return volatility. Chapter 4 focuses on affine term structure models as portfolio management tools. We use returns implied by different models as inputs for an investor's portfolio optimization problem. Each period we determine the optimal investment, and then characterize the financial properties of trading strategies. We show that evaluating term structure models from a financial perspective may yield conflicting results with those arising from a statistical metric.

The introduction of the Autoregressive Conditional Heteroskedasticity (ARCH) model in 1982 by Engle revolutionized the econometric treatment of volatility. The Generalized ARCH (GARCH) model and its variants have proved to be useful in capturing stylised facts about financial markets, which include volatility clustering, leptokurtosis in the distribution of returns, mean reversion tendencies and leverage effects. The Periodic GARCH (PGARCH) variants proposed by Bollerslev and Ghysels (1996), in particular, made it possible to explicitly incorporate the effects of periodicity in financial time series into the parameters of the volatility models. An investigation of return volatility using high frequency Kuala Lumpur Composite Index (KLCI) returns data shows that the intraday volatility pattern follows the double U-shaped pattern, which is consistent with the findings of other studies on markets that are closed during the lunch hour. The study also investigates the best technique for modelling and forecasting the intraday periodicity on the Kuala Lumpur Stock Exchange (KLSE), using both the jointly estimated and the two-step filtration approaches with different PGARCH structures. The results indicate that the PGARCH models produce superior model fit, better forecasting performances and superior forecast quality than the standard GARCH equivalents. However, the results suggest that Value-at-Risk (VaR) models, constructed from the PGARCH forecasts, produce poor results. This study also investigates the integrated realized volatility measure introduced by Andersen and Bollerslev (1998a), which can be constructed by summing up intraday squared returns. The results suggest that the daily integrated realized volatilities constructed using different intraday return sampling frequencies, produce superior forecasting performances for the GARCH models when compared with the results of the same models using the daily squared returns. The VaR models constructed from the GARCH forecasts and the Autoregressive and Moving Average (ARMA) forecasts appear to satisfy the requirements of the framework for interval forecast evaluation.

This thesis addresses three problems associated with the risk in stock markets from a global perspective. First, we investigate the empirical hedging effectiveness using index futures in six world major stock markets. A variety of econometric models including STVECM with bivariate GARCH error structure are employed. The within-sample and out-of-sample results suggest sophisticated models do not produce the best hedging strategies consistently and their usefulness has to be judged on a case-by-case basis. Second, we examine the cross hedging effectiveness of seventeen MS CI indices through a global approach of using a combination of the related index futures. A thorough comparison among strategies corresponding to different combinations of hedging instruments and econometric models is conducted for each MSCI index. The optimal hedge ratio vector is derived for each country on the basis of both within- sample and out-of-sample results. Third, we develop a global asset pricing model on the basis of Barro's rare disaster model to explain the equity risk premium puzzle. Despite the plausible analytical predictions on the expected return of the bill and equity and the equity risk premium, the global model fails to explain the scale of the equity premium observed in the data since the diversification in a global market brings down both the aggregate risk and the reward for holding risk equity. The former results in a rise in the expected return of government bills and the latter leads to a fall in the expected return of equities.

This thesis investigates the behavior of firms listed on the stock exchanges of the Gulf Co-operation Council (GCC) countries in relation to the determination of their dividend policies. This may be considered more generally as a case study of emerging stock exchanges, where the determinants of dividend policy in emerging stock markets have received little attention. The study uses panel data of non-financial firms listed on the stock exchanges of GCC countries as a whole, and of five individual countries (Kuwait, Saudi Arabia, Oman, Qatar and Bahrain,), for the five year period between 1999 and 2003. The study develops nine hypotheses, which relate to the agency cost theory and which have been investigated in the previous literature. Based on these hypotheses, three models have been tested to address the limitations of previous work. The first model considers the impact of government ownership, free cash flow, firm size, growth rate, growth opportunity, business risk, and firm profitability. As some of the GCC states stock markets disclosed additional information about ownership structure, two additional models have been used to investigate whether the additional information provides additional insight into dividend policy. The first additional model re-tests dividend payout policy after adding institutional ownership to the explanatory variables used in the general model. The second additional model introduces the variable large shareholders, whether government, institutions, or individuals. The hypotheses have been tested by using two methods (1) the fixed effects and random effects models, and (2) the random effects Tobit model, which is better able to represent the fact that a significant number of listed firms chose not to distribute cash dividends in some or all of the years of the study period. In general, the fixed and random effects approaches, gave results consistent with the random effects Tobit approach. These results suggest that the main characteristics of dividend payout policy in these firms is that dividend payment relates strongly and directly to government ownership and firm profitability. These results taken as a whole indicate that firms pay dividends with the intention of reducing the agency problem and maintaining firm reputation since the legal protection for outside shareholders is limited in these countries. In addition, and as a result of the significant agency conflicts interacting with the need to built firm reputation, a firm's dividend policy depends heavily on firm profitability for the same year. This may indicate that listed firms, in the GCC states, alter their dividend policy very frequently and do not have a long-run target dividend policy. The results also report that the common variables of transaction cost theory (growth rate, leverage ratio, and business risk) have lower importance in explaining dividend policy that may have been predicted by previous work, as these factors were found to be significant in very few cases. Hence, this study concludes that dividend policy of firms listed on the GCC stock exchanges is affected mainly by agency cost but partly by transaction cost theory. Overall, this research indicates that government ownership plays an important role in dividend policy, and this characteristic is of particular relevance to consider when evaluating firms listed on the GCC stock exchanges.

The prime contribution of this research is that it provides various empirical results regarding the bivariate and multivariate causality and cointegrating relationships between Vietnam’s stock market returns and macroeconomic variables, specifically those pertaining to economic growth (GDP), consumer price index (CPI), broad money supply (M2), interest rates (IR – including deposit rate DR, lending rate LR, and refinancing rate FR), foreign exchange rate USD/VND (EX), and foreign direct investment (FDI). The robustness of Vector Autoregressive (VAR) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) frameworks were tested for Vietnam, which is a new emerging market. Using an updated data set of 161 monthly observations collected for the period from August 2000 to December 2013, a unique equation that represents the linkage among variables of interest was established. Particularly, a wide range of techniques, including unit root tests, Johansen cointegration tests, Granger causality tests, dynamic analysis (impulse response function and variance decomposition) were employed, which demonstrated that the VN-Index corresponds to long run, and also short run, path of selected macroeconomic variables. Furthermore, taking the volatility clustering into account, GARCH (1,1) models reveal the predictability of stock market volatilities using previous shocks (i.e. those originating from GDP, CPI and EX) rather than the previous volatility itself. The discussion of empirical findings has additionally been substantiated and corroborated via a field questionnaire, which gathered views of experts who are directly or indirectly involved with Vietnam’s stock market. The empirical results, along with the outcome of the empirical survey, provide the basis for policy and investment implications, emphasizing that using macroeconomic indicators would be beneficial to policy-makers, as well as securities investors, in promoting the development of Vietnam’s stock market. The addition of external shocks (i.e. global crash 2007-2008) and/or other portfolios of stocks (VN30-Index, HNX-Index, HNX30-Index, UPCoM-Index) could be considered in further research.

Over six chapters, this thesis explores how to estimate risk-sharing when output is not exogenous. The thesis starts with a survey of the current literature and how it estimates risk-sharing. This survey is then followed by risk-sharing estimations based on a panel of 24 countries over the period of 1970-2007. The estimation approaches applied include the literature's Classical and Level approaches, as well as alternative estimation approaches that provide robust parameter estimates when the literature commonly assumed output exogeneity is dropped. These alternative estimators consist of procedures using instrumental variables ranging from first differenced two-stage least squares, a dynamic generalized method of moments estimation, and an instrumental variables estimation using an instrument derived from a structural vector autoregressive model. Also, a Monte Carlo Simulation is undertaken to show the severity of the bias inherent in the Classical estimation method, as well as to show the performance of the proposed alternative methods. When output is endogenous, the Classical estimation method is found to underestimate risk-sharing, while the best performing alternative approaches are concluded to be the Level approach and the instrumental variables estimation approach using an instrument derived from a structural vector autoregressive model. This thesis contributes to the risk-sharing literature by discussing and quantifying the bias the Classical estimation approach suffers from due to output endogeneity. It also contributes by adapting estimation methods from other fields that allow consistent estimations of risk-sharing parameters in the presence of endogeneity bias, and by analyzing the performance of these asymptotic panel estimators in the specific context of the panel dimensions commonly found in the risk-sharing literature.

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This thesis explores the question of model-free trading and hedging in markets where traded asset prices are continuous and where one may trade continuously in time with no transaction costs. In particular, we make no assumptions on the volatility of traded asset prices. The contributions of the thesis are as follows. First, we propose a framework of model-independent replication of financial derivatives based on solutions to systems of PDEs evaluated at market-observed inputs. This provides a model-independent extension of the paradigm of dynamic hedging to general markets with continuous prices. We then relate these replication strategies to local martingales of a certain closed form and characterise the latter for several specifications of markets. The markets we consider are: (1) a market with no traded claims, (2) a market with an underlying asset and a convex claim, (3) a market with an underlying asset and a set of co-maturing call options. The auxiliary results for the latter two markets may be of interest outside of the local martingale characterisation results. Thirdly, we propose a definition of integration with continuous paths that justifies a probability-free version of the hedging results outlined earlier. Finally, we present a number of smaller contributions related to model-free hedging and to probability-free integration with continuous paths.

Finance Theory is built mainly based on the assumption that investors are risk neutral. We run two finance experiments to test American option pricing theory. Dynamic programming and optimal stopping theory are used for the construction of the models. Simulation studies are conducted for the experiments. In the first experiment, we test a disinvestment case of real options theory in discrete time. Our results show that risk aversion explains better the decisions of the participants than risk neutrality as few of the participants appeared to be risk neutral. Furthermore, risk aversion explains better the behaviour of the subjects than myopic behaviour. In the second experiment, we examine the timing of the exercising of an American call option contract in continuous time. We estimate the risk aversion parameters of the subjects from the main experiment, and we elicit their risk aversion parameters by running another small experiment with allocation questions. Based on these parameters we find the estimated and the elicited risk averse optimal trigger respectively. From our analysis we show that the estimated risk averse optimal trigger explains better the actual stopping decisions of the subjects, while the risk neutral optimal trigger has the next highest explanatory power and the elicited risk optimal trigger the lowest. The third project tests the stochastic assumptions underlying an analysis by examining the statistical properties of the estimated parameters and comparing them to the actual values. This study shows that the stochastic specification underlying any analysis matters for the interpretation of its results. In the last project, we check the interdependency relationships among the five major market sectors of Greece, Italy and Portugal. By using dependency tests, such as Johansen cointegration and Granger causality tests, we find that the Greek sectors provide some diversification benefits for sector-level investments, while the opposite is true for the Italian sectors. Only in the case of Portugal do the results suggest non-existence of interdependency relationships among the sectors for the first sub-period of the total period we examine and their existence later. Moreover, by using the variance decomposition and the time-varying volatility methodologies we conclude that for all the three countries the majority of the sectors are exogenous and their volatility is highly increased due to crisis, particularly in the case of the Financials sector.