There is a wealth of literature investigating the relationship between different financial markets such as stock markets and exchange rates, however, these studies do not reveal any theoretical or empirical agreement or any definite pattern or consistent relationship between these markets. It is encouraging to carry out further investigation of this kind especially keeping in mind the majority of the studies are dedicated to developed countries, neglecting developing countries, such as Saudi Arabia. This study contributes to the literature by carrying out an investigation into the dynamic interaction and the volatility spillovers between multiple financial markets and stock market in the emerging economy that is considered to be the biggest and the most important economy in the Middle East. Firstly, this study investigates the relationship between the Saudi stock market and three foreign exchange rates; Swiss Franc, British Pound, and the Euro. Secondly, it investigates the volatility spillovers between the two Saudi Arabia and major Middle Eastern stock markets in one hand and the Saudi stock market and major world equity markets on the other. The study employs multiple unit root testing starting from conventional unit root testing such as ADF, DF GLS, PP, and KPSS to more complex stationarity testing tools such as: non-linear unit root test ESTAR, GARCH unit root test, and M-TAR unit root test. For long-term analysis between the Saudi stock market and exchange rates, the study makes use of Engle and Granger co integration tests, ARDL bounds testing by Pesaran, Johansen, and Asymmetric co integration under M-TAR analysis. The study found no evidence in favour of the long-term relationships between the stock market and the exchange rates. On the other hand, it was discovered that short-term unidirectional causality effect do exist that run from two exchange rates to the return on the stock price after conducting Granger causality, and modified Sims causality test. For volatility spillovers analysis, univariate GARCH, Cross Correlation Function (CCF), multivariate GARCH BEKK, and rangebased volatility of Diebold and YiImaz (2009) are employed. Results on volatility spillovers analysis between the Saudi stock market and major Middle Eastern capital markets indicates the existence of volatility and return spillovers dominated by the Saudi stock market. It also suggests the existence of volatility spillovers coming from more advanced economies to the Saudi stock market dominated by the US and UK markets.

In the world of finance, the emergence of Islamic finance has led to many Islamic financial products and services. Access to professional fund managers who specialize in forming portfolios that fulfil the needs of Muslim investors to trade in investments that do not violate their Islamic principles and rules is now commonly available in both Muslim and non-Muslim countries. Islamic stock market indices (ISMI) have also been established. This thesis consists of three self-contained empirical essays that focus on important financial issues for Muslim investors: (1) the empirical support for orthodox asset pricing models when applied to Islamic stocks; (2) the volatility of Islamic stock market indices and the relevance of oil to this volatility; and (3) seasonality in an Islamic stock market. In addition, each empirical essay compares the findings of ISIM to those of an appropriate counterpart conventional stock market index (CSMI). The findings firstly demonstrated that ISMI can be exposed to different risk factors from those proposed by previous empirical works on CSMI. Secondly, the statistical results established that ISMI proves to be a safe investment during the oil market turbulences contrary to CSMI. Thirdly, the last empirical essay found out that the emergence of ISMI in the non-Muslim countries can bring about another calendar anomaly or at least change the effect of an existing one such as Friday effect. The general conclusion to be drawn from the findings of the whole thesis is that there are variations between ISMI and CSMI in the way they react towards the same exogenous variables. This is despite the fact that previous studies failed to find significant differences between them in terms of performance, and merely observed that investors lose nothing by restricting themselves to ISMI.

The Efficient Market Hypothesis (EMH) has been widely studied in the literature, however there remains no consensus among academics whether markets are efficient or not. Although it was initially thought to hold, the recent explosion of studies that find that markets are not efficient has cast serious doubt on the validity of the EMH. Furthermore, the vast majority of the literature examines the EMH over some predetermined sample period, disregarding the fact that the level of efficiency may change over time and a large sample period may not be efficient or not for the whole period. A new theory that tries to accommodate both these facets is the Adaptive Market Hypothesis (AMH), proposed by Andrew Lo (2004). This theory enables market efficiency and market inefficiencies to co-exist together and market efficiency to evolve over time. The main objective of this thesis is to examine the AMH and stock return behaviour in major stock markets using very long data and determine whether it is a more appropriate model for describing stock market behaviour than the EMH. A five-type classification is proposed to distinguish the differing behaviour of stock returns over time. Daily data is spilt into five-yearly subsamples and investigated in respect of linear and nonlinear time-series tests, three calendar anomalies and the moving average technical rule. The results suggest that the AMH provides a better description of the behaviour of stock returns than the classic EMH. Linked to the AMH is the fact that investors are not rational and investor psychology plays a real role in investor’s decision making. With that in mind, this thesis also examines the level of investor sentiment in stock returns during World War Two in Britain. This is a time period that has not been studied in great detail and provides an opportunity to examine investor sentiment in extreme circumstances. The empirical results show that there was strong negative investor sentiment from major negative events and a strong level of local bias during the period known as the Blitz.

The thesis deals with several aspects of the impact of informed speculation on financial markets. It consists of four chapters. Chapter 1 gives a general discussion of the welfare effects of insider trading, and investigates whether insider trading should be prohibited. The following chapters are concerned with more specific questions of the organisation and regulation of financial markets. Chapter 2 investigates the performance of dealership markets in the presence of informed speculation. It is shown that informed trading creates externalities which might render markets with several competing market makers less liquid than a market with a monopolist specialist. Chapter 3 deals with a different effect of insider trading on secondary markets. It is argued that insider trading influences the allocation of risk between different classes of investors. The premature resolution of uncertainty due to insider trading makes prices more volatile and more informative. The effects of these two opposed effects on ex-ante investment are ambiguous: both more and less investment may occur. Chapter 4 investigates a dynamic asset pricing model with informed speculation and noise trading. The properties of the steady state equilibria in a overlapping generations economy with infinite horizon are characterized. It is shown that noise trading leads to feedback effects of the kind that expectations of a high price volatility become self-stabilizing. The effects of asymmetric information and the early release of information are discussed and related to the results of the preceding chapters.

Using time series analysis, this research provides an approximation of the market dynamics in emerging and developed stock markets. A number of potential risks arising from a range of informational, structural and regulatory features in emerging markets are investigated by taking stock market efficiency as the central concern. Comparative empirical evidence on some of the established anomalies in developed markets is provided for both long standing and recently established emerging markets. The findings suggest that despite perceptions of instability, volatility, and inefficiency emerging markets do not appear to significantly differ in return and risk characteristics from the developed markets considered in this study. Daily returns in both developed and emerging markets appear to violate weak-form efficiency and exhibit day of the week effects. The volatility of the emerging and developed stock markets can be commonly characterised by the presence of persistent shocks and time varying volatility. Even at the individual stock level emerging and developed markets exhibit similar time series features. Daily returns from two of the newly emerging markets also indicate volatility features which are not significantly different from longer established emerging markets and mature developed markets. This research has shown that despite the heterogeneity of systems and investors, return and risk characteristics of stocks from emerging markets appear similar to the developed markets with comparable evidence of time dependence in volatility and returns. The findings of this research have several interesting theoretical and practical implications. First, modern infrastructure and regulations do not appear to have any significant influence on return and volatility characteristics. As documented in this study, even a newly re-established and modern Polish market can support return and volatility characteristics that are consistent with the notion of noise or speculative trading. This suggests that even though markets may have necessary facilities for efficient operation, stock prices may not be consistent with statistically defined market efficiency. Secondly, strictly from the point of view of informational market efficiency, emerging markets do not appear to be significantly different from developed markets, other than in respect of size. This may suggest that perhaps the "emerging markets phenomenon" needs to be reviewed. Thirdly, the Chinese case shows that it is not sufficient to merely have appropriate regulations in place to attract foreign equity investment. Market depth and liquidity are two further factors which influence the decisions of the foreign institutional investors. Last, daily returns in both emerging and developed markets appear to show significant and comparable nonlinearity suggesting that risk cannot be measured by the conventional models of equilibrium.

The degree of stock market integration has important implication for cross-border portfolio diversification, for which the Mainland China has become an attractive destination, particularly following the gradual open-up of its A-share market to foreign institutional investors. The first part of this thesis explores the various aspects of stock market integration taking place in Mainland China, in an attempt to resolve the ambiguity between extant empirical and anecdotal evidence on the issue. The evidence drawn from different statistical perspectives collectively establishes that the Mainland Chinese stock market is in a process of further integrating with a selection of world's developed stock markets. Nevertheless, such increased integration should not preclude foreign institutional investors from diversifying into the Chinese A-share market, as the current integration is far from being complete. Adopting appropriate risk monitoring technique for venturing into the volatile Chinese A- share market is another imperative issue faced by foreign institutional investors, whose risk practices and economic capital are largely regulated by the Basel Accord. The second leg of this thesis addresses this problem through an evaluation of various volatility forecasting models for Value-at-Risk (VaR) reporting. Our results highlight the importance of adopting heterogeneous risk monitoring models in different investment environments for the purpose of regulatory compliance and optimal economic capital allocation. Overall, the studies contained in this thesis should add knowledge to the burgeoning literature on international financial integration at large, while serving the interests of institutional investors, and financial regulatory authorities alike.

This thesis aims to investigate the behaviour of financial markets by using agent-based computational models. By using a special adaptive form of the Strongly Typed Genetic Programming (STGP)- based learning algorithm and real historical data of stocks, indices and currency pairs I analysed various stylized facts of financial returns, market efficiency and stock market forecasts. This thesis also sought to discuss the following: 1) The appearance of herding in financial markets and the behavioural foundations of stylised facts of financial returns; 2) The implications of trader cognitive abilities for stock market properties; 3) The relationship between market efficiency and market adaptability; 4) The development of profitable stock market forecasts and the price-volume relationship; 5) High frequency trading, technical analysis and market efficiency. The main findings and contributions suggest that: 1) The magnitude of herding behaviour does not contribute to the mispricing of assets in the long run; 2) Individual rationality and market structure are equally important in market performance; 3) Stock market dynamics are better explained by the evolutionary process associated with the Adaptive Market Hypothesis; 4) The STGP technique significantly outperforms traditional forecasting methods such as Box-Jenkins and Holt-Winters; 5) The dynamic relationship between price and volume revealed inconclusive forecasting picture; 6) There is no definite answers as to whether high frequency trading is harmful or beneficial to market efficiency.

This thesis examines the gains to acquiring shareholders in cash-acquisitions which occurred in Thailand in the period between 1992 and 2001. It analyses the impact of stock market valuations at the time the acquisitions occurred and the impact of toehold acquisition strategy on acquirers' post-acquisition performance. The first part reviews the merger and acquisition (M&A) history in the US and Thailand, Thai stock market history and corporate governance. It shows that the merger waves which took place in both countries are positively correlated to economic prosperity. However, after the Asian crisis in 1997, this relationship is reversed for Thailand. Accordingly, the second part empirically investigates the impact of stock market valuations and acquiring shareholders' long-term performance. The findings show that high-valuation acquirers perform significantly less well than low-valuation acquirers. The underperformance is due to an overpayment of acquisition premiums. Two-stage regressions allow us to discover that the acquisition premium is endogenously determined by the acquirer's financial constraint and the target's leverage. The acquirer's financial constraint is found to have a positive relationship with the acquisition premium whereas the target's leverage is found to be negatively related to the acquisition premium. The findings suggested that stock market valuation has a significant impact on acquiring shareholders. Engaging in an acquisition during a high-valuation period destroys shareholders' value in the long-run whereas low-valuation acquisition is considered to be a profitable strategy. In the third part, the role of toeholds1 and their impact on acquirers long-term performance is examined. Simultaneous equations are employed in order to investigate the relationship between the size of the toehold, the stock price run-up2 , the acquisition premium, and the acquirer's long-term performance. Since acquiring a toehold alerts the market to the possibility of a successful takeover and to a target's value, the size of the toehold is found to increase the target's stock price run-up. However, the size of the toehold is not found to have a direct effect on the acquisition premium but indirectly influences the acquisition premium through the stock price run-up. An increase in the stock price run-up is found to positively influence the acquisition premium. Both the stock price run-up and the acquisition premium have significant negative impacts on acquiring shareholders' post-acquisition gains. Therefore, toehold acquisition induces an added cost of acquisition by increasing the target's share price prior to the announcement date and leading to an acquisition premium.

This research investigates various issues relating to the level and volatility of returns on ordinary shares. In particular, we have looked at the relation over time between volatility and risk premia, both at a univariate and multivariate levels. We also look at the links between stock markets over the world, and whether they are integrated. We evaluate the role of measurable economic variables in explaining asset price (co-)movements over time. Our model combines an APT factor pricing approach with a GARCH-type parameterisation of the volatility of the factors. These can be "observable" (i.e. related to economic variables), "unobservable" and country-specific. Estimates of these factors and their time-varying variances are obtained using a Kalman Filter-based Full Information Maximum Likelihood method. Using monthly data on sixteen markets it is found that idiosyncratic risk is significantly priced, and that the "price of risk" is not common across countries, which rejects the null of global capital market integration. Another empirical finding is that most of the correlation between markets is accounted for by the "unobservables". The econometric background to the conditionally heteroskedastic factor model employed is also analysed. We find that the matrix of factor loadings is unique under orthogonal transformations, and as a result, that it is possible to evaluate the separate contribution of the different factors to the risk premia if time-variation in the volatility of the factors is recognised. We also obtain a full characterisation of this model under the assumption that the conditional distribution is multivariate t, (the normal being a special case), and GARCH formulations for the conditional variances. A fundamental question in Finance is whether the stock market satisfies the Efficient Market Hypothesis. In this regard, we explore whether lagged variables that help predict stock returns are merely proxying for mis-measured risk. Three different ways of measuring risk are employed (i.e. semi-parametric, GARCH and lagged squared returns). In an application to Japanese data, four key predictor economic variables are shown to have non-trivial additional forecasting power irrespective of how risk is measured. Interestingly, unlike the US, the level of the lagged dividend yield is not positively correlated with returns in either Japan or South Korea. Moreover, there is no consistent relationship between expected volatility and excess returns. Another interesting topic is the hypothesis that the degree of autocorrelation shown by high frequency stock returns may change with volatility. This may result from non-trading effects, feedback trading strategies or variable risk aversion. Results using a century of daily data suggest that when volatility is low there tends to be positive autocorrelation in returns, but this serial correlation can become negative during very volatile episodes. Our results also suggest that returns are more likely to exhibit negative serial correlation after price declines. Finally, a new Quadratic ARCH model for the conditional variance of a time series is introduced, and interpreted as the quadratic projection of the square innovations on information. Since it nests the original ARCH model and several of its extensions, its statistical properties are very similar, while avoiding some of their criticisms. In an application to a century of daily US stock returns, QARCH models provide a better representation of the data by capturing the leverage effect (i.e. volatility is higher following price declines than after rises). QARCH models are also able to capture this asymmetry in a multivariate context: in a factor model for monthly excess returns on 26 industrial UK sectors, the common factor (which is highly correlated with the FTA500) also shows a significant leverage effect.

The present thesis is an empirical investigation into various aspects of the functioning of financial markets. The first chapter includes two studies of the behaviour of the stock market: in the first one, the reaction to announcements of rights issues is analysed and several hypotheses are tested for a sample of UK companies. In the second study a switching regression model is applied to aggregate stock price data to see if a two-states model is better able to describe the behaviour of stock market prices. The second chapter investigates the empirical relationship between managerial ownership of shares and corporate performance, using a panel dataset of UK manufacturing companies. The two measures of performance investigated are: market valuation, as expressed by Tobin's Q, and total factor productivity growth, measured by estimating a production function. The explicit consideration of companies with dual structures of voting rights enables me to study the effects of a disparity in the ownership of equity and votes by managers, and the effects of the concentration of voting rights which is made possible by departures from one share-one vote. Finally, the ability of technical analysis to predict future price behaviour is analysed in the third chapter which consists of three studies. The first reports the results of an experiment in which a Chartist product has been tested for its ability to help users to predict future asset price movements. The second analyses the behaviour of three major exchange rates around support and resistance levels. The third tests two competing theories for their ability to explain the clustering observed in quoted prices. The approach used in this study of technical analysis differs from the previous ones since it employs inputs provided by technical analysts themselves and subjects them to empirical analysis, rather than trying to reproduce the 'data generation process' of technical analysts.