This thesis focuses on two closely related areas of liquidity and market impact. The historic limit order book of Stock Exchange Trading Sys- tem (SETS) operated by the London Stock Exchange (LSE) is rebuilt using this framework for empirical analysis of information contained in the limit order book. The concept of Notional Volume Weighted Average Price (NVWAP) is introduced to construct liquidity supply and demand curves based on real time bid and ask schedules of the full length of the limit or- der book. This unique approach is used to determine how the order book behaves and I find consistent wave-like patterns between up- ward and downward price trends. Regression coefficients of the slope of the curves for each market event are estimated using an exponen- tial model. Four statistics are defined to identify bullish and bearish trends without prior knowledge of the market price. Detailed analy- sis shows that these statistics correctly identify market conditions for 88% to 97% of the observations. The intraday patterns of regression coefficients are revealed using a nonparametric kernel regression model. These intraday patterns are not found to be consistent between stocks over time. A resampled and deseasonalised set of estimated regression coefficients is analysed for temporal dependence using a multivariate vector autoregression (VAR) model. Inferences drawn from marginal probabilities regarding Cranger-causality do not show significant impact of slope coefficients on the opposite side of the limit order book implying that each side of the market is simultaneously rather than sequentially influenced by prevailing market conditions. The VWAP concept is extended to estimate the average shape of the limit order book and average market impact. The average market impact estimates are found to be superior than the order imbalance based approach. A time-of-day market impact for a given aggregate volume is estimated using a multivariate kernel regression model with monotonicity constraint. The estimated market impact shows stock- specific and wave-like impact that is asymmetric for buyers and sellers.

Leverage offers the possibility of enhancing financial returns and, consequently, the profit and the end of period wealth. Leverage is gaining importance and has been widely adopted in the financial markets for t,VD reasons. Firstly, brokers are interested in offering margins because they can charge higher transaction fees and make profits from lending margins. Secondly, investors are also interested in taking leverage because of the ability to enhance their individual returns. The motivation of this thesis is that, even though leverage is gaining importance in modern investments, existing models in the literature models assume that the series of financial returns are normally distributed. However, financial returns present high-level of kurtosis and, hence, are not normally distributed. Thus, existing analytical models underestimate extreme returns and consequently underestimate the risk of default. I contribute to this field by proposing a new trading strategy that uses numerical methods to calculate the optimal level of leverage instead of the existing analytical models. The use of numerical methods allows me to relax the assumption of normally distributed returns, and hence minimises the risk of underestimate extreme returns and the risk. of default. I investigate whether the use of numerical methods leads to a more accurate optimal level of leverage than analytical models, and if the use of the optimal level of le'verage using numerical methods improves the investment performance. In order to test the ability of the optimal1evel of leverage using numerical methods to improve the investment performance, I employ two different approaches: back-testing and agent-based modelling. Back-testing allows me to test the optimal level of leverage using numerical methods using empirical I , evidence, and agent-based modelling allows me to test the optimal level of leverage using numerical methods in a totally controlled environment. The conclusions are that the use of numerical methods leads to a more accurate optimal level of leverage than analytical models; using daily historical data as an empirical evidence, the optimal level of leverage using numerical methods improves investment performance; and in a totally controlled environment) the ability of the optimal level of leverage to improve investment performance depends on the size of the market.

The thesis covers three main chapters. The first chapter (which is a joint work) we develop a theoretical model of rational bubble. In equilibrium, a bubble can persist until it bursts following an exogenous shock, even when all the agents are aware of the bubble and that it will burst in finite time. Applying the model in the context of the sub-prime mortgage crisis, we argue that excessive sub-prime lending behaviour may be sensible with the introduction of securitization. We thus provide a rational explanation for the housing bubble and the dramatic increase in subprime default rates. In the second chapter I conduct empirical short-dated volatility forecasting in foreign exchange, and carry out a realistic volatility swap trading strategy based on the forecast. Additional to applying regime-switch technique, I propose a double-step approach to circumvent the disadvantage of employing GARCH-type model in the high frequency data in FX market, so that it can separate the effect of intraday/intraweek seasonality and pre-scheduled macroeconomic data releases from the underlying data process. By keeping a battery of models and rotating among them, the forecast ability gets significantly enhanced and the trading profit is pronounced even after considering transaction cost. In the third chapter I explore the cross-sectional predictive power of the most important two factors in the implied volatility surface - skew and term structure - at individual firm level. Stocks with lower implied volatility skew and higher implied volatility term structure outperform the comparative peers. In particular, the interaction between these two factors reinforces the predictive power, and the return of a weekly long-short strategy can be improved greatly with the attachment of term structure on skew. By sorting firms based on skew and term structure one may also be able to pick up takeover targets and seize the big positive premium.

The London Stock Exchange is constantly changing as the global financial landscape evolves. By aggregating detailed intraday trading data, I analyse its liquidity for a period spanning the introduction of a pure electronic order book platform for the most liquid stocks in 1997, its expansion to include less liquid stocks with market maker participation, the structural and environmental changes brought about by MiFID regulation in 2007, and the beginning of the global financial crisis. By all measures, liquidity has increased over the years, although recently intensified competition from alternative trading venues may be limiting further improvement. The most liquid stocks are the constituents of the FTSE 100 index, which are picked by largest market capitalization. When a new stock is added to this index there is a temporary price effect which I ascribe to the closing auction just before the index is revised. This is a natural time for passive investors who track the index by replicating its composition to adjust their portfolio holdings. The auction trade is facilitated by a build-up of liquidity on the opposite side of the order book in advance, as limit orders are placed in competition to take the other side of this information-free order flow at a premium. Naturally, ordinary trading in index constituents does contain information about individual stocks, groups of stocks and the entire market. Conveniently, another liquid security trades on the market which can be used as a conduit for the latter information: the FTSE 100 exchange-traded fund. Due to arbitrage opportunities its price is closely related to the index, and in fact I determine that they are cointegrated, even intraday. According to the eo integration analysis the fund makes a significant contribution to the index price discovery process, and this is especially evident when order flows are incorporated into the model.

This thesis explores the meaning and measures of market development theory. Unlike abundant previous studies that approach the stock market development concept as homogeneous, this work asserts that stock market development has multiple meanings depending upon the perspective of user groups. Accordingly, the study defines the stock market development concept from the international institutional investors' and governments' perspectives. The thesis identifies empirically the factors that influence the current stock market classification by practitioners, namely S&P's, FTSE and MSCI, as developed or emerging. In addition, cut-off points are suggested to distinguish developed markets from emerging markets. The results show that there are in fact three main segments in the development path of a stock market, namely developed markets (top), emerging markets (middle) and another segment comprising stock markets that are below the emerging markets (bottom). The last group may also be labelled 'pre-emerging'. Measures of stock market development from both the international institutional investors' and governments' perspectives are applied to achieve two objectives. First, to test claims or theories asserted on the basis of previous measures of stock market development in the literature, which are considered generally weaker than the measures constructed in this thesis. Secondly, to investigate the scenarios in which the interests of international institutional investors converge or diverge with those of governments, and the reasons for such convergence or divergence. The results obtained from the investigation above confirm, modify or differ with previous claims as follows: First, results confirm the proposition that stock market development is negatively related to ownership concentration, conditional on investor protection quality (La Porta et al., 1997, 1998). Second, this work builds on a claim that stock market development is inversely related to dividend yield, conditional on governance quality and cost of capital, as suggested by La Porta et al. (2002) and Henry (2003) respectively by showing that not all perspectives conform to these relations. Third, this work not only confirms, but also extends Demirguc-Kunt and Maksimovic's (1996) claim that stock market growth favours equity financing over debt financing in more developed markets and that the opposite is true in under- developed stock markets. Fourth, Morck et al.'s (2000) proposition that stock market returns in under-developed markets tend to move together more than in developed markets is re-visited and re-interpreted. Fifth, this thesis confirms the existence of divergent and convergent interests 11 .> , ABSTRACT among equity market stakeholders. This finding extends and confirms the 'interest group theory' suggested by Rajan and Zingales (2003). And sixth, this study, like Spamann (2005, 2010) reports that the original anti-director rights index from La Porta et al. (1998) and the revised anti-director rights index from Djankov et al. (2008) are not good predictors of ownership concentration. Interestingly, the stock market development indices developed in this research are found to associate better with ownership concentration than both previous indices in the literature and anti-director rights indices. This thesis concludes that clear understanding of the meaning and measures of the stock market development concept may improve investment, policy and regulatory decisions globally. Specifically, this understanding among policy makers and academicians can help to prevent or reduce the potential for future financial crises. III

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This thesis identifies and fills certain gaps in the empirical literature on the relationship between exchange rates and stock prices, and equity portfolio diversification, with the aim of providing useful information for academics, private investors, currency risk hedgers, and policy-makers. Firstly, it analyses granger-causal links between exchange rates and stock prices even at a level of stock market disaggregation not previously considered, taking into consideration a number of factors that may influence the lead/lag results. Secondly, the thesis considers whether exchange rate movements actually contribute to systematic or undiversifyable risks in national equity markets, particularly assessing the implications (thus far) of the single European currency (the euro) on the risk premiums of major equity markets, given the general perception that the EMU should reduce exchange rate and equity market risks. Several studies have advocated cross-border equity investments as a tool for reducing equity portfolio risks, despite inherent problems including exchange rate risks. Finally therefore, this thesis contributes to the literature on the diversification of equity portfolio risks by assessing the potential of home-based diversification in three developed European equity markets as an alternative to international portfolio diversification, and the potential benefits of eurozone diversification. The evidence suggests the existence of time-varying granger-causal links between exchange rates and stock prices in most countries, although the lead/lag structure for each country may differ when the stock market index is disaggregated, contradicting theoretical models. Although the EMU does not appear to have reduced the exchange rate risk premium in key member states, the same cannot be said about the equity market premium, which has reduced in three of the four member countries investigated. Finally, it appears that the potential of diversifying within the European equity market is such that any extra benefit from international equity acquisitions for diversification purposes is statistically and economically insignificant.