The consequences of financial market speculation go far beyond the floors of stock and currency exchanges. In the last decade, speculative behaviour caused financial panics in South America, Southeast Asia and Russia. Questions about the reasons and nature of speculation once again attracted the attention of economists and financial practitioners. Although it seems to be rather impossible to provide a full explanation of speculation, partial evaluations are certainly possible. This thesis concentrates on the impact of speculation on the distribution of market returns. The relationship between parameters of speculation processes and stable distribution is established. This allows conclusions to be drawn about the level of market speculation based on the estimated parameters of distribution of returns. The thesis proposes an application of the minimum chi-squared methodology to estimate parameters of symmetric stable distribution. This approach offers substantial precision and flexibility when dealing with clustered, truncated and grouped data. It is applied to analyse Polish and Hungarian stock prices. In the main part of the thesis, the speculation processes that could produce heavy tailed returns are reviewed. The relationship between the parameters of the Diba-Grossman speculative process and those of the stable distribution of returns is evaluated. In particular, the positive dependence between the variance of the stochastic root of Diba-Grossman process and thickness of tails of the distribution is shown. In the empirical part, the thesis analyses returns to 66 stock indices. The tendency for mature markets to reveal slightly lower exposure to speculation than the emerging markets is found. Outlier tests show that some countries, e.g. Russia, Estonia and Bangladesh, are characterised by a lower level of speculation than is implied by the degrees of non-normality.

This study has examined the efficiency of the Saudi stock market by applying the weak-form test of the efficient market hypothesis, because the only information available is the prices of past years. To test for weak-form efficiency of SSM, the prices over a four-years period from 1992 to 1995 have been statistically analysed.;This thesis is divided into nine chapters. Chapter one is an introduction to this thesis. Chapters two and three briefly outline the structure of the Saudi Arabian economy and the financial system. The following two chapters review the classification of financial markets in general and the structure and regulation of the Saudi stock market.;Chapter six reviews literature concerning the efficient market theory and its implications in many studies.;Chapter seven discusses research methodologies used for market efficiency tests at the weak-form level in this study. In addition, data transformation and description are discussed.;Chapter eight contains the empirical examination included tests for empirical distribution of log price changes, auto-correlation tests, runs test and filter rules. The results are summarised in chapter nine.;However, this weak-form evidence indicates that the Saudi stock market has a lower level of efficiency than other large markets. The findings of this study are following the many researchers suggestions that small markets tend to have lower levels of efficiency than large well-traded markets.

This thesis is the first directly to study the entire limit order book of a large market. Herein, I conduct a population study on the microstructure of the Eurodollar future market, to my knowledge this is a) the first study of its type and b) the largest microstructure study ever conducted. I will build a data-drive model that incorporates information from the entire population of quotes updates and transactions on this type of future market. This thesis aims to provide a comprehensive understanding of the market microstructure on money market derivatives and the impact of high-speed algorithmic trading activity on the market characteristics and quality. I apply a broad battery of market volatility and liquidity measurements, and gauge the proportion of high-frequency algorithmic traders in the market. This thesis provides a standard asymmetric information based theoretical model to predict the relation on the term structure of Eurodollar future contracts. The prediction is a non-linear relation between the saturation of algorithmic traders (ATs) versus the impacts on the quality of the market. Therefore, I develop a novel semi-parametric estimator and model the non-linear relation between the impact of the fraction of algorithmic trading and a large set of different market quality indicators including volatility, liquidity and price informativeness. Finally, I consider the efficiency and the speed of high-frequency prices formation by implementing the return autocorrelations and vector autoregression, and also make a contribution to the trade classification algorithm using the order book data. My findings are fourfold. First, the impact of high-frequency trading (HFT) on market quality is a non-linear by implementing the semi-parametric model. This may partially explain why prior studies have found contradictory results regarding the impact of high-frequency traders (HFTs) on market characteristics. Second, prior studies only including the inside quotes or best bid best ask are limited to reflect all the information in the market. My findings suggest that the second level quoting in the limit order book is by far the most rapidly quoted element of the order book. Furthermore, I find that wavelet variance covariance of the bid and the ask side changes substantially over the term structure; providing further supporting evidence of the non-linear impact of HFTs. Finally, the adjustment time of the trade prices formation process is within one second, and the quote prices are even faster within 200 milliseconds (ms). The mid-quoted return autocorrelation is positive and gradually increase from the shortest time interval to the longest time interval. The trade prices are less sensitive to new information as the contract approaches its maturity.

In the London of August 1914, there was no statutory regulation of share trading. By the beginning of 1946, only traders registered in accordance with the Prevention of Fraud (Investments) Act 1939 were permitted to engage in share trading between members of the public. This study examines the stages by which share trading in the United Kingdom came to be a statutorily regulated activity and by which the London Stock Exchange moved from being antagonistic towards public regulation in 1914 to lobbying in 1944 for the new scheme to be implemented. A number of challenges were posed by changes in the character of the demand for and supply of securities which were evident before 1914 but hastened by the 1914-1918 war. There is no evidence that the Exchange, its members or outside observers understood how these changes would affect the overall character of the market or its sensitivity to risk. Almost all regulatory interventions between 1914 and 1945 responded to crises which exposed the failure of existing arrangements to cope with the consequences of market changes. Whilst these interventions show that self-regulatory arrangements could be effective, they also demonstrate the limitations of reliance on self-regulation alone. Although the Exchange’s members supported severe action after the crashes of 1929, the criminal justice system again proved inadequate to deal with abusive share trading generally. The 1939 legislation responded to the criminal justice system’s failure and, for the Exchange, was made palatable by protecting its formal independence. Each successive regulatory intervention in part responded to compromises in previous interventions occasioned by the need to secure acceptance by market operators.

This thesis uses liquidity to examine some stock market phenomena. It begins by researching the role of liquidity in explaining the “disappearing dividend puzzle” across several financial markets. Then, it examines the cash/stock dividend payouts and their determinants in China. Finally, this paper investigates the interplay among illiquidity, variance risk premium and stock market returns. The research studies the disappearing dividend puzzle with a large sample of firms representing eighteen countries over the sample period from 1989 to 2011. Our investigation finds that risk is an important determinant of firms’ dividend payout policy. For firms in the US, France, UK and other European markets, liquidity plays an additional role in explaining the changes in propensity to pay. Then we test the explanatory power of liquidity, risk and catering incentives in the “disappearing dividend puzzle”. The thesis finds support for catering theory among firms in common law countries but not those in civil law countries. The catering incentives persist even after adjusting the propensity to pay for liquidity. However, after controlling for risk, the significant explanatory power of catering incentives in the changes in propensity to pay disappears. Our results indicate that catering incentives capture the risk difference between dividend payers and non-dividend payers. Then, the research studies the payout patterns of both cash and stock dividend in China over the sample period 1999-2013. The Chinese stock market is a fast-growing market with some special characteristics, such as complicated corporate ownership structures. The specific characteristics of Chinese firms might affect the dividend payout policy in China. We first study the determinants of Chinese firms’ dividend payout policy. Our results indicate that lifecycle, risk and liquidity are important determinants of firms’ cash/stock dividend policy. We find that firms with larger board size and fewer annual board meetings are more likely to pay cash dividends and less likely to pay stock dividends. Also, the research notes that managerial stake is insignificant in explaining Chinese firms’ cash/stock dividend payouts. Then, we investigate the catering theory in China. Our findings show that catering incentives matter in explaining the unexpected percentage of dividend payers if we do not control for liquidity/risk. However, once we control for liquidity/risk, the catering incentives contribute little toward explaining the changes in propensity to pay cash/stock dividends. Our results imply that Chinese firms’ cash/stock dividend policy is influenced by the board, rather than managers or investors. Finally, this thesis investigates the interplay among illiquidity, variance risk premium and market returns. Previous studies that test whether liquidity is useful in forecasting market returns ignore the question of whether variance risk premium might also be useful for this purpose. As a result, these papers potentially overestimate the role of liquidity in predicting market returns. This thesis tests whether liquidity and variance risk premium are useful for return forecasting by comprehensively investigating the interplay among illiquidity, variance risk premium and market returns. We adopt monthly US data from January 1992 to December 2010. The results show that variance risk premium, reflecting investors’ risk aversion to volatility risk, causes variations in stock returns, and in turn causes market illiquidity, rather than vice versa. Furthermore, we find that variance risk premium has substantial forecasting power over future market returns, while liquidity measure does not. Additionally, our results indicate that variance risk premium impacts equity returns by acting on the risk factors, i.e. market risk premium, value factor and momentum factor.

The thesis seeks a better understanding of the market microstructure topic, evaluates an informed trading measurement tool that is available for econometricians, and attempts to measure the impact of the presence of hidden liquidity to market quality. The two favorable prevailing informed trading detection, PIN, and VPIN models are used to investigate the informed trading activity around LIBOR manipulation in the LIBOR reference futures market- Eurodollar futures. These two models show a significant performance as an early warning system, however, there is not statistically significant differences relative to the event in the long-run variation. In addition to the chapter seven of this thesis, I examine the relationship between market quality and hidden liquidity, uncovering a strong positive effect from hidden order to market quality proxies.

The study examines the effects of price limits on return, volatility and liquidity by testing three hypotheses: delayed price discovery hypothesis, volatility spillover hypothesis and trading interference hypothesis (Kim and Rhee, 1997, JF). The delayed price discovery hypothesis states that if the price continues to move in the same direction in the subsequent period after a price-limit-hit, the existence of limits delays price discovery. The volatility spillover hypothesis argues that the stock will have a higher volatility after a price-limit-hit. The trading interference hypothesis asserts that a share that hits the price limits on day t will experience more trading on day t+1. The rationale behind price limits is to provide investors with a cooling-off period to counter noise trading and alleviate market panic. If price limits work, all three hypotheses should be rejected. Firms on the Shanghai and Shenzhen Stock Exchanges can simultaneously issue two types of shares: A and B-shares. A-shares were initially traded only by domestic Chinese citizens, but opened to Qualified Foreign Institutional Investors (QFIIs) from July 2003 onwards. B shares were initially traded only by foreign investors but then by local Chinese citizens from June 2001. A and B-shares are subject to the same price limits but exhibit different risk and return characteristics. This study explores the effects of price limits on AB-shares using daily data (intraday data) over the period 2004-2012 (2010-2012). For the first time, this study estimates a GARCH model that explicitly incorporates truncation in the distribution of returns that is induced by price limits. The truncated-GARCH model provides a better fit than a conventional model. Based on the study of daily data, the delayed price discovery and volatility spillover hypotheses are not rejected on either exchange. Similar results have been found in the study of intraday data that price limits are not effective in controlling volatility and counter noise trading. Regarding the trading interference hypothesis, price limits interfere with market liquidity but the level of interference depends on the choice liquidity measures.

This thesis consists of three essays, which examine the behaviour of stock market indices in light of the recent crises, in relation to volatility, information and sentiment. Essay 1 focuses on the link between the flow of public information and stock market volatility in the FTSE, DJIA and the S&P 500 indices. This essay builds on existing literature in several ways. First, a new proxy for the daily public information flow is created to encompass a wider range of publication than previous contributions. It is also disaggregated by media type. This proxy is tested as an explanatory variable in index return volatility. Through the use of augmented GARCH models, the essay explores (a) whether information flow is a significant explanatory variable in volatility persistence, (b) whether the type of media the information flow is carried in impacts the volatility-information relation, (c) whether information backlog is incorporated into volatility when market re-open, and (d) whether there is a lag in the way information is incorporated into volatility (including by media type). Results show conclusive evidence of a strong relation between information and volatility. Further, the media types which deliver the most current information, i.e. Wire-Feeds, tend to have the largest impact on returns volatility. The evidence on the role of backlog and information lags in volatility is mixed, with significance only in the S&P 500 for Backlog, and only in S&P 500 and DJIA for lags. Essay 2 further examines the stock market volatility and public information relation in light of daily market anomalies. Building on the literature on the Day of Week Effect, this essay investigates whether a Day of the Week effect is present in US and UK indices both before and during the latest financial crisis. Augmented GARCH models are constructed to test for a Day of the Week Effect in either returns and/or volatility, and are further explored in light of the information arrival proxy created in Essay 1. Results show weak evidence of Day of the Week effect in the data, except for a Friday Effect in the Russell 2000, both before and during the crisis; which confirm that small size stocks are more likely to exhibit Day of the Week effects, as suggested by previous uses of equal-weighted indices. Through the interaction variables, results show that information flow can satisfactorily explain Day of the Week effects. Essay 3 investigates the relation between proxies for investor sentiment and stock market crises and recoveries on international indices. Using an Early-Warning-System (EWS) model, the essay examines whether investor sentiment is a useful predictor for the occurrence of stock market crises and early signs of recovery. Three alternative proxies are used to measure investor sentiment, including previously cited measures of stock market riskiness, investors’ risk aversion and investors’ optimism about stock markets. The results show that investor sentiment is overall a significant predictor of the occurrence of crises within a one year period, and that the addition of sentiment into early warning signal models of stock market crises can improve the predictive performance of the model (increases in investor sentiment increase the probability of occurrence of a crisis, which is in line with previous contributions finding a negative lead-lag relation between sentiment and stock returns). The extension of the model to early signs of recoveries also shows that sentiment is a reliable predictor. The measure of stock market riskiness (Baker and Wurgler, 2006) is found to be a better predictor than the Volatility Index (VIX) and the Put-to-Call Ratio (PCR). The cross-country comparison results confirms the literature findings that the link between sentiment and stock market returns varies across indices and cultures, as the predictive power of the variable appears strongest in the French and U.S. indices.

In recent years, the economies of Eastern Europe have experienced a complete breakdown of their political and economic structures in the transition process. These changes have led to the emergence of a financial sector, the infrastructure of which has had to be established practically from scratch. In Poland, the most important non-bank financial sector, the Warsaw Stock Exchange (WSE), has played an essential role in the privatisation process and in providing an alternative source of finance and investment amongst firms and households. In this thesis, we provide an econometric analysis of asset returns on the WSE. On the WSE, there exists a one-period censoring of asset returns moving beyond a pre-specified range introduced to limit speculative behaviour and volatility on the market. Our principal aim has been to incorporate such a feature into any analyses undertaken. Considering predictability, in an explicit intertemporal model of an investor's effective demand for a single asset facing a binding quantity constraint, we show that the market may not be predictable and return predictability on such constrained markets is non-trivial. Proposing an approach to model the predictability of returns, we find evidence of predictability of six main returns series on the WSE. Considering the volatility of asset returns, we investigate whether the finding for developed stock markets that negative shocks entering the market lead to a larger return volatility than positive shocks of a similar magnitude also applies to two emerging Eastern European markets. Concentrating on the WSE and the Budapest Stock Exchange, we therefore also examine whether the findings differ depending on the exchanges' institutional microstructures. We propose an approach to model the conditional volatility of returns on a quantity constrained market such as the WSE and find no evidence of an asymmetric impact of news on the volatility of returns on either exchange.

The purpose of this thesis is to contribute to theoretical knowledge and help investors, fund administrators, financial regulators and database vendors. Its chapters examine hedge fund performance attribution and fund persistence under changing market conditions, and issues of hedge fund index engineering, using a rigorously constructed unified database (U.S. dataset, from 1990 to 2014). The core of my modelling approach is a custom piece-wise parsimonious multifactor model with predefined and non-defined structural breaks, flexible enough to capture differences in asset and portfolio allocations. This is implemented on a strategy, fundamental, and a mixed level. Concerning funds’ persistence, I use several parametric and non-parametric techniques whereas I develop a framework with mixed trading strategies for investors’ conditional high returns. I examine the classification problem of hedge funds by implementing several classification techniques used by database vendors, on the same dataset. The findings are robust, showing that during stressful market conditions most hedge fund strategies do not provide significant alphas to investors as fund managers are more concerned about minimizing their systematic risk and there is a switch from equity to commodity asset classes. Directional strategies have more common exposures than non-directional strategies under all market conditions. Falling stock markets are harsher than recessions for hedge funds. Moreover, during stressful conditions, small funds suffer more than large funds, young funds outperform old ones and funds that do not impose restrictions (and survive) outperform funds with no lockups. There are cases where funds can deliver significant negative alpha to investors conditional on stressful market conditions. In general, stressful market conditions have a negative impact on all types of funds’ persistence whereas my zero investment “synthetic” trading strategy can bring conditional high returns to investors. Furthermore, I found that the differences between index vendors are mainly due to the use of different selection criteria and different datasets.