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This study investigates the reported operating performance of Chinese IPOs (Initial Public Offerings) before and after the IPO. It shows that Chinese IPOs report a significant decline in operating performance relative to the pre-IPO level, in terms of Return on Assets (ROA) and Operating Cashflow on Assets (CFO). Importantly, the study explores the explanations for the operating performance from before to after the IPO. It starts with testing the 'Managerial Ownership Dispersion Hypothesis'. However, there is no evidence that the decline in reported operating performance of Chinese IPO firms is associated with the change in managerial ownership from before to after the IPO. Managers in Chinese listed firms hold a very small percentage of ownership, which is too small to make any effective impact on corporate operating performance, and there is no significant decrease In the post-IPO managerial ownership relative to the pre-IPO managerial ownership. So, in this sense, Chinese IPO data cannot provide empirical evidence to support the Managerial Ownership Dispersion Hypothesis, which is conjectured by Jensen and Meckling (1976). This study also tests the 'Earnings Management Hypothesis' to explain the operating performance decline of Chinese IPOs from before to after the IPO. There is significant evidence that Chinese IPO firms manipulate accruals so as to boost pre-IPO reported earnings. Besides accruals manipulation, this study further investigates related party transactions (RPTs) around the IPO. The findings show that related party transactions between IPO firms and controlling shareholders have significant effects on reported operating performance of IPO firms. The abnormally high reported operating performance in the pre-IPO period is positively associated with the size of operating RPTs (non-loan) between controlling shareholders and IPO firms in the pre-IPO period. Evidently, controlling shareholders significantly structure artificial operating RPTs to boost revenues and/or profits of their IPO subsidiaries. However, in the post-IPO period, controlling shareholders discontinue these RPT-based manipulative practices, and begin to expropriate IPO subsidiaries by obtaining cash loans from IPO subsidiaries, primarily in return for profits and/or resources transferred into IPO subsidiaries in the pre-IPO period (Cheng et al., 2007). The post-IPO operating performance is negatively associated with the size of such loans by IPO firms to controlling shareholders in the post-IPO period.

This dissertation extends the literature on the efficacy of technical analysis in the direction of the `risk premium view' as an explanation for excess trading rule returns. First, we generally rely on the theoretical alternatives to the efficient market hypothesis which encourages possibilities for markets to be inefficient. We then investigate the link between the risk involved in trading rule strategies and the resulting excess returns. The empirical analysis is based mainly on a sample of stocks drawn from the London Stock Exchange, (LSE), portfolios constructed from three US markets; the New York Stock Exchange, (NYSE), the American Stock Exchange, (ASE), and the National Association of Securities Dealers Automated Quotation market, (NASDAQ). Data from ten small emerging markets of Africa is also used in empirical analyses. Focusing on documented evidence of differences in risk levels among several markets or market segments, the empirical analyses examined whether these risk differentials can explain excess trading rule profits as compensation for bearing risk. The empirical analyses find that, to a large extent, liquidity, book-to-market ratio, and institutional arrangements can explain the excess profits from technical analysis. These empirical analyses are carried out in chapters three, four and six. As part of the analysis, I conduct empirical tests to assess the appropriateness of some risk estimates for trading rules. Using recently developed techniques, the evidence in chapter five is consistent with the notion that certain risk estimates may not be appropriate for adjusting trading rule returns for risk.

There is an emerging consensus that the threat of global warming, as well as regulatory and market initiatives for the reduction of GHG-emissions, result in significant costs for companies today and in the future. The magnitude of these costs is unknown to investors and transforms climate change into a market-wide financial risk. An efficient stock market prices this risk and rewards investors with higher returns for assuming higher levels of systematic risk. The purpose of this thesis is to analyse the efficiency of stock markets with regard to climate change induced systematic risk. To that end, a Carhart 4 Factor Model extended for industry effects is applied to a sample of 433 European companies in the years 2005 to 2009. This research thus contributes to the understanding of the behaviour of stock prices towards the financial implications of climate change. Results indicate that the stock market was inefficient in pricing all six proxies for climate change induced systematic risk applied in this study, i.e. a company's affiliation to the European Emissions Trading Scheme or high carbon industries, the existence of disclosure of GHG-emissions, the completeness of such disclosures, the absolute level GHG-emissions and GHG-efficiency. Persistent economically and statistically significant arbitrage opportunities exist when trading on publicly available information concerning these proxies. In this evidenced state of market inefficiency, investors are not rewarded for assuming higher levels of climate change induced systematic risk, but instead can achieve abnormal risk-adjusted returns by exploiting the inefficiently priced positive effects of (complete) climate change disclosure and good corporate climate change performance in the short-term. In conclusion, the financial market did not fulfil its role to correctly allocate ownership of the economy's capital stock with regard to the risk induced by the financial implications of climate change during the time period analysed in this study.

Multiple solutions often exist in both non-cooperative and cooperative games. In this thesis we use game theoretical arguments and experiments to examine multiplicity in two different areas, namely uniform price auctions and weighted voting games. In the second chapter we develop a theoretical model of IPO auctions and show that when demand is discrete the tacit collusion equilibrium is obtained under a stricter condition than in the continuous format. There also exists a continuum of equilibria where investors with a higher expected valuation bid more aggressively, and as a result the market price increases with market value. The tacit collusion equilibrium is in fact an extreme case of this set. Bertrand competition, i.e, submitting a flat demand function, does not form an equilibrium in this game. We then test our equilibrium predictions and compare the performances of uniform price auctions with fixed price offerings using laboratory experiments. In the uniform treatment, there is no evidence that the tacit collusion equilibrium has been achieved. On the contrary, subjects with higher expected value bid more aggressively. Their behaviour is close to an equilibrium derived where all players participate. The resulting market prices are significantly higher than the market value of an investor with a low value signal. As a consequence, in our experiment uniform price auctions are superior to fixed price offerings in terms of revenue raising. In chapter four we move to weighted voting games. Power indices predict that enlargement of the voting body may affect the balance of power between the original members even if their number of votes and the decision rule remain constant. Some of the existing voters may actually gain, a phenomenon known as the paradox of new members. We test for this effect using laboratory experiments. We find empirical support for the paradox of new members. Our results also allow an assessment of the predictive performance of standard power indices.

This study examines the decision-usefulness of financial information produced in the external financial reports from the implementation of the International Accounting Standards (IAS) and the International Financial Reporting Standards (IFRS) to equity investors of the Amman Stock Exchange (ASE) in their investment decision-making process. The study employs mixed method research that uses quantitative and qualitative methods. The quantitative research methodology employs archival financial data from the ASE using inferential statistics to investigate the association between share market prices and a well known model, the residual earnings model, derived from (Preinreich 1938, Ohlson (1995) Feltham and Olson (1995)). Data is collected from companies listed on the ASE for the period before implementation of the IAS/IFRS, 1980-1989, and for the period after implementation, 1991-2009. In general, the results indicate a statistical association between share market prices and book value per share (BVPS) and residual earnings per share (REPS) with the BVPS robust to share market prices. The second quantitative method employs questionnaires administered to individual and institutional equity investors of the ASE. Key findings indicate that equity investors believe the implementation of the IAS/IFRS produces decision-useful financial information, that the accounting information has the useful qualitative characteristics proposed by the International Accounting Standards Board and that the price-to-book ratio, the dividend discount model and the price-earnings multiple are very useful models as inputs into their investment decision-making process. Semi-structured interviews were conducted to accounting, auditing and ASE experts in Jordan. Prevalent findings indicate that developments within the ASE and accounting profession have influenced the decision-usefulness of financial information. Few believed that Jordan should develop its own accounting standards. This research contributes to knowledge, being the first comprehensive study that employs a mixed method research using archival financial data for a 29-year study period from the ASE and primary data to evaluate the decision-usefulness of financial information produced from implementing the IAS/IFRS. Furthermore, this research fills a gap in the literature by examining the period before IAS/IFRS implementation and the period after implementation in Jordan to determine if IAS/IFRS implementation resulted in decision-useful financial information. The main implication of this research is that reported financial information has greater decision-usefulness after the implementation of the IAS/IFRS than before, implying positive effects of accounting standard-setting in an emerging economy.

Market making is central to the study of market microstructure. Market makers stand ready to provide liquidity, market stability and price discovery, issues of great importance to regulators, practitioners and academics. This thesis contributes to the literature by studying four topical issues related to market making. The thesis consists of four essays. In the first essay we develop a simple multi-period model of market making for a monopolistic stock market maker. The market maker tries to solve simultaneously the problems of managing his inventory and trading with informed traders. He uses a Kalman filter to update his estimates of the unknown market prices through his noisy order flow observation. We analytically characterize the optimal bid and ask prices and find that they depend on the beginning inventory, the estimated price, and the market maker's prior estimation error of the price process for each time period. We obtain desirable numerical results by using properly chosen parameters. The extensions to the continuous time and a competitive market making environment are also discussed. The second essay extends the model in the first essay to consider the market making of multiple stocks. The market maker still does not know the true prices but is assumed to know the return covariance structure of these stocks. When the market maker considers the correlated order flow information, his knowledge of the return covariance improves his estimation of the unknown price processes, resulting in higher cumulative profits and lower risks of the profits. The third essay analyzes the effect of option market makers' hedging on the informed trading strategy and the subsequent changes in the costs of liquidity provision in both stock and option markets. In a sequential trading framework, an option market maker uses the stock market to hedge his option position. His hedging trade affects the way that informed traders submit their orders in both the stock and the option market, which in turn changes the informed trading pressure faced by the market makers in each market. Furthermore, information in the option trading is passed to the stock market through the hedging trade. Both stock and option spreads are wider with option market maker's hedging. The increase in the spreads is more significant when the option market maker hedges in the underlying market than when it hedges with different options. The fourth essay provides a model of bookmaking in a horse race betting market. The bookmaker observes the noisy public betting flow and faces the risk of trading with possible informed traders, as well as the risk of his unbalanced liability exposures. Even the noisy demand can unbalance the bookmaker's book. In our model, the bookmaker revises his odds to mitigate the risk. Allowing the bookmaker to set odds over several rounds of betting gives a clear view of the bookmaker's price setting strategy and its impact on the public betting flow over time. The study of horse race bookmaking provides useful insights into the market making of state contingent claims such as options.

This thesis consists of three research topics, which together study the related topics of volatility jumps, modeling volatility and forecasting Value-at-­Risk (VaR). The first topic focuses on volatility jumps based on two recently developed jumps detection methods and empirically studied six markets and the distributional features, size and intensity of jumps and cojumps. The results indicate that foreign exchange markets have higher jump intensities, while equity markets have a larger jump size. I find that index and stock markets have more interdependent cojumps across markets. I also find two recently proposed jump detection methods deliver contradictory results of jump and cojump properties. The jump detection technique based on realized outlyingness weighted variation (ROWV) delivers higher jump intensities in foreign exchange markets, whereas the bi-­power variation (BV) method produces higher jump intensities in equity markets. Moreover, jumps under the ROWV method display more serial correlations than the BV method. The ROWV method detects more cojumps and higher cojumps intensities than the BV method does, particularly in foreign exchange markets. In the second topic, the Model Confidence Set test (MCS) is used. MCS selects superior models by power in forecasting ability. The candidate models set included 9 GARCH type models and 8 realized volatility models. The dataset is based on six markets spanning more than 10 years, avoiding the so-called data snooping problem. The dataset is extended by including recent financial crisis periods. The advantage of the MCS test is that it can compare models in a group, not only in a pair. Two loss functions that are robust to noise in volatility proxy were also implemented and the empirical results indicated that the traditional GARCH models were outperformed by realized volatility models when using intraday data. The MCS test based on MSE selected asymmetric ARFIMA models and the HAR mode as the most predictive, while the asymmetric QLike loss function revealed the leveraged HAR and leveraged HAR-­CJ model based on bi-­power variation as the highest performers. Moreover, results from the subsamples indicate that the asymmetric ARFIMA model performs best over turbulent periods. The third topic focuses on evaluating a broad band of VaR forecasts. Different VaR models were compared across six markets, five volatility models, four distributions and 8 quantiles, resulting in 960 specifications. The MCS test based on regulatory favored asymmetric loss function was applied and the empirical results indicate that the proposed asymmetric ARFIMA and leveraged HAR models, coupled with generalized extreme value distribution (GEV) or generalized Pareto distribution (GPD), have the superior predictive ability on both long and short positions. The filtered extreme value methods were found to handle not only extreme quantiles but also regular ones. The analysis conducted in this thesis is intended to aid risk management, and subsequently reduce the probability of financial distress in the sector.

Renneboog et al (2008) argue that it remains to be seen whether corporate social responsibility (CSR) can be priced. In light of this, this thesis tests the performance and market valuation of CSR indicators by using a comprehensive set of KLD indicators. Chapter Three of this thesis examines the effect of CSR on financial performance by incorporating CSR into the investment process. As no clear break point is found for the normalised KLD score, the net KLD score is used as an alternative portfolio metric. In addition, most KLD indicators are found to have insignificant alphas for the high-scoring, low-scoring, and long-short portfolios—meaning that investors do not earn abnormal returns through a long-short strategy. Moreover, insignificant alphas are recorded for most of the indicators under the best-in-class approach—meaning that the application of industry classification does not affect results. Finally, both the conditional Ferson and Schadt (1996) model and conditional three-factor model are used as robustness checks, with most indicators having insignificant alphas for these conditional models. As such, the results imply that there is neither outperformance nor underperformance when using portfolios formed with CSR scores; however, there are significant differences in factor loadings between high-scoring and low-scoring CSR portfolios. Chapter Four uses a framework consistent with the Peasnell (1982) and Ohlson (1995) model to examine whether CSR is reflected in share prices. The CSR indicator is treated as the “other information” variable, and the association between CSR and market price is estimated by controlling for book value of equity, net income and dividends. Although the market is found to value different KLD indicators differently, most of the indicators are found to have positive impact on market value (except for corporate governance and human rights). R&D and advertising expenditure are both added to the valuation model for robustness checking purposes. Some of the CSR indicators—and especially for the case of environment—are not valued during the earlier stages, but become increasingly valued over time. The ten industries are also found to have varying effects on market valuation. In summary, high-scoring CSR firms display higher valuations than low-scoring CSR firms, and thus it can be concluded that a socially responsible agenda does not conflict with maximising shareholder value. Since most of the CSR indicators in Chapter Four lead to positive market price valuations, Chapter Five aims to disaggregate the value effect into the separate components of ROE ratio, the implied cost of capital (ICC) and growth rate. Three different methodologies are used to test the relationship between CSR, ICC and the long-run growth rate. The relationship between CSR and growth rate is positive with all of the methodologies. However, the different methodologies return differing results for the relationship between CSR and ICC, which may be due to the different assumptions made by each approach. Furthermore, it suggests that long-run growth rate differences in general may be more important than ICC differences. Finally, most KLD indicators are found to have significantly higher P/V and ROE1 ratios for the high-scoring CSR portfolios than for the low-scoring CSR portfolios.

This research examines the cross-section of expected returns in the UK stock market for the period January 1969-December 2001, with particular reference to the role of risk adjustments and the pricing of characteristic factors. This study has three empirical parts. This first part of the empirical study is concerned with the testing for cross-sectional relationships between expected returns and firm size, book-to-market equity ratio and beta. A methodology similar to that of Fama and French (1992) is employed for this purpose. Most of the research relating the behavior of stock returns to variables such as beta, size and book-to-market equity ratio has been done for the US markets, but there has been limited research relating to the UK markets. In order to further fill the gap, this study provides new evidence by using a more up to date dataset for the UK stock market. In addition, this study further tests the relationship by employing methods not previously employed for the UK market. The cross sectional relationships are tested using robust regressions. Because of seasonal patterns and small-firm effects detected in prior cross-sectional studies, this study also explores cross-section relations for different months of the year and different size cohorts. In the second part, this study analyses models that explain the time series of stock returns using portfolios that mimic the characteristics found to be priced in the first stage cross-section analysis. It was ascertained whether these characteristics proxy for sensitivity to risk factors in returns or whether the characteristics themselves explain the cross section of expected stock returns. This study also discriminates between these two explanations by testing whether it is the time variation in expected risk premiums as measured by the characteristic factors or time variation in the risk loadings as measured by the risk factors arising from characteristic factors. In the third part, it was detennined whether the characteristic factors found to priced in the first and second stage have any explanatory power relative to the loadings on the factors through the different asset pricing risk models. Throughout the study, other issues in both the cross-section and time-series analysis, such as data-snooping biases and residual analysis are also addressed. From all three parts, there is strong evidence that the book-to-market equity ratio is a very important detenninant of the cross-sectional variation in average stock returns while there is hardly any role for beta or size effects in explaining returns. However, the book-to-market effect is only visible for portfolios of small firms and for the month of April. This study further finds some evidence supporting a rational asset-pricing risk model as a possible explanation of book-to-market and size premiums and some evidence supporting book-to-market and size characteristics as a possible explanation. But the analysis of risk-adjusted returns through different factor models suggests that, the priced firm characteristics like book-to-market equity and size are not proxying for loadings on omitted factors that are priced.