In this thesis I provide evidence related to the existence, or otherwise, of the accruals anomaly (Sloan, 1996) in the UK stock market. The accruals anomaly is one of the several anomalies relative to the efficient market hypothesis that have been reported in the accounting and finance literature, and that has received wide attention from researchers in order to better understand it and determine if a real anomaly exists.

This thesis analyses the response of aggregate and sectoral stock returns to monetary policy announcements and inflation in the United Kingdom. Given the unique monetary policy framework, the monetary policymaking process and inflation target of the United Kingdom are different from other countries in many aspects, investigating the UK case could add international evidence to the current literature. This thesis contains three main parts: (i) monetary policy and stock returns, examining the impact of monetary policy announcements on stock returns and stock market volatility under different monetary policy regimes, especially before and after the independence of the Bank of England in 1997; (ii) inflation and stock returns, investigating the issues whether common stocks are a hedge against inflation in short, medium and long-term and under different inflationary economies and regimes; (iii) corporate financing mix and inflation exposure, testing how corporate financing mix affects the exposure of common stocks to inflation. The results suggest that monetary policy announcements negatively affect stock returns and significantly impact stock market volatility. The responses of stock returns and stock market volatility vary before and after May 1997, when the Bank of England gained independence, which suggests that a change in the monetary policymaking process tends to affect the responses of stock markets. The research also uncovers the fact that the UK stock market fails to hedge against inflation in short and medium-term, but provides a good hedge against inflation in long-term. Different inflationary economies or regimes also affect the relationship between inflation and stock returns. In addition, this thesis finds support for the nominal contracting effect suggesting that firms with higher debtors gain while firms with higher creditors lose from higher-than-expected inflation. The empirical mixture of the results found in the relationship between inflation and stock returns is likely to be explained by the nominal contracting hypothesis.

This thesis examines the effects of reducing segmentation and commitment to increase the level of investor protection on expected return, risk, trading volume and the level of disclosure of cross-listed firms. Previous studies have mainly focused on foreign firms listed in the US and produced inconclusive evidence regarding the benefits of cross-listing. Also, the existing research failed to adequately explain the reason behind the drop in abnormal return (AR) reported in all cross-listing studies, and whether it is associated with the timing of cross-listing. In addition, the research failed to explain the choice of foreign listing between regulated (AMEX, NASDAQ, NYSE, and LSE) and unregulated exchanges (OTe and PORTAL). Moreover, the lack of empirical investigation of the relation between cross-listing and increasing the level of investor makes this research important. My results show a significant decline in share price after the cross-listing, evidenced by the drop in abnormal return (AR). I find that the drop in AR is related to firm performance, suggesting that managers cross-list in a period of good performance to take advantage of the overvaluation of share price. I also report no relation between cross-listing and the commitment to increase the level of in-vest or protection. The logit model suggests that firms with poor investor protection are more likely to cross-list on unregulated exchanges to avoid the costs associated with listing on regulated exchanges. My results also reveal that foreign firms from good investor protection environments are traded more, before and after cross-listing, than foreign firms from poor investor protection environments. This evidence suggests no relation between foreign trading and the level of investor protection in the firm's home market. In terms of increasing disclosure, the analysis shows that the level of disclosure does not increase after cross-listing, irrespective of the location of cross- 1 listing. The results are also consistent across foreign firms from civil and common law countries. When comparing between cross-listed and non-cross-listed firms, the analysis shows no significant statistical difference. The above results provide new thinking on cross-listing, especially in respect of the relation between the time of cross listing and firm performance. Moreover, the evidence casts doubt on previous results that favour the investor protection (bonding) hypothesis, and question its validity.

The long-term underperformance of initial public offerings (IPOs) is now a well established and generally accepted anomaly. The aim of this thesis is to extend previous studies and establish whether the previous results found in the literature are robust to extending the sample and using more advanced econometric tools.

One of the most controversial issues for long-term stock performance is whether the presence of anomalies is against the efficient market hypothesis. The methodologies to measure abnormal returns applied in the long-run event studies are questioned for their reliability and specification. This thesis compares three major methodologies via a simulation process based on the UK stock market over a period of 1982 to 2008 with investment horizons of one, three and five years. Specifically, the methodologies that are compared are the event-time methods based on models (Chapter 3), the event-time methods based on reference portfolios (Chapter 4), and the calendar-time methods (Chapter 5). Chapter 3 covers the event-time approach based on the following models which are used to estimate normal stock returns: the market-adjusted model, the market model, the capital asset pricing model, the Fama-French three-factor model and the Carhart four-factor model. The measurement of CARs yields misspecification with higher rejection rates of the null hypothesis of zero abnormal returns. Although the application of standard errors estimated from the test period improves the misspecification, CARs still yield misspecified test statistics. When using BHARs, well-specified results are achieved when applying the market-adjusted model, capital asset pricing model and Fama-French three-factor model over all investment horizons. It is important to note that the market model is severely misspecified with the highest rejection rates under both measurements. The empirical results from simulations of event-time methods based on reference portfolios in Chapter 4 indicate that the application of BHARs in conjunction with p-value from pseudoportfolios is appropriate for application in the context of long-run event studies. Furthermore, the control firm approach together with student t-test statistics is proved to yield well-specified test statistics in both random and non-random samples. Firms in reference portfolios and control firms are selected on the basis of size, BTM or both. However, in terms of power of test, these two approaches have the least power whereas the skewness-adjusted test and bootstrapped skewness-adjusted test have the highest power. It is worth noting that when the non-random samples are examined, the benchmark portfolio or control firm needs to share at least one characteristic with the event firm. The calendar-time approach is suggested in the literature to overcome potential issues with event-time approaches like overlapping returns and calendar month clustering. Chapter 5 suggests that both three-factor and four-factor models present significant overrejections of the null hypothesis of zero abnormal returns under an equally-weighted scheme. Even for stocks under a value-weighted scheme, the rejection rate for small firms shows overrejection. This indicates the small size effect is more prevalent in the UK stock market than in the US and the calendar-time approach cannot resolve this issue. Compared with the three-factor model, the four-factor model, despite its higher explanatory power, improves the results under a value-weighted scheme. The ordinary least squares technique in the regression produces the smallest rejection rates compared with weighted least squares, sandwich variance estimators and generalized weighted least squares. The mean monthly calendar time returns, combining the reference portfolios and calendar time, show similar results to the event-time approach based on reference portfolios. The weighting scheme plays an insignificant role in this approach. The empirical results suggest the following methods are appropriately applied to detect the long-term abnormal stock performance. When the event-time approach is applied based on models, although the measurement of BHARs together with the market-adjusted model, capital asset pricing model and Fama-French three-factor model generate well-specified results, the test statistics are not reliable because BHARs show severe positively skewed and leptokurtic distribution. Moreover, the reference portfolios in conjunction with p-value from pseudoportfolios and the control firm approach with student t test in the event-time approach are advocated although with lower power of test. When it comes to the calendar-time approach, the three-factor model under OLS together with sandwich variance estimators using the value-weighted scheme and the mean monthly calendar-time abnormal returns under equal weights are proved to be the most appropriate methods.