The Ph.D. thesis, called Testing for Non-linearity and Asymmetry in Time Series, focuses on various issues related to testing for non-linearity and marginal asymmetry of economic time series. This is an important issue since testing for non-linearity and/or asymmetry represents an early, yet crucial, step in the whole process of time series modelling. A mistake in this preliminary step may lead to model misspecification, and, subsequently, to a sequence of related issues throughout all the modelling steps (i.e. identification, estimation, and forecasting). As a result, this type of mistakes is very likely to result in wrong business or economic policy decisions. The thesis is divided into six chapters. The first chapter explains the motivation for the thesis. The second chapter, called Robustness of the Power of Non-linearity Tests, examines the statistical properties of the selected univariate non-linearity tests under different conditions. In particular, special attention is paid to the robustness of the power properties of the tests against moment condition failure of innovations, asymmetry of innovations, and the parameter configuration of data generating processes. Since analytical results are available only for a very limited number of the test statistics, an extensive Monte Carlo approach is implemented instead. The Monte Carlo results reveal that the power of the selected non-linearity tests is statistically significantly inflated under asymmetry of innovations and moment condition failure. In the third chapter, called Testing for Non-linearity Using a Modified Q Test, a new version of the portmanteau Q test, based on auto- and cross-correlations, is developed. The main task of this chapter is to propose a new type of the Q test in order to bypass some of the shortcomings of the McLeod and Li Q test discovered in Chapter 2. Our results, based on extensive Monte Carlo experiments, suggest the proposed Q test significantly improves the power against some non-linear time series models (e.g. threshold autoregressive and moving average models) and is capable to detect some interesting non-linear processes (e.g. non-linear moving average models), for which the standard Mcleod and Li Q test completely fails. In the fourth chapter, called Testing for Marginal Asymmetry in Time Series, a modified test for symmetry of the marginal law of weakly dependent processes is proposed. The test statistic is based on sample quantiles. It is shown that the test has an intuitive interpretation, it is easy and fast to calculate, it it follows a standard limiting distribution, and much more importantly, it is robust against weak dependence of observations. Especially the last feature makes the test very attractive for the use in applied economics since it minimizes inferential errors due to the incorrect configuration of the test. The finite sample properties of the test are examined via Monte Carlo experiments. The results suggest that the quantile-based test of symmetry performs very well. In the fifth chapter, called Testing for Non-linearity in Multivariate Time Series, two new principal component-based multivariate non-linearity tests are considered. The main goal of this chapter is to modify two well known multivariate test statistics which suffer from the curse of dimensionality. It is shown that a dimensionality problem can be easily bypassed by means of a principal component analysis. Our results, based on extensive Monte Carlo experiments, suggest that a principal component analysis reduces the dimensionality problem very efficiently without any systematic power distortion. The results also reveal that the BIC stopping rule performs best in determining the number of components for the selected multivariate non-linearity tests. The last chapter summarizes the results of this thesis and discusses directions for further research.

This thesis explores the magnitude and the determinants of the return to the merger arbitrage strategy in the UK context. We perform empirical analysis of the three hypotheses namely the risk-based hypothesis, the limited arbitrage hypothesis and the arbitrageurs' role hypothesis. First, in the risk-based hypothesis, using a sample of 1105 UK cash and stock mergers from 1987 to 2007, we find that the strategy generates significant positive return in excess of the systematic risk adjustment benchmark. The result is robust to a range of methods to control for systematic risk. The finding is consistent with the existing evidence from other markets. As for the risk-return characteristics of the strategy, in contrast to the US evidence, we find little evidence supporting the non-linear pattern. This finding is in line with the restrictions on bidder's ability to abandon the bid imposed by UK Takeover Code. This finding, combined with the evidence in the US market (strong non-linearity) and the Australian market (no nonlinearity), demonstrates the impact of takeover regulation on the risk-return characteristics of the strategy. Second, in the limited arbitrage hypothesis, we test the impact of different types of risks, costs and constraints (other than systematic risk) on the arbitrage return. We find that transaction costs are one of the important drivers of the cross-sectional variation of the arbitrage return. The result is robust to 4 different proxies for transaction costs, that is, firm size, price level, dollar trading volume, and frequency of zero return days. Holding costs are found to be an important determinant of the return. Idiosyncratic risk, the most important type of holding costs, contributes significantly to the source of the arbitrage return. We find that short-sale constraints appear to be another important holding cost that the arbitrageurs concern about. The result about the impact of shortsale constraints is, however, still inconclusive due to the small sample size. We also test the agency-based model of limited arbitrage hypothesis proposed by Shleifer and . Vishny (1997) but find no supporting evidence. Third, in the arbitrageurs' role hypothesis, utilizing a manually collected dataset to identify arbitrageurs and their holding of target stocks, we examine how different roles that arbitrageurs play in the takeover process help explain the source of the return to the strategy. We find that arbitrage holding is significantly related to arbitrage return after a host of factors that can determine the bid outcome and the market's assessment of the bid outcome are controlled for. This finding shows that the arbitrageurs are better than the average investors in the market in picking better takeover bids, the investment in which yields higher risk-adjusted return. In contrast to the US evidence, arbitrage holding is found to be negatively related to bid premium and has no impact on the probability of bid success. The difference between this finding and the US evidence may be attributable to the much more stringent UK disclosure rule during the takeover period compared to the US counterpart. Overall, our study, while providing evidence broadly in support of significant return to the merger arbitrage strategy, also highlights the importance of recognizing the impact of the takeover regulation on such return.

No description available.

This thesis discusses the liberalisation and banking regulation and supervision policies in the large data set of countries. Chapter 1 provides the detailed overview of the three distinct essays. Chapter 2 examines the impact of capital account liberalisation and financial development on economic growth by utilizing the data of 71 developed and developing countries. The empirical evidence of this chapter indicates that capital account liberalisation and financial sector development play an important role in future economic growth. More specifically, in middle and lower income countries, capital account liberalisation and financial development also have a positive and significant relationship with economic growth; the effects of capital account liberalisation in these countries are much higher than in high income countries. Chapter 3 investigates the impact of financial liberalisation and banking regulation and supervision policies on net interest margins by using the Bank-scope database of more than 1300 individual banks in 76 countries. A dynamic two-step system GMM estimation technique provides the evidence, which indicates that financial reform, financial liberalisation and banking regulation and supervision lead to lower net interest margins. Specifically, interest rate controls and barriers to entry have become more important factors in reducing interest margins. Chapter 4 also uses the Bank-scope database of the banking sector of 76 developed and developing countries to explore the relationship between financial reform, financial liberalisation and the quality of banking regulation and supervision on financial fragility, by applying a dynamic two-step system GMM panel estimator. The finding of this chapter is that the financial vulnerability of the banking sector could be affected not only by bank-specific and macro-specific variables, but also by financial liberalisation and banking regulation and supervision policies. The results show that financial reform and financial liberalisation significantly enhance the likelihood of financial fragility, while strong banking regulation and supervision reduce it.

The three chapters of this thesis share the common theme of computational approaches to modeling financial markets. Chapter 1, “Market Ecologies: The Interaction and Survival of Technical Trading Strategies”, finds its place in the boundedly-rational heterogeneous agent literature. Market prices result from the interaction of fundamental and technical trading strategies. We show that the way in which traders process information is critical in determining the long-run profitability of individual strategies. More realistic auction settings— in which price information is incorporated into trading methods in “real time”—demand computationally demanding techniques. The main conclusion of the chapter is that contrarian technical traders inadvertently mimic the role of arbitrageurs in more realistic auction settings. Chapter 2, “Capital Allocation in a Delegated Trading Model”, develops a model of capital allocation that removes the need for full mean-variance optimization of the firm-level portfolio. The strategies explored within the artificial setting of Chapter 1 are used to test the model against empirical foreign exchange data. We observe that the proposed capital allocation scheme yields economically and statistically significant returns, even when traders choose rules without the benefit of hindsight. Chapter 3, “Portfolio Choice: The Costs and Benefits of Asymmetric Information”, continues the theme of artificial markets, with the auction process departing from the fictitious auctioneer of Chapter 1, toward a market making model in which risk-neutral dealers quote bid-ask spreads to compensate them for the losses incurred by trading with informed agents. We obtain the intriguing result that, in multiple markets, there is an “optimal” level of inside information. In individual markets, portfolio managers incur higher transaction costs as asymmetric information increases, but benefit from an externality at the portfolio level, as inside information aids price discovery.

No description available.

No description available.

No description available.

No description available.

No description available.