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This thesis systematically analyses the introduction of Mortgage Backed Securitisation (MBS) in China from the perspective of Douglass North's institutional change theory. Based on a holistic and critical review of his work, this thesis establishes a systematic normative framework of Northian institutional change theory. This consists of the fundamental assumption of procedural rationality, the core concept of the institution, and three theoretical blocks which explain the source, path dependence and adaptive efficiency of institutional change. From this, a set of specific research protocols is devised to operationalise North's institutional change theory for the study of MBS in China. The empirical work is divided between macro and micro levels. At the macro level, the introduction of MBS in China is deciphered from a national and system-wide viewpoint, utilising archival analysis with supplementary survey research. Three main findings emerge. First, the introduction of MBS in China was driven by a mixture of external and internal factors. The external factors included the emergence of private residential property markets, the associated rapid expansion of the mortgage market, and the technological innovations in major domestic residential property finance markets. The main internal factors concerned the attitudes of Chinese financial and property authorities toward further reforms in the Chinese banking and property sectors. Second, the creation of the institutional infrastructure for MBS in China was narrowed by an existing set of institutional constraints that were shaped in the past. These affected the choice of special purpose vehicle for securitisation, the ways of securing housing as reliable collateral for loans, the scope for implementing credit enhancement and the methods for transacting MBSs. This path dependence has three dimensions: the historical sequence of events, the stake of interests groups and their power, and the mental constructs of policy makers and market actors. Third, the different levels of the existing institutional matrix exhibited differing degrees of response to the creation of the institutional infrastructure for MBSs. This reveals the contingent nature of adaptive efficiency and certain frictions in the change process. At the micro level, the investigation focuses on the Construction Bank of China (CBC) in launching its Jianyuan 2005-1 MBSs. Case study research shows how the establishment of a new institutional infrastructure created legal and regulatory opportunities for Chinese banks to construct MBSs. CBC utilised those institutional opportunities to introduce the first MBS in China. The pioneering CBC can be expected to have an enduring influence on the banks coming after them in terms of the transaction structure, credit quality of mortgage pool, method of credit enhancement, information disclosure mechanism and approach of MBSs pricing. An epilogue to this thesis briefly considers the crisis originating in US sub-prime MBSs, which emerged during the final stages of this research. Reviewing those events from Northian institutional perspective suggests that a series of formal and informal institutional arrangements for originating, rating and trading sub-prime MBSs (and their derivatives) has caused the systematic collapse in the value of traded securities. The institutional arrangements were induced by a mixture of the increasing pressure of competition in mortgage lending market, the continuous expansion of the MBSs (and their derivatives) investment market, and the internal subjective mental constructs of the mortgage lenders, institutional investors, finance authorities and home buyers. Retracing history, a number of institutions formulated in the past intertemporally contributed to the introductions of the institutional arrangements. Looking at the Chinese MBS practice, it protects from similar institutional problems by focus on prime mortgage-backed securitisation. Nonetheless, China needs to learn from lessons of the sub-prime crisis by further tightening rules governing future MBSs.

The aim of this thesis is to evaluate the effectiveness of technical analytic indicators in the fixed income markets. Technical analysis is a widely used methodology by investors in the equity and foreign exchange markets, but the empirical evidence on the profltability of technical trading systems in the bond markets is sparse. Therefore, this thesis serves as a coherent and systematic examination of technical trading systems in the government bond futures and bond yield markets. We investigate three aspects of technical analysis. First, we evaluate the profitability of 7,991 technical trading systems in eight bond futures contracts. Our results provide mixed conclusions on the profitability these technical systems, since the results vary across different futures markets, even adjusting for data snooping effects and transaction costs. In addition, we find the profitability of the trading systems has declined in recent periods. Second, we examine the informativeness of technical chart patterns in the government benchmark bond yield and yield spread markets. We apply the nonparametric regression methodology, including the Nadaraya-Watson and local polynomial regression, to identify twelve chart patterns commonly taught by chartists. The empirical results show no incremental information are contained within these chart patterns that investors can systematically exploit to earn excess returns. Furthermore, we find that bond yield spreads are fundamentally different to price series such as equity prices or currencies. Lastly, we categorize and evaluate five type of price gaps in the financial markets for the first time. We apply our price gap categorisation to twenty-eight futures contracts. Our results support the Gap- Fill hypothesis and find that some price gaps may provide additional information to investors by exhibiting returns that are statistically different to the unconditional returns over a short period of time. ՝In conclusion, this thesis provides empirical evidence that broadly support the usage of technical analysis in the financial markets.

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This thesis is about interest rate modelling with applications in pricing and risk management of interest rate derivatives and portfolios. The first part of the thesis is developed within the random field framework suggested by Kennedy (1994). The framework is rich enough to be used for both pricing and risk management, but we believe its real value lies in the latter. Our main objective is to construct infinite-factor Gaussian field models that can fit the sample covariance matrices observed in the market. This task has not previously been addressed by the work on field methodology. We develop three methodologies for constructing strictly positive definite covariance functions, characterising infinite-factor Gaussian fields. We test all three constructions on the sample covariance and correlation matrices obtained from US and Japanese bond market data. The empirical and numerical tests suggest that these classes of field models present very satisfactory solutions to the posed problem. The models we develop make the random field methodology a much more practical tool. They allow calibration of field models to key market information, namely the covariation of the yields. The second part of the thesis deals with pricing kernel (potential) models ofthe term structure. These were first introduced by Constantinides (1992), but were subsequently overshadowed by the market models, which were developed by Miltersen et al. (1997), and Brace et al. (1997), and are very popular among the practitioners. Our objective is to construct a class of arbitrage-free term structure models that enjoy the same ease of calibration as the market models, but do not suffer from non-Markov evolution as is the case with the market models. We develop a class of models the within pricing kernel framework. I.e., we model the pricing kernel directly, and not a particular interest rate or a set of rates. The construction of the kernel is explicitly linked to the calibrating set of instruments. Thus, once the kernel is constructed it will price correctly the chosen set of instruments, and have a low-dimensional Markov structure. We test our model on yield, at-the-money cap, caplet implied volatility surface, and swaption data. We achieve a very good quality of fit.