Acknowledgements I would first like to acknowledge the contribution of my supervisors, Dr Fergal O’Brien and James Ryan, for their expertise, advice and encouragement throughout my research at the University of Limerick. I started doctoral research in February 2009. After part of the draft of the thesis was completed, I convened the Irish conference on accounting and finance, from May 6th–7th, 2010. I learnt a lot from many of the conference and workshop participants, particularly when I disagreed with them. I would also like to thank Dr David McAree for their excellent support to make the conference and workshop possible. Among those who helped read the draft, Defen Peng and Stephen Kinsella gave us detailed comments. I would like to thank them for their critiques and suggestions, which lead to many improvements. I have to thank the University of Limerick Kemmy Business School and later the School of Economics & Management at Nanchang University for their financial assistance over the years for fees, travel, data and publications. I also want to thank many individuals who have generously supported us during the entire process of research, including but not limited to: Linna Chen, Shengbao Hong, Peng Jiang, Rui Wang, Xin Zhang, Sarah Milne, Sean McKillen, Anthony Carroll, Maeve O’Sullivan, Saeed Alshahrani. Preface The interest in predicting stock returns is probably as old as the markets themselves. The study of return predictability, particularly that on time-varying investment opportunities, is however not that common and knowledge regarding trading strategies within the Chinese financial market is relatively scarce. Previous return predictability studies have not focused on economic gains in context of asset allocation nor attempted to consider the instability in model parameters when evaluating forecasting performance/making forecasts of equity returns. In the existing literature on the Chinese market, there has been little attempt to analyse return predictability in equity markets. It is in light of a noticeable deficiency in return predictability research within a Chinese context that the kernel of this book is concerned. Specifically, this book examines the statistical and the economic significance on the predictability of both equity market downturns and equity market returns in China while accounting for model instability. Conducting this research in different equity markets and comparing against each other provides a basis on which to address some of the knowledge deficit in this area. The objective of this book, therefore, questions the predictability of equity market performance in China. Specifically, it questions whether predictor variables, including those under macroeconomic, sentiment, and technical categories are able to predict and affect differences in the behaviour of domestic equity markets. The research approach is based on a quantitative approach using statistical tests well documented in the literature. A naturally deductive research process emerged as the methodological paradigm of choice in this instance. Primarily an empirical approach was selected and ultimately the study examined the return performance of a population of 3 equity market indices in China based on 43 predictor variables. This book therefore serves several markets. It is appropriate for academic researchers who are looking for Chinese equity data and methodologies to conduct empirical research on return predictability and trading strategies. It also helps policy-makers to better understand the functioning of different Chinese equity markets when making related policies. Practitioners involved in the Chinese equity markets will find the book useful as well.