This thesis is concerned with the predictability of equity market performance in China
while accounting for the possibility of model instability. 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 research is concerned. Specifically, this thesis examines the statistical and
the economic significance on the predictability of both equity market downturns and
equity market returns in China while allowing 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 research, 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 behavior 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.
The results show that Chinese equity markets tend not to be efficient, with investors
being able to trade on the basis of inflation-related information. They also show that
statistical significance does not necessarily lead to an economic value given that these
measure different elements of forecasting ability. As evidenced in this study, several
predictor variables with statistically significant forecasting ability do not generate
excess returns when used as the basis for market timing strategies. In addition, the
domestic equity markets, particularly the Shanghai and the Shenzhen markets, are
driven by different underlying dynamics. As with previous studies, the findings provide
evidence that model instability is an important source of investment risks, which may
significantly influence the degree of return predictability and consequently affect
investors’ long-term wealth. It is therefore essential to take into account the possibility
of model instability when making asset allocation decisions. Overall, the results
highlight that return predictability varies through time in Chinese equity markets.