Business and economic cycles have played a major factor in economies and people lives for centuries; indeed, it could be argued that the economic crises and economic good times affect all people’s wellbeing. As financial markets have developed in modern economies, researchers have observed that market cycles tend to be leading indicators of business cycles. While there is a long history of academic research into business cycles, academic research into how market states differentially influence security returns is a more recent phenomenon. The aim of this thesis is to explore not only new methods but also to create innovative schemes that enable the examination of how market states influence security returns in new and significant ways. The encompassing theme is the interplay between stock market anomalies and market states. The resulting empirical research in the thesis involves three separate but related empirical studies. The first study of the thesis examines whether market states (defined simply by past market performance) are able to provide information about the future performances of individual industries. In other words, can market states predict future industry returns? Specifically, I investigate whether an industry’s past relative performance in the same market state as the current one predicts the industry’s future performance. The findings show that market states can be used to construct profitable dynamic industry rotation strategies. Moreover, in support of market practitioners’ preferences for specific industries in different states of the market, certain industries are shown to have predictable returns in different market states.