Investing in emerging markets becomes more and more attractive for investors because of the rapid underlying economic growth, the improved liquidity and the still low correlation with mature capital markets. In cooperation with the systematic equity team of Allianz Global Investors, the thesis explores the viability of adopting a systematic style approach, which has been very successful for developed capital markets, to emerging markets. The main hurdle to investing in emerging markets is the incomplete financial data. The thesis uses the Markov Chain Multiple Imputation method (MCMI), which originated in physics as a tool for exploring equilibrium distributions of interacting molecules, to fill in the missing values. After filling in the data holes, the thesis defines an emerging market benchmark consisting of approximately 500 companies with the highest market capitalization. Subsequently, six investment styles value, growth, momentum, earnings revision, profitability and cash flow stability are back-tested for the observation time period between 1995 and 2006, based on the self-constructed benchmark. The beta, alpha, average outperformance, tracking error and information ratio of each of the six investment styles are analyzed, both before transaction cost and after transaction cost. The performance of each of the six investment styles in different economic scenario is scrutinized. At the end, the possibility of building up a strategic style mix is discussed.     «

Investing in emerging markets becomes more and more attractive for investors because of the rapid underlying economic growth, the improved liquidity and the still low correlation with mature capital markets. In cooperation with the systematic equity team of Allianz Global Investors, the thesis explores the viability of adopting a systematic style approach, which has been very successful for developed capital markets, to emerging markets. The main hurdle to investing in emerging markets is the in...     »