Smart Beta - index weighting

Abstract: This study is a thesis ending a 120 credit masters program in Mathematics with specialization Financial Mathematics and Mathematical Statistics at the Royal Institute of Technology (KTH). The subject of Smart beta is defined and studied in an index fund context. The portfolio weighting schemes tested are: equally weighting, maximum Sharpe ratio, maximum diversification, and fundamental weighting using P/E-ratios. The outcome of the strategies is measured in performance (accumulated return), risk, and cost of trading, along with measures of the proportions of different assets in the portfolio. The thesis goes through the steps of collecting, ordering, and ”cleaning” the data used in the process. A brief explanation of historical simulation used in estimation of stochastic variables such as expected return and covariance matrices is included, as well as analysis on the data’s distribution. The process of optimization and how rules for being UCITS compliant forms optimization programs with constraints is described. The results indicate that all, but the most diversified, portfolios tested outperform the market cap weighted portfolio. In all cases, the trading volumes and the market impact is increased, in comparison with the cap weighted portfolio. The Sharpe ratio maximizer yields a high level of return, while keeping the risk low. The fundamentally weighted portfolio performs best, but with higher risk. A combination of the two finds the portfolio with highest return and lowest risk.