Tracking an Index with Narrow Baskets : Efficiency, Costs and Tradeoffs Involved in Optimized Portfolios

Many trading, investing and structured product applications require narrow, liquid basket that efficiently track the market. In this paper, we examine tracking efficiency and turnover of highly liquid baskets, which track the investable European stock market as represented by the S&P Europe 350 index. The paper suggests a modification of standard stepwise regression based optimization. Our modified selection process vastly reduces turnover in the tracking baskets with very little sacrifice in tracking efficiency. We compare the results of using stepwise regression with that of a naive sampling strategy which simply picks the largest liquid stocks with respect to capitalization. Our empirical results demonstrate that for narrow baskets (up to 125 stocks), the optimization algorithm generates portfolios with far better tracking performance than the naive strategy, which is in part due to improved sector matching. For larger portfolios (i.e. for more than 125 stocks), the benefits of optimization vanish