ENHANCING REBALANCING GAINS THROUGH SYNTHETIC DIVERSIFICATION ON COMMODITIES

Abstract

Synthetic diversification is a new technique that allows investors to reap larger rebalancing gains using randomization. We show empirically on three commodity indexes that although synthetic diversification cannot be used alone to gain larger geometric returns, it can be used to reduce correlation to other asset classes, such as equities, and potentially increase returns in a larger portfolio of investments. Synthetic diversification is also analyzed in conjunction with additional investment strategies, such as principal component analysis and k-means clustering. These additional investment strategies yield promising results, especially when applied to the Continuous Commodity Index.