Measuring Commodity Hedge Funds Performance by Applying Data Envelopment Analysis, DEA

CTA, commodity trading advisers, or managed futures managers' trade in the commodity market. The hedge funds invest in commodity futures, currencies, bonds and shares. The portfolio is leveraged and the risk is quite high. Forward and futures contracts have similarities in terms that they involve two parties to exchange a commodity, a currency or a bond at a specified price in the future. The costs of carry that characterize these contracts are insurance, storage and interest costs. Measuring efficiency have been made using non-parametric mathematical linear programming approaches such as data envelopment analysis, DEA, that enable efficiencies for each firm in an industry to be estimated relative to a dominant set of efficient firms with similar characteristics. The overall degree of efficiency in terms of risk and return in the commodity trading funds sectors is assessed by applying data envelopment analysis, DEA. DEA estimates efficiency in firms with multiple inputs and outputs. In our case, we are testing one input and one output. We are testing a sample of 10 different commodity hedge funds. As an input we use the annual standard deviations as a measure of risk and as an output we use logarithmic monthly returns. We try to find which commodity hedge funds companies lies on the efficient frontier in terms of increasing return to scale, constant return to scale and decreasing return to scale