Trading efficiency of commodity trading advisors using Data Envelopment Analysis
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Practical applications Investors can use Data Envelopment Analysis (DEA) as complementary performance appraisal technique to examine and rank the relative trading efficiency of commodity trading advisors (CTAs). Data Envelopment Analysis can offer added insight by observing which CTAs are best at optimising their inputs to produce the largest outputs. One of the benefits of using DEA is that it allows comparisons among CTAs without the use of external benchmarks or indices. With this in mind, investors can monitor whether the CTAs they have selected for inclusion in their portfolio possess efficient trading skills. Abstract This paper investigates the trading efficiency of commodity trading advisors (CTAs) during the period January 1998–June 2004. The 90 largest CTAs are analysed using the basic Data Envelopment Analysis (DEA) model, followed by the cross-efficiency and super-efficiency models. A detailed efficiency analysis of CTAs is provided, and the results indicate that only a handful of CTAs are efficient in terms of minimising trading to attain the highest compounded return.
INTRODUCTION The argument in favour of diversifying a traditional portfolio with commodity
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trading advisors (CTAs) has regained ground since the collapse of the dot com bubble in March 2000. The negative correlation and lower standard deviation versus various equity markets makes them ideal diversifying vehicles for traditional stock and bond portfolios. While stocks and bonds are considered a traditional asset class for investment portfolios, they do not achieve optimal portfolio diversification.1 Including alternative investments, such as managed futures, in traditional portfolios will diversify, reduce overall risk and enhance portfolio returns.2 Considered as alternative investment vehicles, CTAs produce absolute returns by employing leverage, short selling, futures
Derivatives Use, Trading & Regulation V olume T welve Numbers One/Two 2006
Derivatives Use, Trading & Regulation, Vol. 12 No. 1/2, 2006, pp. 102–114 䉷 Palgrave Macmillan Ltd 1747–4426/06 $30.00
and options, etc. Typically, CTAs are classified as being either systematic or discretionary. Systematic traders use computerised mathematical models that produce buy and sell signals, whereas discretionary traders (non-systematic) use economic indicators or fundamental analysis to execute their trades. Commodity trading advisers use proprietary trading systems to create market positions in commodity, currency markets and financial futures in global futures markets. They can assume either long or short positions and invest in futures contracts to make leveraged bets on currencies, energy, bonds, interest rates, stock market indices as well as agricultural and consumer goods. Having an alternative performance measure such as Data Envelopment Analysis (DEA) is important, because it enables investors potentially to pinpoint the reasons behind a CTA’s poor trading efficiency. For institutional investors considering using CTAs, it is critical that a measure provide not only a
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