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April 01, 2005 at 02:00 AM
Last month, we examined some of the characteristic differences between global macro (GM) and managed futures programs offered by commodities trading advisors (CTAs): two directional-biased hedge fund strategies largely dependent on market trends for their returns (for a look at CTAs themselves, see page 82).
The discretionary nature of the global macro approach is evident in that GM managers generally take positions in anti-cipation of a trend. GM traders also tend to exit these positions prior to the trend’s tailing off. Conversely, CTA traders take positions in response to price trends that are established, and tend to exit only after the trend has played itself out. Mark Szycher of Weston Capital sums it up nicely: “Macro managers get to the big party early and go home early. CTAs get to the party late, party hard, and go home late.”
This different approach toward exploiting the same market movements results in considerable differences in the long- and short-term performance of the two strategies. A comparison (see chart at right) of the 10-year performance data of HFR’s Global Macro Index against the Barclay’s CTA Index shows that GM managers have exceeded the returns of their CTA counterparts by more than 50% annually over the past 10 years while exhibiting 10% less volatility and, therefore, more than twice the return per unit of risk.
Clearly, the willingness of the GM trader to exit a trend before its technical reversal contributes to the strategy’s lower standard deviation and implied dependency on directionality. Unlike CTAs, it is not uncharacteristic of GM traders to sit out a trend where there is too much macro uncertainty or when fundamentals or the trader’s market view conflicts with quantitative signals. Moreover, Global Macro is frequently implemented via non-directional relative value trading strategies, and often with a value bias.
The two strategies may play distinctively different roles in portfolios, since both the GM approach and CTAs exhibit unique risk and return characteristics yet are both effective diversifiers that render portfolios more efficient.
