The Style Heat Map below offers a snapshot for the month on all categories of strategies. For the month of September the following summaries highlight five of the 10 style categories that we track.
Global Macro – Discretionary
The discretionary global macro programs we follow were generally positive in September, primarily by being long fixed income and rates, short the US dollar on a highly anticipated Fed rate cut (50bps on September 18) and long gold (as an alternative way of reflecting a weaker US dollar.) Outside of precious metals, only a few programs mentioned any meaningful exposures to commodities markets (e.g. energies, industrial metals or grains). These latter markets were more difficult to trade as the underlying macro drivers were less obvious than the aforementioned financial market themes (clearly announced intentions by central banks and the US Fed to ease interest rates).
Systematic Trend Programs
The returns of longer-term trend followers were unusually mixed in September, with a wide range between bottom and top performers. From observing the programs we follow, it seems the biggest determinant was the program’s weighting to commodities, which were clearly the worst performing sector. The three worst sub-sectors within commodities were grains (programs were short and suffered from rallies in corn and the soy complex), industrial metals (programs were short and suffered after China announced a large stimulus package), and energies (most programs were long and wrong in crude oil). Profits in the more successful programs largely came from the fixed income and equities markets, with minimal damage from commodities and currencies. Fixed income (bonds and rates) positions were generally positive (long exposure), while equity indices were a bit more mixed. FX was a non-factor due to all the deleveraging that occurred in August after the significant losses caused by the Japanese Yen rally.
Commodity Managers – Agricultural Specialists
Although most of the agricultural programs we track were generally negative on the month, the reason why this style bucket is green on the chart came almost entirely from managers focused on softs markets. In the softs, many managers performed extremely well in coffee (long), sugar (long), and cotton (long). Grains specialists, in contrast, were almost all negative. This was largely due to the news and sentiment driven environment – as opposed to the fundamentally driven environments experienced earlier this year. By this we mean that long-term fundamentals overwhelmingly point to lower prices in corn and soybeans, but short-term headlines and events, as well as short-covering from professional traders and money managers, moved sharply against fundamentally-based short positions (whether expressed via relative value spreads, options positioning, or just outright shorts). Livestock traders also generally did poorly for largely the same reason, holding short exposures to live and feeder cattle.
Commodity Managers – Metals & Energies Specialists
Like their agricultural trading brethren above, metals and energies traders faced a mixed bag in September. Metals traders generally outperformed energy-focused managers. The most profitable metals programs were positioned long both precious (gold, silver, platinum) and base metals (copper, zinc, aluminum), and were rewarded handsomely for it. When gold rallied to all-time highs silver rallied 9%, and base metals all spiked upwards after China announced its massive stimulus package late in the month. Energy traders faced more struggles. The fundamental discretionary programs in the energy sector appeared split between directional programs (most of whom were generally long crude oil and heating oil – both losing positions) and the more profitable relative value programs (particularly those focused more on natural gas). The +17% rally in natural gas (which accelerated later in the month) actually made matters a bit more difficult, not better, for many RV/spread strategies, as the spreads changed rapidly. Model-driven energy programs were mixed as well, with price-based systems (particularly those trading spreads) outperforming supply/demand driven models.
Currency Specialists
Following the sharp spike in currency market volatility (both historical and implied) back in early August (when Japanese central bank moves triggered a rapid unwinding of the Yen carry trade), the markets in September were more broadly rangebound and provided fewer opportunities. Not surprisingly, systematic FX programs, particularly short-term price-based ones, outperformed the longer-term discretionary fundamental (macro) managers and econometric quant programs – most of which were still digesting the events of August. The short-term programs did well to catch a weakening US dollar versus other G10 and commodity driven emerging currencies (Mexico, Brazil, S. Africa). Those programs that include gold (the “yellow currency”) fared well if they were long gold vs the USD.
Past performance is not necessarily indicative of future results. See notes at end of this document for details on the construction of the Hydra “baskets” and the benchmark used for each style class. Also note that some baskets may contain managers that have not yet reported by this date.
*=Less than 75% reported. **=Less than 75% reported and absence of a core manager’s return.
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Kettera Strategies
Footnotes:
For the “style classes” and “baskets” presented in this letter: The “style baskets” referenced above were created by Kettera for research purposes to track the category and are classifications drawn by Kettera Strategies in their review of programs on and for the Hydra Platform. The arrows represent the style basket’s overall performance for the month (e.g. the sideways arrow indicates that the basket was largely flat overall, a solid red down arrow indicates the basket (on average) was largely negative compared to most months, etc.). The “style basket” for a class is created from monthly returns (net of fees) of programs that are either: programs currently or formerly on Hydra; or under review with an expectation of being added to Hydra. The weighting of a program in a basket depends upon into which of these three groups the program falls. Style baskets are not investible products or index products being offered to investors. They are meant purely for analysis and comparison purposes. These also were not created to stimulate interest in any underlying or associated program. Nonetheless, as these research tools may be regarded to be “hypothetical” combinations of managers, hypothetical performance results have many inherent limitations, some of which are described below. No representation is being made that any product or account will achieve profits or losses similar to those shown. In fact, there are frequently sharp differences between hypothetical performance results and the actual results subsequently achieved by any particular trading program. One of the limitations of hypothetical results is that they are generally prepared with the benefit of hindsight. In addition, hypothetical trading does not involve financial risk, and no hypothetical trading record can completely account for the impact of financial risk in actual trading. There are numerous other factors related to the markets in general or to the implementation of any specific trading program which cannot be fully accounted for in the preparation of hypothetical performance results and all of which can adversely affect actual trading results.
Benchmark sources:
- Blend of Eurekahedge Macro Hedge Fund Index and BarclayHedge Global Macro Index
- The Eurekahedge Macro Index (same link as above)
- The Societe Generale Trend Index
- The Societe Generale Short-term Traders Index (same link as above)
- The BarclayHedge Currency Traders Index
- Blend of Bridge Alternatives Commodity Hedge Fund Index and BarclayHedge Discretionary Traders Index
- The BarclayHedge Agricultural Traders Index
- The Eurekahedge Commodity Hedge Fund Index:
- Blend of CBOE Eurekahedge Relative Value Volatility Hedge Fund Index and CBOE Eurekahedge Long Volatility Index:
- Blend of Eurekahedge Asset Weighted Multi Strategy Asset Weighted Index and BarclayHedge Multi Strategy Index
Indices and other financial benchmarks shown are provided for illustrative purposes only, are unmanaged, reflect reinvestment of income and dividends and do not reflect the impact of advisory fees. Index data is reported as of date of publication and may be a month-to-date estimate if all underlying components have not yet reported. The index providers may update their reported performance from time to time. Kettera disclaims any obligation to verify these numbers or to update or revise the performance numbers.
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The views expressed in this article are those of the author and do not necessarily reflect the views of AlphaWeek or its publisher, The Sortino Group
