The Style Heat Map below offers a snapshot for the month on all categories of strategies. For the month of October the following summaries highlight five of the 10 style categories that we track.
Systematic Trend
Trend followers posted a negative October, with the clear underperforming sector being fixed income – both shorter-term rates and longer-term bond markets. After the Fed had signaled rate cuts mid-summer, and subsequently cut 50 bps in September, almost every systematic trend model went long (yields falling). The turnaround in the U.S. and European bond markets during October inflicted losses to most trend programs –overwhelming gains elsewhere. Currencies were a mixed bag, where a very strong US dollar strengthened vs. most G10 and emerging market currencies. Most longer-term systems have held long USD positions from mid-summer that (finally) started performing; shorter- and medium-term programs, in contrast, suffered setbacks as most went short the dollar back in September. Commodities were also mixed. Precious metals were positive as many systems were long gold and silver; the ag sector was mostly negative as programs had come into the month long soybeans, soymeal and corn as all three declined. The energy sector brought mixed results to the systems as the oil market spiked sharply then quickly sold off, basically negating any gains. In the equity index sector, returns for the shorter- to medium-range systems was flat to slightly positive, but slightly negative overall for longer-term systems.
Global Macro – Discretionary
Most of the discretionary macro programs we track, in the aggregate, performed poorly in October, largely the victim of the same culprit that dogged systematic CTAs: Fixed income. Many came into October clinging to the continued theme of rate easing by the U.S. Fed and most central banks. Fortunately, some managers de-levered their portfolios in anticipation of what was expected to be an extremely close US presidential election, thereby avoiding the setbacks inflicted by the bond reversal. Long precious metals, primarily gold, on the other hand was a popular holding for the macro crowd, and positive performer especially considering the uncertainty of the election. Currencies were mixed, as those programs that were long fixed income also tended to be short the US dollar (which becomes less attractive as yields fall) and were punished as the USD strengthened in October. Equities did not appear to impact the macro managers’ performance much, as there was little net movement in global indices. Commodities were mixed and only marginally impactful for most discretionary macro strategies.
Global Macro – Quantitative
In stark contrast to their systematic trend and discretionary macro brethren above, most quant macro programs we follow appeared to be positive in October. Model-driven programs based on econometric and fundamental inputs seemed to outperform price-based (technical) programs – most notably in currencies. Most programs we follow were short a select set of G10 currencies against the USD, and reaped the gains. Long precious metals (silver, gold) was a common winner, as was short natural gas. We were most surprised by the predominance of short interest rates (yields rising) positioning by the quant crowd. This was strong performer amidst the reversal in yields – and a reminder how model-driven macro programs can often be nimble enough to pick up on changing environment. In equities, the best performers came into the month with long VIX exposures – during a month when the VIX index rallied over 20%.
FX Specialists
FX programs performed well in October, with longer-term, fundamentally-based/econometric and systematic programs slightly outperforming shorter-term systematic price-based programs, although both were positive. The strengthening US dollar was obviously the big story in October, appreciating versus most G10 and emerging market currencies. The longer-term programs, after suffering in August and September from long dollar exposures, were able finally to capitalize on a strong DXY rally. Short-term programs, especially those that include gold/USD in their mix (yellow currency) did well as gold rallied another 3.5% to new all-time highs.
Commodity Specialists – Agricultural Markets
Grain specialists (e.g. soybeans, corn, wheat) performed well, while many traders in soft commodities (e.g. cocoa, coffee, sugar) faced a very difficult month. For the former, the setbacks suffered toward the end of September (due to overreaction to misleading headlines concerning Europe and China) appeared to be reversed as longer-term bearish fundamentals kicked in – and pulled prices back down. Many, if not most, grains programs had anticipated this and positioned their portfolios accordingly. The regained ground was achieved largely in the first half of the month while the second half was less lucrative. For softs specialists, it was somewhat the opposite story: Outsized gains in September, accompanied by outsized exposures, got chewed up in October as markets retreated and stops were hit.
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
