Recent headlines focus on option-buying strategies and their extraordinary performance in March, usually leaving out their generally high long-term cost. The tail insurance strategies with the largest wins in crash months are likely ones that in good times lose all or most capital allocated to them, perhaps many times over.
Investors have a natural urge to protect their portfolios from sudden crashes like the one we’ve seen recently. We argue that they should instead focus on bad outcomes that unfold over longer periods, as those tend to be more detrimental to the long-term goal of wealth accumulation.
We show that options-based hedging can be effective over shorter periods but tends to weaken over time. In contrast, risk-mitigating and diversifying strategies such as defensive equities, risk parity, alternative risk premia, and trend-following have more consistently added value over the horizons that matter most — as well as on average. This latter point suggests a crucial advantage for these strategies: that unlike options-based hedging, it’s never “too late” to consider diversifying into them.
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We thank Nick McQuinn, Ashwin Thapar and Dan Villalon for their work on this paper. We also thank Gregor Andrade, Matt Chilewich, Jeff Dunn, Jeremy Getson, Antti Ilmanen, Pete Hecht, Kelvin Lee, Thom Maloney, Toby Moskowitz, and Harsha Tummala for their helpful comments, and Rachel Lee, Sarah Schroeder, Nitin Krishna, and Derek Jansma for their excellent research assistance.
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Hypothetical performance results (e.g., quantitative backtests) have many inherent limitations, some of which, but not all, are described herein. No representation is being made that any fund or account will or is likely to achieve profits or losses similar to those shown herein. In fact, there are frequently sharp differences between hypothetical performance results and the actual results subsequently realized by any particular trading program. One of the limitations of hypothetical performance 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. For example, the ability to withstand losses or to adhere to a particular trading program in spite of trading losses are material points that can adversely affect actual trading results. The hypothetical performance results contained herein represent the application of the quantitative models as currently in effect on the date first written above and there can be no assurance that the models will remain the same in the future or that an application of the current models in the future will produce similar results because the relevant market and economic conditions that prevailed during the hypothetical performance period will not necessarily recur. 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, all of which can adversely affect actual trading results. Discounting factors may be applied to reduce suspected anomalies. This backtest’s return, for this period, may vary depending on the date it is run. Hypothetical performance results are presented for illustrative purposes only. In addition, our transaction cost assumptions utilized in backtests, where noted, are based on AQR Capital Management, LLC’s, (“AQR”)’s historical realized transaction costs and market data. Certain of the assumptions have been made for modeling purposes and are unlikely to be realized. No representation or warranty is made as to the reasonableness of the assumptions made or that all assumptions used in achieving the returns have been stated or fully considered. Changes in the assumptions may have a material impact on the hypothetical returns presented. Actual advisory fees for products offering this strategy may vary.
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