Same Same But Different

Investors sometimes become concerned when they observe discrepancies in the performance of seemingly identical strategies with identical expected long-term performance.

In this article, which is a summary of a more comprehensive whitepaper (download here), we hope to alleviate these concerns by showing that short-term discrepancies will almost always arise when the same strategy is executed on different channels, like SMAs, UMAs, or mutual funds. Moreover, these discrepancies can be quite large in the short term without compromising the long-term expectations of the strategy.

For example, we offer AAA mandates using both futures and ETFs for a given volatility target. While they provide very similar underlying market exposures in the long term, over the short-term small differences in the underlying constituents of the ETFs versus futures, will produce short-term deviations.

Differences in trading costs and turnover preferences for each delivery channel also prompt us to execute AAA at different rebalance frequencies, and on different days of the week. Again, while the long-term returns for these mandates are statistically indistinguishable, performance over shorter horizons like a few months or years can be quite distinct due simply to how often and when these portfolios are rebalanced.

Consider two strategies that have precisely the same methodology, executed on the exact same investment universe. However they are executed with different rebalance frequencies between 1 and 20 days, and on different days of the month.

The strategies have returns that are statistically indistinguishable from one another over 25 years. How different could short-term performance really be if all that stood between them was the portfolio’s rebalancing frequency?

Perhaps surprisingly, the average difference between the best and worst strategy simulation was 7.2% over any given year. The difference was larger than 10.9% five percent of the time. Even when the strategies were tracking closely, we still observed a 4.2% dispersion between the best and worst performer. Figure 1 shows a few of the years where merely changing the rebalancing frequency led to large dispersions.

Figure 1: Performance of best and worst performing strategy permutations in years with the largest dispersion. Simulated results.

Source: ReSolve Asset Management. Each chart represents the growth of $1 for the worst and best performing strategy permutation each the calendar year. Simulated and hypothetical data. Past performance is no guarantee of future results.

The moral of the story is that investors have to either buy into the underlying process or not. Short-term performance is just noise. Investors need to trust (or not) that the fundamental drivers of the methodology (momentum/trend factors and diversification) are likely to prevail in the long-term, even in the face of random dispersion in the short-term.

Of course, this doesn’t just apply to AAA. It is axiomatic across any investment approach. The performance of the S&P500 would have been materially different from year-to-year if it added or removed companies at different times. How different would the index have been if the index committee had added Apple, Microsoft, or Amazon just 6-months earlier or later?

The ability to ignore short-term noise and focus on long-term evidence is what separates the willing losers from the alpha harvesters.