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Joseph Wilkins is a funds correspondent at FTAdviser.
Look at this graph. Soak it in:
Bank of America frequently updates this futile but oddly charming mosaic, showing the best-performing assets each year since the turn of the century. Besides resembling the stretched hide of Elmer the Patchwork Elephant, its eldritch title is also eye-catching.
The Asset Class Quilt of Total Returns is so obviously a World of Warcraft item that we could almost believe the analysts are having us on — almost. Here it is, anyway, gamers:
Now, let’s get practical. Using only the quilt, which asset class do you think has made the most money for investors since 2000?
If you guessed the navy square (S&P 500), congratulations! And if you didn’t get it right, we can hardly blame you — compound percentages are hard, as is . . . everything else about the quilt.
We’ve attempted to create an equally-pointless-but-considerably-duller chart that shows how some of the same assets would have performed cumulatively if an investor had bought them on 1 Jan 2000 and held on to them since. Ta da:
Perhaps the real lesson amid BofA’s Paul Klee-esque effort is this: it’s really, really hard to time the market.
No tile has outperformed the other tiles consistently enough to appear a clear winner, and some serious portfolio rebalancing would be required to yield consistent alpha year-on-year. Not only is predicting the future really hard, it’s also really expensive.
Is there a way around this? In a recent note, Citi analysts write:
For many investors when they hear the words ‘style rotation’ and ‘tactical’, a hint of skepticism emerges. Style rotation is often considered the ‘holy grail’ of systematic investing — easy to say but hard to do. Either the live trading results don’t hold up or transaction costs erode performance. However, this doesn’t mean investors should give up on this endeavor, and having a style allocation framework can aid investors in making tactical decisions.
Handily, they have a solution! Espousing the benefits of their ‘style rotation’ bot, they wrote:
Adapting to market shifts, our tactical style allocation model, introduced in 2017, continues to exhibit out-of-sample performance gains. In some regions, risk adjusted performance has become more challenged, but overall, the model shows continued efficacy in outperforming a benchmark 1/N style allocation strategy.”
Exciting stuff. Although if you’re reaching for an expenses form already, it pays to read the kicker:
Implementation practicalities however do pose a sizeable headwind in replicating the same results in practice.
Markets: still hard.
Further reading
— Axes of Evil
