A calendar that offers a forecast for every day of the coming year is not uncommon in Chinese households. I don’t often hear references to the calendar on most days. But every now and again I would hear my mom marvel, “Oh that calendar was right on for today!” In investing, there is also particular penchant for prediction at the beginning of the year. The start of a new year means we have put the previous one behind us, and knowledge of what the coming year will bring will be helpful.
But rarely do people look back to see whether those forecasts actually panned out…except, of course, on the rare occasions when some did materialize. As an example, “Why 2017 could be the year stock pickers regain their edge,” was published in early 2017. Among the many predictions used to justify a “stock pickers’ market” were: inflation should rise, interest rates should rise, value stocks will do well, correlations will be low and dispersion will be high.
Many of these just did not happen in 2017; inflation remains tame, the 10-Year Treasury rate barely budged year over year, value did not make a comeback and dispersion was lower on average in 2017 compared to 2016.
One prediction, however, did happen. Correlations were lower on average in 2017 compared to 2016, and this is a commonly used justification for a better stock pickers’ market. Unfortunately, it is dispersion that defines the opportunities available for outperformance—and SPIVA data show that the lowest dispersion environments correspond with the worst manager performance).
More Managers Underperformed in Low-Dispersion Environments
In contrast, active managers are no more likely to outperform when correlation is low than when it is high.
Correlation Had No Significant Influence on the Outcome of Manager Performance
Undoubtedly, more predictions will be forthcoming for 2018 and likely, many will be the same ones that were made for 2017. But at least if we come across the one about low correlations we can check it off the list because it is irrelevant to the outcome of active performance.