But problems arise when we outsource our lack of conviction in an investment, such as a factor or a style, to its time series. In the lingo of finance academics, this is the difference between having a Bayesian prior (and informing it further with available data) and not having a prior, whatsoever, on which to base educated investment decisions.3
Nonprofessional investors can be forgiven for taking this unfortunate shortcut. They do not have the knowledge base advisors do, which can lead them, understandably, to believe that the “proof is in the pudding” in terms of performance, as it is with many things in life. (To be clear, this observation is not a slight to nonprofessional investors—even the most skilled of experts can fall prey to behavioral fallacies and knowledge gaps.) Obviously, not everyone can, or should, be a professional investor. Job specialization is very necessary, as you and I likely have little desire to build our own car or perform our own surgery. But those of us who do make our living as well-trained and well-intentioned overseers of capital, including financial advisors, can and must recognize the dangers of short-term performance measurement.4 The most evident way to combat this peril is to develop investment beliefs informed by, but not solely derived from, data.5
The reality, however, is that performance measurement often leads us to now-cast—a combination of “now” and “forecast”—which presumes that the near-term future will look an awful lot like the near-term past. The human brain loves a good way to make sense of an uncertain future, and where better to look than in the readily available past. Blindly relying on recent performance to infer a lasting future trend is fraught with danger.