One may be forgiven for thinking that the investment profession and navel gazing have little in common. Funnily enough, the reverse is true. The recognition that measurements of performance are statistics leads to an appreciation that each data point must be seen not as an exact number but rather as a “good approximation” of the number.
Three major factors affect the numbers that are intended to measure investment performance. First, “sampling error” is the likelihood that the numbers do not accurately represent the facts. Given a specific time period, the performance data may not be a representative sample of the manager’s style and ability. Second, market conditions may have been highly favourable or against the investor during the period of measurement. Third, do the numbers capture luck or skill? Nassim Taleb suggests it would require more than 50 years of observations to conclusively infer that even 3 percent incremental annual return is the consequence of superior investment skill rather than dumb luck!
Performance measurement has meaning only when seen in relation to a clear and explicit investment policy. However, seen in this context, there are a number of practical problems with a quantitative assessment of investment performance. Importantly, while past patterns are typically our best available guides to likely future patterns, the future is bound to differ significantly from the past. Further, mean reversion acts as a powerful drag on corporate performance and valuation metrics. Not surprisingly, the extent of “drift” in these relationships is far less for large, established companies as compared to the smaller companies. So, portfolio composition matters a great deal over time but not in the short run. Equally, just one or two decisions — perhaps remarkably skilful, perhaps plain lucky, maybe both — can make a huge impact on portfolio performance in a given period. Last, but certainly not the least, the choice of starting date and ending date is something to watch out for.
Given these quirks, the numbers typically lead users of the data to think counter-productively. It is more helpful to figure out whether the investment manager “does as he says”. Is the basis for investment behaviour consistent with common sense? Most often, these “soft” cues act as a leading indicator of the performance trends highlighted by the “hard” data.
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(This story appears in the 24 September, 2010 issue of Forbes India. To visit our Archives, click here.)