Investing And The Deceptiveness of Data

Updated on


The table above contains primary data that is typically used for peer/relative valuation purposes. The idea is that by comparing the metrics between companies of the same industry, one can approximate how much a similar company should be worth by applying a similar multiple.

An analyst’s job is to find a suitable multiple under this slew of numbers that best fits the industry, but even in the course of such a relatively simple process, there is room for deception and pushing of vested interest. Any high schooler will be to tell you the 3 statistical measures of central value – Mean, Median, Weighted-Average. Unfortunately, we often take for granted that statistics are best applied under the law of large numbers, something that we usually do not have the luxury of when it comes to investment research. The number of listed companies in a similar industry and market is usually only a handful. Statistical tools can only be crudely applied to investment research at best.


As you can see, depending on the measure of central value used, the swing in valuation can be more than double. One can justify almost any call on a stock with such a tremendous range. When you realise that this is one of the simplest form of valuation and usually the most straight forward part of a research report, just imagine how much else can be manipulated.

This is not to say that research reports are totally useless and unbelievable. I would like to think that the majority was written objectively and for better or for worse, more complex forms of valuation are also often used in conjunction with peer valuation. I would argue that the mind set in reading such reports is the most important and I personal adopt a mentality of askance.

If there is anything I learnt from this, it is the following. We know the flaws of absolute valuation (DCF etc.) and peer valuation is by no means perfect, but what is most important is that they collectively serve as a check and balance. When they contradict significantly, it is time to rethink and re-evaluate your numbers with some common sense.

Leave a Comment