Imagine you are drafting an initiation note for a mid-cap Indian pharmaceutical firm. You have gathered a peer group of ten similar companies, but as you calculate their P/E ratios, you notice that one company has an anomalously high multiple due to a one-time litigation settlement that depressed its earnings, while another has a rock-bottom multiple because of a massive, non-recurring divestment gain.
Relying on a simple arithmetic mean would lead you to an inflated or deflated sector average, potentially skewing your valuation of the target stock. This is why professional research analysts look beyond the mean and employ the median to anchor their valuation models.
Statistical analysis of peer groups is the process of filtering data to identify the ’typical’ market sentiment toward an industry. The mean is sensitive to extreme values, or outliers, which are common in volatile Indian market sectors like infrastructure or textiles. In contrast, the median represents the middle value of your data set, effectively ignoring the noise created by these statistical extremes.
By utilizing both, you can gauge the skewness of your sample—a high gap between the mean and the median often signals that the sector is dominated by a few exceptionally valued performers, rather than reflecting broad industry health.
Consider an analyst valuing a cluster of Indian NBFCs. If the mean Price-to-Book ratio is 4.5x but the median is 2.8x, the analyst must investigate if the higher-than-average mean is driven by a market darling with high growth expectations or if it is merely a data distortion. If the majority of firms trade near the median, then that 2.8x becomes a far more reliable benchmark for your DCF or relative valuation exit multiple.
Using both metrics allows you to build a ‘valuation corridor’—a range of values that accounts for market irrationality while staying grounded in the reality of the majority of the peer set.
Ultimately, your goal as an analyst is to avoid being misled by the ‘average’ if the average does not represent the industry’s consensus. When your model’s output for a target company aligns with the median, your recommendation gains credibility because it is tethered to the industry standard. Relying exclusively on one statistical measure is a tactical error that can undermine your entire investment thesis during a committee review or client presentation.
Nuance
Check Your Understanding
An analyst is valuing a cement manufacturer and observes that the P/E mean of the peer group is 35x, while the median is 22x. What is the most appropriate next step for the analyst?
Which of the following describes the advantage of using the median over the mean when performing relative valuation of a highly volatile sector?
This is a companion read for Section 10.8 — Assets based Valuation Matrices from PASS Research Analyst Certification Examination by Akhilesh Gururani, available on Amazon Kindle.
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