Why P/E ratios mislead more often than they illuminate

A P/E ratio is a number, not a story. The trap most students fall into in their first month of trading is treating the number as if it's a verdict.

The mechanic

Price-to-earnings (P/E) is the ratio of a company's current share price to its earnings per share over the trailing twelve months. If a stock trades at \$100 and the company earned \$5 per share last year, the P/E is 20. The intuition: at this price, you're paying for 20 years of last year's earnings.

That intuition is partly true and very misleading.

Why it misleads

1. Earnings are an opinion, price is a fact. Earnings depend on accounting choices — depreciation schedules, R&D capitalization, one-time write-offs. Two companies with identical underlying economics can report very different earnings depending on how aggressive their accounting is. P/E embeds all of that opinion into the denominator.

2. The "E" looks backward; the "P" looks forward. Trailing-twelve-month earnings tell you what already happened. The stock price tells you what the market expects. When earnings are growing fast (technology, biotech, early-stage anything), a high trailing P/E often just reflects the market's correct forecast that next year's earnings will be much higher. Calling Nvidia "overvalued" in 2023 at a P/E of 50 missed the point — the market was right that earnings would 5× by 2025.

3. The "E" can be negative. Loss-making companies have no meaningful P/E. The metric breaks at exactly the moment you'd most want a valuation discipline (early-stage growth, turnarounds, deeply cyclical troughs).

4. Different industries justify wildly different P/Es. A utility with regulated 4% earnings growth deserves a P/E of 15. A SaaS company growing 40% deserves a P/E of 50. Comparing them by P/E is like comparing two people's hourly rates without asking what they do.

When P/E is actually useful

P/E works best when you're comparing similar companies within the same industry at the same point in the cycle, AND when earnings quality is roughly comparable. Two Mauritian banks with similar loan books, similar regulatory exposure, similar deposit franchises — comparing their P/Es tells you which one the market currently prefers and how much premium it's assigning.

It also works as a sanity check on your own forecasts. If you've built a discounted cash flow model that implies a P/E of 80 on a slow-growing utility, you should suspect your forecast before you suspect the market.

A better mental model

Replace P/E with two questions:

1. What does the market currently expect this company to earn five years from now? (Imply the growth rate from the price.)
2. Is that expectation aggressive, conservative, or about right based on what I know? (Compare to your own forecast.)

If the market expects 8% earnings growth and you think 15% is likely, the stock is undervalued whether the P/E is 12 or 40. If the market expects 30% growth and you think 10% is realistic, the stock is overvalued at any P/E.

Try this in the simulator

1. Pick three companies in the same sector. Look up their current P/Es.
2. For each, write down what earnings growth you'd need over the next five years to justify the current price. (Use the rough rule: P/E ≈ 1 / (cost of equity − growth rate).)
3. Compare your numbers to the consensus analyst estimates on a free site like Yahoo Finance.
4. Where do you disagree with consensus? Place a paper trade on your highest-conviction disagreement.

What you should remember

P/E is a starting point, not an endpoint. The students who do well in this course are the ones who use it as a question generator ("why is this one cheaper?") rather than as an answer ("therefore buy / sell").

Next lesson: Risk vs. uncertainty — why most "risk management" courses teach the wrong concept and what to do instead.