Fundamentals and Purpose
The analysis of Current P/E vs. Historical P/E is a relative valuation technique based on one of the most powerful and persistent principles of financial markets: Mean Reversion. Unlike absolute valuation models (like Discounted Cash Flow), this model does not attempt to calculate how much money the company will generate in the future, but rather to determine whether the market is valuing those cash flows with optimism or pessimism compared to its own past.
The underlying philosophy is that the valuation of a mature and stable company tends to oscillate around a central average over time. Investors often overreact to good news (expanding the P/E multiple) and bad news (contracting the multiple).
This model serves as a barometer of Market Sentiment. Its purpose is to identify opportunities where a quality company is trading at an unjustified discount relative to its "normal" valuation, or to warn about dangerous overvaluation when the price has detached from historical reality. It is a favorite tool of Contrarian investors and those seeking "Quality at a Reasonable Price" (QARP).
Components and Calculation Mechanics
This model compares the current valuation multiple with the average of that multiple over a significant period (usually 5 or 10 years).
Key Formulas
To apply this model, we must first establish the two base variables and then the deviation ratio.
1. Current P/E (TTM or Forward):
2. Historical Average P/E:
(Where n is usually 5, 7 or 10 years to capture a complete economic cycle)
3. Relative Valuation Ratio:
The Logic of Interpretation
Ratio < 1.0: The stock trades at a discount relative to its history. (Possible Undervaluation).
Ratio = 1.0: The stock trades at its historical "fair value".
Ratio > 1.0: The stock trades at a premium relative to its history. (Possible Overvaluation).
The goal is to buy when the downward standard deviation is significant (e.g. current P/E is 20% below average) and sell or hold when it returns to the mean.
Practical Application and Use Cases
The process involves normalizing data to avoid distortions from extraordinary events and then looking for divergence.
Use Case: The Consumer Giant "Stable S.A."
Imagine a leading food company, Stable S.A., known for its predictable revenues.
Data:
Current market price: 80 €
EPS (Last 12 months): 4.00 €
Average P/E over the last 5 years: 25x
1. Current P/E Calculation:
2. Comparison and Deviation: The market has historically paid 25 times earnings for this company due to its safety. Today it pays only 20 times.
3. Target Price Estimation (Regression Value): If we assume the company will recover its historical valuation (mean reversion):
Decision: The stock offers a 20% discount (implied margin of safety) relative to its own historical valuation. If the business fundamentals haven't changed, it's a strong buy signal based on the temporary contraction of the multiple.
Methodological Criticism and Limitations
Although it's a powerful tool for Market Timing in quality companies, historical analysis has dangerous pitfalls if used blindly.
The Value Trap
The most serious risk is assuming that the past always predicts the future. If the current P/E is low (e.g. 10x) compared to historical (e.g. 20x), it might not be an opportunity, but a signal that the business has deteriorated structurally. If growth prospects have permanently decreased, the company deserves a lower P/E. Buying here would be falling into a value trap.
Comparison with Absolute Valuation (Graham/DCF)
| Characteristic | Historical P/E (Relative) | Graham / DCF (Absolute) |
| Reference | Past behavior of the stock itself. | Accounting fundamentals or future cash flows. |
| Strength | Excellent for high-quality companies (Moat) that are never "cheap" according to Graham. | Better for determining real liquidation value or profitability. |
| Weakness | Fails if there are structural changes in the business. | Can be too conservative in bull markets. |
| Utility | Detect entry and exit timing. | Detect solvency and safety. |
The historical model assumes the market was right in the past average, which is not always true.
Frequently Asked Questions and Investor Adjustments
What time period should I use for the average? A minimum of 5 years is recommended, but ideally 10 years. A shorter period could be biased by a recent bubble or temporary crisis. Using 10 years helps smooth economic cycles.
How to treat years with negative or extremely high P/E? If the company had a loss year (negative P/E) or earnings close to zero (P/E of 500x), this data distorts the average.
Adjustment: Remove outliers or use the Median of P/E instead of the Arithmetic Mean. The median is much more resistant to extremes.
Does this model work for high-growth technology companies? It's difficult. High-growth companies (Growth) often see natural compression of their P/E as they mature. Amazon traded at a P/E of 100 years ago; expecting it to return to that average today would be a mistake. For these companies, the PEG ratio (Price/Earnings to Growth) is more appropriate.
The Final Verdict: When to Use It?
The Current P/E vs. Historical P/E analysis doesn't tell you if a company is solvent, but it tells you if it's "on sale" according to its own standards.
You should use this model if:
You're evaluating "Blue Chip" companies or sector leaders with lasting competitive advantages (e.g., Coca-Cola, J&J, McDonald's).
The company has suffered a price drop due to temporary news that doesn't affect its long-term business model.
You want to avoid buying at the peak of euphoria; comparing with the historical P/E maximum warns of multiple contraction risk.
It's the perfect tool to answer the question: "I like this company, but is this a good time to buy it?". While Graham and DCF tell you what to buy, Historical P/E helps you decide when to do it.
