#longitudinal analysis

[procurement-insights]

A hypothetical 30-year trajectory built from public data. A practitioner who lived it. The graph matched. The inflection point matched. The mechanism matched. That's RAM 2025.

RAM 2025: When a 30-Year Hypothetical Matches Lived Experience

[frankluengo]

Longitudinal analysis: A long look backward

I have had several discussions with peers on whether you can value a security just using ratios. My view is that ratios can help you triangulate price, but you need an estimation of future cash flows to come up with a reasonable estimate first. People love P/E ratios specifically, but if you do not try to test the ratio with other data, you may be in for a surprise.

This is where longitudinal and cross sectional analysis can provide you with a much better use of ratios than just looking at a company's current P/E. Longitudinal analysis in particular, can tell you how the market has priced a particular security over a long period of time. If your hypothesis is that the market is unusually bearish on a stock, you can look at historical prices to test your hypothesis.

Consider the following example of a tourism firm I evaluated a few months ago. At first I noticed that the firm had a very low price to book value, so I wanted to see how it had been priced historically:

The graph above has three data series, all over the same 10 year period. The green bar shows the historical price to earnings ratio. The orange bar is the price to book value ratio, and the solid line is the historical return on equity. What I noticed was the price to earnings fluctuated significantly but that price to book value tended to follow return on equity fairly closely. This told me that price to book was a more telling historical marker than P/E for triangulating fair value.

So, the real question for me was: Is the recent low return on equity the new reality for the firm, or will there be a reversion to a previous mean? Are current investors right to depress the stock price due to a loss or competitive advantage, or were they unusually pessimistic due to recent events?

It is critical that you have a good hypothesis for this. Some companies, such as tobacco, show low valuations because of secular changes in the market and are unlikely to bounce back to a historical mean.

This result was counter intuitive for me but it is a reminder that one ratio does not tell a story. Only by looking at all available data can you come up with a clear picture.